• automation
    LinkedIn推出AI招聘助手：重新定义未来招聘流程 LinkedIn Enters AI Agent Race With LinkedIn Hiring Assistant LinkedIn推出了首个AI Agent : Hiring Assistant，旨在帮助招聘人员重新成为招聘人员。 LinkedIn于本周推出了全新的AI招聘助手，这款工具旨在自动化招聘过程中高达80%的工作，特别是候选人筛选和招聘前的步骤。通过与LinkedIn平台的无缝集成，这款助手不仅提高了招聘人员的工作效率，也显著提升了候选人的质量。该工具的“体验记忆”和“项目记忆”功能，可以记录招聘人员的搜索和操作习惯，并将所有与招聘项目相关的信息进行整合，从而智能化地优化招聘流程。 这款助手已经在西门子、Canva等公司的招聘流程中得到了应用，这些公司报告称，通过LinkedIn招聘助手，招聘人员的生产力显著提升，候选人质量也得到了极大的改善。招聘前的AI辅助搜索仅需30秒即可完成，而传统的搜索通常需要15分钟。 LinkedIn招聘助手还通过AI驱动的沟通功能改善了候选人的体验。数据显示，使用AI辅助发送的招聘信息的接受率提高了44%，接受速度也加快了11%。此外，AI搜索的候选人接受率高出18%。 随着越来越多的公司采用AI技术，招聘与候选人之间的竞争日益加剧。求职者也在利用AI工具优化简历，甚至在面试中使用AI辅助表现，从而使HR在筛选候选人时面临更多挑战。因此，LinkedIn招聘助手等工具正成为招聘人员不可或缺的助手。 LinkedIn招聘助手不仅仅是提高效率的工具，它真正的价值在于解放招聘人员，使他们能够专注于与候选人和招聘经理的对话，改善雇主品牌，并更好地了解就业市场。这种转变反映了人才获取的战略性转变——从执行角色转变为人才顾问，帮助公司更好地实现增长。 详细请看Josh Bersin 写的这篇介绍 As I discussed in the article Digital Twins, Digital Employees, Agents Everywhere, tech vendors are creating AI-powered Agents as fast as they can. And in HR, where we deal with hundreds of mundane checklist-types of processes, the opportunity for automation is everywhere. This week, just as Microsoft launched a tools to help companies build Agents in Copilot, LinkedIn announced its Hiring Assistant. And this is a pretty amazing product. The Hiring Assistant is the first highly-integrated agent I’ve seen that fits right into the LinkedIn workflow. And the companies using it now (Siemens, Canva, AMS) are seeing recruiter productivity and candidate quality skyrocket. Here’s how to think about it: consider a schematic of the recruitment workflow. As you can see, there are more than 30 steps to complete, and this doesn’t even include background checking, offer-letter generation, benefits discussions, pre-boarding, and onboarding. With this brand new Assistant LinkedIn believes they can automate almost 80% of this pre-offer workflow. And the LinkedIn Hiring Assistant is just getting started. Here are some screenshots of the workflow: As you can see, the agent prompts the recruiter with intelligent responses and questions along the way. And throughout the process it stores more and more information to get smarter and smarter. This Is A Sophisticated Product This is a well-engineered product. Not only does it include many subtle features (ie. “find me a candidate like Joe,” which brings in Joe’s profile and analyzes Joe’s role, skills, and experience), it includes several platform innovations. The first is something LinkedIn calls “Experiential Memory,” storing the recruiter’s search and activity history for future work. The Hiring Assistant learns what this recruiter is doing, how they communicate, and how they operate, to tune its results to each recruiter’s needs (ie. a tech recruiter vs. an executive recruiter). Second is a feature called “Project Memory,” which brings together all the information about a single search project. This means the candidate selection criteria, emails, and input from hiring managers are stored in the project, enabling the assistant to see the whole experience of selection. Recruiters understand this challenge: every hire and every hiring manager is different, and each project has unique and sometimes new requirements which have nothing to do with the job description. Other Agents Will Have To Take Notice LinkedIn is not the first mover in this space, but the company’s credibility will accelerate the market. Paradox, the current leader in recruitment automation, has been automating high-volume recruiting for almost a decade and offers an agent that not only helps recruiters but also supports job seekers. It isn’t focused on sourcing liked LinkedIn, but it automates the rest of the process (candidate inquiries, interview scheduling, assessment, onboarding). And it really works: this week Chipotle announced that Paradox’s solution reduces time to hire by 75%, making it a central part of the company’s growth strategy. LinkedIn Hiring Assistant is receiving similar accolades. “Doing a normal search before AI took upwards of 15 minutes. Now, with AI-Assisted Search, it takes about 30 seconds to get results. The time saved is tremendous. It is so much more convenient and easier doing it this way,” said Victoria Östryd Söderlind, Senior Recruitment Specialist, Toyota Material Handling Europe.  “The AI features on LinkedIn have allowed our recruiters to do more, to be better and to grow faster in all of our activities. It’s about spending time in the right places where our time is more valuable and LinkedIn’s AI features have enabled us to do that. What it’s not doing is removing great conversations with candidates, stopping our ability to ask them questions or getting to know candidates as people and humans,” said Olivia Brown, Head of Talent Acquisition, Octopus Energy. Improving Candidate Experience While LinkedIn talks about the value to HR, the bigger value may be for candidates. The company found that AI-Assisted outreach messages generate a 44% higher acceptance rate and are accepted 11% faster by job seekers. And AI-based searches produce 18% higher candidate acceptance. As Paradox has discovered, candidates don’t like to waste time scheduling calls with recruiters if they can avoid it. And that leads to another important issue. There is now a growing AI battle between recruiter and candidates. AS AI helps recruiters source and screen candidates, the candidates are using AI to “power-up” their resumes. One of our clients told me that almost all their job applicants now submit resumes that look eerily similar to job descriptions. Why? Job candidates are using AI also! This means is that tools like LinkedIn Hiring Assistant are more essential than ever. As job seekers tweak their identity and even use AI interview assessments to game interviews, HR has to beef up its tools to better differentiate candidates. Liberating Recruiters To Recruit And Advise The big story is actually this: while Hiring Assistant is an efficiency tool, what it really does is free up recruiters to talk to candidates. Recruiters who are bogged down with drudgery can talk with hiring managers, improve employment brand, and get to know candidates and the job market better. This is part of what we call Systemic HR: moving talent acquisition away from the “fulfillment center” role to that of a talent advisor, helping the company think about its best ways to grow. As you look at these tools and think about automation, I encourage you to read our new research on the strategic shift in talent acquisition. Automation is not just about productivity and cost savings: it’s really about liberating our minds to think and add value in new and exciting ways.
    automation
    2024年10月29日
  • automation
    美国2025年HR发展趋势：数字员工与未来工作场景，大选带来的可能影响 2025年，HR领域将面临前所未有的变革，技术、社会、政治因素共同推动着工作场所的迅速转型。随着AI、数字孪生体、智能代理等技术的加速发展，HR从业者必须应对不断变化的工作环境。与此同时，政治变革，如特朗普有可能在大选中回归执政，将带来政策的不确定性，影响劳动力市场和企业的运营。在这一背景下，HR需要更加灵活、创新和前瞻性。以下是2025年HR发展的八大趋势： 1. 数字员工的全面普及 数字员工、数字孪生体和智能代理将在企业中迅速普及，成为HR团队的重要组成部分。通过AI驱动的自动化，HR能够更高效地处理招聘、员工管理、数据分析等任务。比如，数字员工将帮助筛选简历、安排面试、甚至进行员工培训。这不仅能提高HR的工作效率，还将使HR从繁琐的日常事务中解放出来，专注于更具战略意义的任务，如人才保留和文化建设。 2. 远程工作与混合办公的进一步常态化 远程工作在全球大流行后逐渐成为常态，2025年这种模式将进一步成熟和优化。HR将需要设计更好的政策来管理远程和混合工作的员工，包括技术支持、绩效评估和团队协作。尤其是在政治环境可能受到影响的情况下，如特朗普重回白宫可能带来的政策变化，公司需要更灵活的劳动力管理方式，以应对政策的不确定性和跨州的不同规定。 3. 多元化与包容性在政治压力下的挑战 随着可能的政治环境变化，多元化与包容性可能面临更大的挑战。特朗普回归可能带来对劳动力市场的管制和移民政策的收紧，这将直接影响到HR对全球化人才的招聘。HR需要更加积极地维护职场的多样性与包容性，创造一个公平、包容的工作环境。这也意味着企业需要加强文化敏感度培训，确保在更具分裂性的社会氛围中维护公司内部的和谐。 4. 数据隐私与合规性管理的复杂性增加 随着数字员工和智能代理的使用，企业对员工数据的收集和使用将大幅增加，这对HR的隐私和合规管理提出了新的挑战。特别是在美国，如果特朗普再次执政，劳工和数据保护政策可能会有显著变化。HR需要更加密切关注新的法律法规，确保数据的收集和处理符合各州和联邦法律的要求，并保持透明的沟通以赢得员工的信任。 5. 技能提升与终身学习成为HR焦点 2025年，技能差距问题将进一步凸显，尤其是在技术快速发展的背景下。HR需要与培训和学习部门合作，设计持续的技能提升计划，确保员工能够掌握最新的技术和工作方法。随着AI和自动化工具的普及，员工需要具备更高层次的技术技能和问题解决能力，HR也将更多地参与人才的技能重塑，确保企业在竞争中保持优势。 6. 心理健康与员工幸福感得到更多关注 心理健康已经成为HR的重要议题，2025年这一趋势将继续深化。随着技术和远程工作的普及，工作与生活的界限日益模糊，HR需要关注员工的心理健康，提供相关支持。这不仅涉及到心理健康资源的提供，还需要通过文化建设和员工关怀政策来提高员工的幸福感。随着美国社会可能面临的政治分裂和不确定性，HR需要积极缓解由此带来的员工焦虑。 7. 劳动力市场的多代际管理 2025年，劳动力市场将由多代人组成，包括婴儿潮一代、X世代、千禧一代以及Z世代。不同代际的员工有着不同的工作方式、价值观和技术适应度。HR必须设计灵活的工作政策，平衡各代员工的需求，特别是在招聘、工作模式和员工发展上。同时，AI和数字员工的崛起将进一步重塑这些代际的工作方式，HR需要帮助员工适应这种新常态。 8. 政治环境对劳工政策的影响 如果特朗普在2024年大选中获胜，其政府可能会实施更严厉的劳工政策，影响薪酬、福利、移民和就业法律等方面。 HR需要随时了解政府的政策变化，确保公司运营合规，并积极调整劳动力管理策略。未来几年，美国的政治环境将对企业运营和HR的日常工作产生深远影响，因此HR必须具备应对快速政策变化的灵活性和适应性。 结语 2025年，HR将在技术变革和政治环境变化的双重推动下，面临前所未有的机遇和挑战。数字员工的普及将为企业提供更高效的工作方式，但HR也必须重新思考如何在人与技术之间找到平衡，维护企业文化和员工福祉。在不确定的政治环境中，HR需要具备敏捷性和创新精神，帮助企业在复杂多变的环境中实现可持续发展。
    automation
    2024年10月20日
  • automation
    2025年HR领域的6大关键趋势：迎接未来工作的变革 随着技术的进步和员工期望的不断变化，2025年的人力资源管理将面临前所未有的挑战和机遇。以下是六大关键趋势，它们将推动未来职场的发展： 1. 远程和混合办公模式的普及 远程和混合办公已成为员工最期待的工作形式。2025年，更多企业将采用灵活的工作安排，不仅能提高员工的满意度，还能减少运营成本。HR团队需要确保远程员工享有与办公室员工相同的支持和资源。 2. 人工智能（AI）深度融入HR流程 AI技术正在快速改变HR流程，如招聘和绩效管理。2025年，AI将更加普及，帮助HR自动化日常任务，并提供数据洞察以优化决策。但企业在使用AI时必须保持透明，定期进行偏见审查。 3. 强调员工健康和心理健康 员工心理健康在疫情后成为企业的首要关注点。到2025年，企业将进一步加大对员工健康的投入，如提供灵活的工作安排、心理健康资源等，以提高生产力并减少员工流失。 4. 多样性、公平性和包容性（DEI） DEI是未来工作的核心。2025年，更多公司将推进多元化招聘和公平政策，培养包容性的企业文化，以推动创新和更好的决策。 5. 技能提升与再培训 技术的快速发展导致技能过时的速度加快。到2025年，50%的员工需要再培训。企业将需要投资于员工的持续学习计划，以确保其技能与未来工作需求匹配。 6. 人才分析的兴起 人才分析通过数据驱动决策，使HR能够更有效地管理员工并优化业务成果。2025年，企业将加大对数据工具的投入，提升HR决策的科学性和精准性。 2025年，企业若能掌握这些趋势，将在未来职场中占据竞争优势。
    automation
    2024年10月19日
  • automation
    Workday签署最终协议收购Evisort，这是一家AI原生文档智能平台 Workday宣布收购Evisort，这是一家AI原生文档智能平台，此举旨在提升Workday在财务和HR数据管理领域的能力。Evisort利用先进的AI技术，从复杂的法律和商业文件中提取清晰、可操作的见解，帮助企业优化支出、增加收入、降低风险并管理义务。通过此次收购，Workday的客户将能够更高效地挖掘数据价值，加速业务决策和行动。 Evisort的平台使用户能够快速从合同、发票和政策文件等非结构化数据中提取信息，自动化流程，发现错误或缺失信息，并做出更明智的业务决策。例如，客户可以利用Evisort的AI技术更快地理解合同条款，优化文件创建过程，并确保利益相关者了解审查情况和必要的行动。 此次交易预计将在Workday 2025财年第三季度结束前完成，需满足惯常的交割条件。Workday表示，这次收购将帮助公司实现其愿景，即帮助客户从最重要的数据中释放更大的价值。 Evisort的AI驱动文档智能平台将使Workday客户能够更快、更高效地从大量的财务和HR数据中获取关键洞察并采取行动 拉斯维加斯，2024年9月17日 -- Workday公司（纳斯达克股票代码：WDAY），一家致力于帮助组织管理人力和财务的领先解决方案提供商，今天宣布已签署最终协议，将收购Evisort，一家领先的AI原生文档智能平台。通过此次收购，Workday将在其财务和HR套件中引入AI驱动的文档智能解决方案。 超过80%的业务数据是非结构化的，组织方式不利于搜索、分析或行动，包括合同、发票和政策文件中的数据。通过Evisort强大的AI功能，Workday将帮助客户从这些未开发的数据中获取关键洞察，以便更快地做出关键业务决策和行动。 Evisort是一家在文档智能领域受信任的AI领导者和先锋。该公司的平台利用AI技术，从存储在文档管理系统中的复杂法律和商业文件中提取清晰且可操作的洞察。大型组织使用Evisort分析整个企业的文件，挖掘重要信息，帮助他们减少支出、增加收入、降低风险和管理义务。 “组织坐拥海量数据，但由于搜索和分析过于复杂和耗时，往往无法发挥其全部潜力。”Workday首席财务官办公室集团总经理Terrance Wampler表示。“Evisort将帮助我们实现帮助客户解锁最关键数据价值的愿景。借助AI驱动的文档智能功能，客户将能够更快、更高效地获取并行动在这些洞察上，保持在当今快速变化的商业环境中的领先地位。” “AI是一股强大的力量，正在转变组织将文件中的非结构化数据转化为战略性业务决策的方式，”Evisort创始人兼首席执行官Jerry Ting表示。“我们很高兴将Evisort的文档智能技术与Workday的统一财务和HR平台相结合，这将使客户能够更有效地利用关键业务数据，在一个单一的真实系统内工作。” 通过Workday和Evisort的文档智能解决方案，客户将能够将非结构化数据从文档管理系统引入Workday，帮助客户更高效、智能地管理人力和财务流程，包括： 获取更准确的数据。 客户将能够在几秒钟内从业务文件中提取并转移数据，且更加准确和自信。这包括直接从文件中提取财务和运营细节以自动化下游流程，揭示错误或缺失信息，以及搜索支付条款等详细信息。 通过自动化驱动对齐和行动。 客户将能够使用强大的AI帮助员工更好地理解合同，简化文件创建过程，并让利益相关者了解审查和必要的行动。 做出更明智的业务决策。 客户将能够最大限度地利用业务文件，通过通知有利条款和条件以及建议的行动来提升决策效果。 Workday与Evisort：AI驱动的文档智能，打造变革工作场所 Workday将在各种应用场景中提供Evisort的AI驱动文档智能解决方案，帮助团队更好地实现目标并重塑角色，包括： 会计。 会计人员将能够利用AI功能快速导航业务文件，如收入合同、供应商发票和资产协议，更有效地阅读、转换、匹配和记账。例如，对于收入合同，会计人员将收到合同错误的警报，获得收入确认时间表的建议，并在合同续约时得到通知。 采购。 组织将利用这些AI驱动的解决方案提升供应商合同谈判和合同风险管理活动。这将推动降低支出机会，支持合规，并帮助减少风险。例如，采购专业人员将能够识别现有供应商协议中的未声明利益，并根据历史基准评估合同语言以指导谈判。这将有助于保护利润并防止不必要的风险。 员工知识库。 员工将能够更快速地访问有关HR和财务政策（如福利和费用）的信息，从而减少获取关键员工信息的时间。例如，员工将能够使用AI聊天机器人简单提问，并获得即时答案和参考支持文档。 关于Evisort收购的详情 该交易预计将在Workday的2025财年第三季度结束（2024年10月31日）前完成，需满足惯常的交割条件。Orrick律师事务所担任Workday的法律顾问，Goodwin律师事务所担任Evisort及其股东的法律顾问。 关于Workday Workday是一家领先的企业平台，帮助组织管理其最重要的资产——人力和财务。Workday平台以AI为核心，帮助客户提升人力、提升工作效率，并推动业务持续发展。全球超过10,500家组织在使用Workday，包括中型企业和超过60%的《财富》500强公司。有关Workday的更多信息，请访问workday.com。 © 2024 Workday, Inc. 保留所有权利。Workday及其标志是Workday公司的注册商标。所有其他品牌和产品名称是各自所有者的商标或注册商标。 关于Evisort Evisort的AI原生合同智能平台帮助包括微软、Workday、McKesson、BNY Mellon、西联汇款和NetApp在内的知名组织全面了解其合同。Evisort通过先进的专有AI技术——包括第一个专为合同设计的大型语言模型（LLM）——赋能团队更快速、更智能地起草、管理、分析和优化协议，帮助加快交易，减少风险和成本，并将法律和合同挑战转化为战略性业务机会。 前瞻性声明 本新闻稿包含与Workday、Evisort及Workday收购Evisort相关的前瞻性声明。这些前瞻性声明仅基于当前可用的信息以及Workday的当前信念、期望和假设。由于前瞻性声明涉及未来，因此存在固有的风险、不确定性、假设和难以预测的情况变化，其中许多因素超出了Workday的控制范围。如果风险变为现实，假设证明不正确，或者我们经历意外的情况变化，实际结果可能与这些前瞻性声明所暗示的结果有重大差异，因此，您不应依赖任何前瞻性声明。此声明中的前瞻性声明包括但不限于：有关拟议交易潜在利益和效果的声明；Workday对Evisort业务及其能力的计划、目标、期望和意图；以及拟议交易的预期完成时间。风险包括但不限于：（i）交易可能无法按时或根本无法完成的风险；（ii）未能实现交易预期利益的风险；（iii）Workday实施其对Evisort业务及其能力的计划、目标和其他期望的能力，以及我们在我们的HR和财务应用套件中交付AI驱动的文档智能解决方案的能力；（iv）交易公告或完成的负面影响；（v）与收购相关的意外费用或负债；以及（vi）我们向美国证券交易委员会（“SEC”）提交的文件中描述的其他风险和因素，包括我们最近提交的10-Q表格和我们将不时向SEC提交的其他报告，这些文件可能导致实际结果与预期有差异。Workday不承担任何义务，也不打算在本新闻稿发布后更新任何此类前瞻性声明。 本文件、Workday网站或其他新闻稿或公开声明中引用的任何尚未发布的服务、功能或功能均可能会发生变化，且可能不会按计划交付或根本不交付。购买Workday服务的客户应根据当前可用的服务、功能和功能做出购买决策。 来源：Workday公司
    automation
    2024年09月17日
  • automation
    Josh Bersin: 随着经济放缓，关注未来的技能：改变的能力 本周，我们看到美国失业率“上升”到 4.3%，经济学家开始呼吁降低利率。对于那些每天与公司和领导者交流的人来说，我会说我们正经历一个正常的经济周期。 上一次重大衰退（不包括疫情，因为那不是需求放缓）是在2008年和2009年。这意味着我们已经有近16年没有经历严重的经济周期了，几乎是通常周期的两倍。虽然疫情确实让公司放慢了脚步，但我们迅速恢复了。所以从失业率来看，它大致是这样的。 在经历了50年的失业率变化后，目前的失业率比五十年前降低了12%，这让我得出结论，我们正生活在“长期劳动力短缺”中。同时，美国的GDP在此期间增长了1500%。 虽然我们目前的GDP增长可能有所放缓（我认为这是由消费者价格使我们耗尽了支出引起的），但实际上我们只是看到从“工业化、高劳动密集型企业”向所谓的“后工业化”公司的长期转型，这些公司往往需要更少的“工人”和更多高技能员工。（阅读我们的后工业时代研究。） 仍然有大量的小时工工作：护理、医疗、交通、建筑、零售、娱乐、能源和许多其他行业依赖各种类型的“劳动”工人。这些工作随着时间的推移变得越来越自动化，导致工资提高和技能升级，但美国仍有约63%的工人没有大学学位，其中大多数人找到了工作。 虽然每个人似乎对英特尔、UKG, Intuit或其他“与AI相关”的裁员感到有些恐慌，但美国经济的反应良好。我知道许多公司正在试验AI和其他技术，每个公司都担心失去有价值的人才，因为劳动力市场依然竞争激烈。 是的，一些公司会进行裁员。通常这是由糟糕的领导、糟糕的规划或只是对投资者的本能反应引起的。最终，随着出生率保持在低水平，我们仍将面临劳动力短缺，人的价值将继续上升（正如我过去指出的，裁员并非不可避免）。 在过去的三周里，我与欧洲超过20家大公司会面，每家公司都在投资于员工发展、技能再培训、内部流动性和提高生产力的项目。在欧洲，裁员既困难又昂贵，因此公司感受到劳动力短缺的压力，他们仍在投资员工。 至于消费者需求开始下降，我们正面临一个“长期结束”阶段，这是由高价格的延续引起的。消费者对过去五年的高价格感到厌倦，而在此之前，我们经历了近十年的零利率时期，房价和大多数资本品价格持续上涨。现在这两个因素都结束了，我们只是回到了更正常的经济状态。 换句话说，如果你因为“可以”而提高价格，最终你将付出代价，当消费者反抗时。如果你停止投资于员工，他们会“悄然离职”或另寻他处。这些是我认为的“正常商业经济”，我认为我们正看到这种正常性的发生。 作为一个动态组织运营 当然，最大的“趋势”是各行业的数字化和AI革命。汽车制造商被“虚假”引导进入电动车领域，发现混合动力发动机、数字相机和电子产品以及新的购车方式非常具有破坏性。出版商正在找出如何应对AI平台，这次他们保留了自己的知识产权并协商了许可协议。能源公司正在慢慢转向新来源，其他公司都在找出如何实现数字化、AI赋能，并进一步简化我们生产和销售的产品。 这都是商业的“激动人心的工作”，一切都与成为一个动态组织有关。我们的研究指出，以动态方式运营完全是关于人。 经济，通常以周期性变化（通常由过度兴奋和随之而来的疲惫引起）为特征，只是需要应对的事情。对于我这样经历了许多这种高峰和低谷的人来说，当事情不再上升并且我们看到一些冷却期时，我总是感到有点“解脱”。 是的，股市可能会暴跌。它总会在某个时候发生。但那实际上是“众包”效应，通常与我们的公司无关。如果你照顾好你的客户，投资未来，迅速学习AI和所有新技术，你将顺利过渡。正如许多HR领导本月与我谈到的，你的成功很大程度上取决于人。 未来的技能很明确：推动变革的能力 今天我与一群我们每隔几周就交流的HR领导进行了一次有趣的会议。每一位CHRO和其他领导都告诉我们，他们正在投资于员工的“变革管理”和“业务转型”技能。这意味着什么？ 这意味着这样。虽然我们都希望公司有更多的工程师、制造专家、科学家和销售与营销专家，但我们最需要的“技能”是“推动变革的能力”。这种特定的技能非常复杂，需要时间来学习，并且在当前尤为重要。这引出了我的最后一点。 如果你是图凡·厄金比尔吉，劳斯莱斯的首席执行官，你正处于业务转型的过程中，旨在推动工程效率和卓越，你不仅要担心工程师。你要担心那些能够推动、领导、激励和创造变革的人。我相信，这些就是大家常谈的“未来技能”。如果你作为一个专业人士、经理或领导者真正知道如何“推动和执行变革”，这些经济周期在你的职业生涯中只是“一个小波折”。 在与HR领导交谈超过30年并在许多周期中经营我们自己的业务后，我敦促你“不要过于担心”这些大的经济数据。我们正生活在一个每个公司中每个人的经济价值飙升的时期。投资于你的员工和自己，随着经济的变化，你会做得很好。   https://joshbersin.com/2024/08/as-the-economy-changes-focus-on-the-real-skills-of-the-future/
    automation
    2024年08月03日
  • automation
    101 real-world gen AI use cases from the world's leading organizations 在过去一年半的时间里，生成式人工智能（AI）在企业领域的应用迅速发展。Google Cloud的Next活动中展示了超过300家组织如何利用AI推动企业转型。这些企业已经从简单的问答助手，发展到能够进行预测和采取行动的AI代理，进一步扩展其业务功能和提升效率。 具体来说，AI代理在以下几个关键领域表现出显著的效益：首先是客户服务，AI能够帮助企业更好地理解和满足客户需求；其次是员工赋能，通过自动化日常任务和优化工作流程，AI提升了工作效率；在创意构思和生产领域，AI助力企业快速生成创新的解决方案；数据分析方面，AI通过高效处理和解析大数据，支持决策制定；在编码创建方面，AI简化了开发流程，提高了代码质量；最后在网络安全领域，AI加强了数据保护和风险管理。 这些应用不仅提高了生产力和操作效率，还极大地改善了客户体验和企业的创新能力。AI的多模态能力，即在文本、语音、视频等多种通信模式中的应用，使其能够更全面地满足不同行业的需求。通过这些先进的技术，企业正在开创一个智能、高效和互联的新时代。 我们一起来看看，是否有参考？ Since generative AI first captured the world’s attention a year and a half ago, there’s been a vigorous discussion about what, exactly, the new technology is best used for. While we all enjoyed those early funny chats and witty limericks, we’ve quickly discovered that many of the biggest AI opportunities are clearly in the enterprise. Our customers and partners at Google Cloud have found real potential for creating new processes, efficiencies, and innovations with generative AI. For proof, look no further than the 300-plus organizations who are featured at this week’s Next event in Las Vegas. In a matter of months, organizations like these have gone from AI helping answer questions, to AI making predictions, to generative AI agents. What makes AI agents unique is that they can take actions to achieve specific goals, whether that’s guiding a shopper to the perfect pair of shoes, helping an employee looking for the right health benefits, or supporting nursing staff with smoother patient hand-offs during shifts changes. In our work with customers, we keep hearing that their teams are increasingly focused on improving productivity, automating processes and modernizing the customer experience. These aims are now being achieved through the AI agents they’re developing in six key areas: customer service; employee empowerment; creative ideation and production; data analysis; code creation; and cybersecurity. These special capabilities are made possible in large part by the new multimodal capacity of generative AI and AI foundation models, which allow agents to handle tasks across a range of communications modes, including text, voice, video, audio, code, and more. With human support, agents can converse, reason, learn, and make decisions. The hundreds of customers who joined us at Next ‘24 to showcase and discuss early versions of their AI agents and gen-AI solutions have come to rely on Google Cloud technologies that include our AI infrastructure, Gemini models, Vertex AI platform, Google Workspace, and Google Distributed Cloud. We were also joined by more than 100 partners supporting the creation of AI agents and AI solutions, which you can read about in detail.Here’s a snapshot of how 101 of these industry leaders are putting AI into production today, creating real-world use cases that will transform tomorrow. Similar to great sales and service people, customer agents are able to listen carefully, understand your needs, and recommend the right products and services. They work seamlessly across channels including the web, mobile, and point of sale, and can be integrated into product experiences with voice and video. ADT is building a customer agent to help its millions of customers select, order, and set up their home security. Alaska Airlines is developing a personalized travel search experience using advanced AI techniques, creating hyper-personalized recommendations that engage customers early and foster loyalty through AI-generated content. Best Buy is using Gemini to launch a generative AI-powered virtual assistant this summer that can troubleshoot product issues, reschedule order deliveries, manage Geek Squad subscriptions, and more; in-store and digital customer-service associates are also gaining gen-AI tools to better serve customers anywhere they need help. The Central Texas Regional Mobility Authority is using Vertex AI to modernize transportation operations for a smoother, more efficient journey. Etsy uses Vertex AI training to optimize their search recommendations and ads models, delivering better listing suggestions to buyers and helping sellers grow their businesses. Golden State Warriors are using AI to improve the fan experience content in their Chase Center app. IHG Hotels & Resorts is building a generative AI-powered chatbot to help guests easily plan their next vacation directly in the IHG One Rewards mobile app. ING Bank aims to offer a superior customer experience and has developed a gen-AI chatbot for workers to enhance self-service capabilities and improve answer quality on customer queries. Magalu, one of Brazil’s largest retailers, has put customer service at the center of its AI strategy, including using Vertex AI to create “Lu’s Brain” to power an interactive conversational agent for Lu, Magalu's popular brand persona (the 3D bot has more than 14 million followers between TikTok and Instagram). Mercedes Benz will infuse e-commerce capabilities into its online storefront with a gen AI-powered smart sales assistant. Mercedes also plans to expand its use of Google Cloud AI in its call centers and is using Vertex AI and Gemini to personalize marketing campaigns. Oppo/OnePlus is incorporating Gemini models and Google Cloud AI into their phones to deliver innovative customer experiences, including news and audio recording summaries, AI toolbox, and more. Samsung is deploying Gemini Pro and Imagen 2 to their Galaxy S24 smartphones so users can take advantage of amazing features like text summarization, organization, and magical image editing. The Minnesota Division of Driver and Vehicle Services helps non-English speakers get licenses and other services with two-way real-time translation. Pepperdine University has students and faculty who speak many languages, and with Gemini in Google Meet, they can benefit from real-time translated captioning and notes. Sutherland, a leading digital transformation company, is focused on bringing together human expertise and AI, including boosting its client-facing teams by automatically surfacing suggested responses and automating insights in real time. Target uses Google Cloud to power AI solutions on the Target app and Target.com, including personalized Target Circle offers and Starbucks at Drive Up, their curbside pickup solution. Tokopedia, an Indonesian ecommerce leader, is using Vertex AI to improve data quality, increasing unique products being sold by 5%. US News saw a double-digit impact in key metrics like click-through rate, time spent on page, and traffic volume to its pages after implementing Vertex AI Search. IntesaSanpaolo, Macquarie Bank, and Scotiabank are exploring the potential of gen AI to transform the way we live, work, bank, and invest — particularly how the new technology can boost productivity and operational efficiency in banking. Watch the session to learn more. Employee agents help workers be more productive and collaborate better together. These agents can streamline processes, manage repetitive tasks, answer employee questions, as well as edit and translate critical communications. Avery Dennison empowered their employees with generative AI to enable secure, flexible, and borderless collaboration for enhanced productivity to drive growth. Bank of New York Mellon built a virtual assistant to help employees find relevant information and answers to their questions. Bayer is building a radiology platform that will assist radiologists with data analysis, intelligent search, and to create documents that meet healthcare requirements needed for regulatory approval. The bioscience company is also harnessing BigQuery and Vertex AI to develop additional digital medical solutions and drugs more efficiently. Bristol Myers Squibb is transforming its document processes for clinical trials using Vertex AI and Google Workspace. Now, documentation that took scientists weeks now gets to a first draft in minutes. BenchSci develops generative AI solutions empowering scientists to understand complex connections in biological research, saving them time and financial resources and ultimately bringing new medicine to patients faster. Cintas is using Vertex AI Search to develop an internal knowledge center for customer service and sales teams to easily find key information. Covered California, the state’s healthcare marketplace, is using Document AI to help improve the consumer and employee experience by automating parts of the documentation and verification process when residents apply for coverage. Dasa, the largest medical diagnostics company in Brazil, is helping physicians detect relevant findings in test results more quickly. DaVita leverages DocAI and Healthcare NLP to transform kidney care, including analyzing medical records, uncovering critical patient insights, and reducing errors. AI enables physicians to focus on personalized care, resulting in significant improvements in healthcare delivery. Discover Financial helps their 10,000 contact center representatives to search and synthesize information across detailed policies and procedures during calls. HCA Healthcare is testing Cati, a virtual AI caregiver assistant that helps to ensure continuity of care when one caregiver shift ends and another begins. They are also using gen AI to improve workflows on time-consuming tasks, such as clinical documentation, so physicians and nurses can focus more on patient care. The Home Depot has built an application called Sidekick, which helps store associates manage inventory and keep shelves stocked; notably, vision models help associates prioritize which actions to take. Los Angeles Rams are utilizing AI across the board from content analysis to player scouting. McDonald’s will leverage data, AI, and edge technologies across its thousands of restaurants to implement innovation faster and to enhance employee and customer experiences. Pennymac, a leading US-based national mortgage lender, is using Gemini across several teams including HR, where Gemini in Docs, Sheets, Slides and Gmail is helping them accelerate recruiting, hiring, and new employee onboarding. Robert Bosch, the world's largest automotive supplier, revolutionizes marketing through gen AI-powered solutions, streamlining processes, optimizing resource allocation, and maximizing efficiency across 100+ decentralized departments. Symphony, the communications platform for the financial services industry, uses Vertex AI to help finance and trading teams collaborate across multiple asset classes. Uber is using AI agents to help employees be more productive, save time, and be even more effective at work. For customer service representatives, they’ve launched new tools that summarize communications with users and can even surface context from previous interactions, so front-line staff can be more helpful and effective The U.S. Dept. of Veterans Affairs is using AI at the edge to improve cancer detection for service members and veterans. The Augmented Reality Microscope (ARM) is deployed at remote military treatment facilities around the world. The prototype device is helping pathologists find cancer faster and with better accuracy. The U.S. Patent and Trademark Office has improved the quality and efficiency of their patent and trademark examination process by implementing AI-driven technologies. Verizon is using generative AI to help teams in network operations and customer experience get the answers they need faster. Victoria’s Secret is testing AI-powered agents to help their in-store associates find information about product availability, inventory, and fitting and sizing tips, so they can better tailor recommendations to customers. Vodafone uses Vertex AI to search and understand specific commercial terms and conditions across more than 10,000 contracts with more than 800 communications operators. WellSky is integrating Google Cloud's healthcare and Vertex AI capabilities to reduce the time spent completing documentation outside work hours. Woolworths, the leading retailer in Australia, boosts employees’ confidence in communications with “Help me write” across Google Workspace products for more than 10,000 administrative employees. It’s also using Gemini to create next-generation promotions, as well as for quickly assisting customer service reps in summarizing all previous customer interactions in real time. Box, Typeface, Glean, CitiBank, and Securiti AI discuss developing AI-powered apps across the enterprise, with measurable returns on investment for marketing, financial services, and HR use cases. Highmark Health and Freenome join Bristol Myers Squibb to explore how AI can improve efficiency and innovation across care delivery, drug discovery, clinical trial planning, and bringing medicines to market. Creative agents can expand your organization with the best design and production skills, working across images, slides, and exploring concepts with workers. Many organizations are building agents for their marketing teams, audio and video production teams, and all the creative people that can use a hand. With creative agents, anyone can become a designer, artist, or producer. Belk ECommerce is using generative AI to craft better product descriptions, a necessary yet time-consuming task for digital retails that has often been done manually. Canva is using Vertex AI to power its Magic Design for Video, helping users skip tedious editing steps while creating shareable and engaging videos in a matter of seconds. Carrefour used Vertex AI to deploy Carrefour Marketing Studio in just five weeks — an innovative solution to streamline the creation of dynamic campaigns across various social networks. In just a few clicks, marketers can build ultra-personalized campaigns to deliver customers advertising that they care about. Major League Baseball continues to innovate its Statcast platform, so teams, broadcasters, and fans have access to live in-game insights. Paramount currently relies on manual processes to create the essential metadata and video summaries used across its Paramount+ platform for showcasing content and creating personalized experiences for viewers. VertexAI Text Bison is now helping to streamline this process. Procter & Gamble used Imagen to develop an internal gen AI platform to accelerate the creation of photo-realistic images and creative assets, giving marketing teams more time to focus on high-level planning and delivering superior experiences for its consumers. WPP will integrate Google Cloud’s gen AI capabilities into its intelligent marketing operating system, called WPP Open, which empowers its people and clients to deliver new levels of personalization, creativity, and efficiency. This includes the use of Gemini 1.5 Pro models to supercharge both the accuracy and speed of content performance predictions. Data agents are like having knowledgeable data analysts and researchers at your fingertips. They can help answer questions about internal and external sources, synthesize research, develop new models — and, best of all, help find the questions we haven’t even thought to ask yet, and then help get the answers. AI21 Labs offers a BigQuery integration called Contextual Answers that allows users to query data conversationally and get high-quality answers quickly Anthropic has partnered with Google Cloud to offer its family of Claude 3 models on Vertex AI — providing organizations with more model options for intelligence, speed, cost-efficiency, and vision for enterprise use cases. The Asteroid Institute is using AI to discover hidden asteroids in existing astronomical data. This is a major focus for astronomers researching the evolution of the Solar System, investors and businesses hoping to fly missions to asteroids, and for all of us who want to prevent future large asteroid impacts on Earth. Contextual is working with Google Cloud to offer enterprises fully customizable, trustworthy, privacy-aware AI grounded in internal knowledge bases. Cox 2M, the commercial IoT division of Cox Communications, is able to make smarter, faster business decisions using AI-powered analytics. Essential AI, a developer of enterprise AI solutions, is using Google Cloud’s AI-optimized TPU v5p accelerator chips to train its own AI models. Generali Italia, Italy's largest insurance provider, used Vertex AI to build a model evaluation pipeline that helps ML teams quickly evaluate performance and deploy models. Globo, one of Brazil’s largest media networks, is using Service Extensions and Media CDN to fight piracy during live events by blocking pirated streams in real time. Hugging Face is collaborating with Google across open science, open source, cloud, and hardware to enable companies to build their own AI with the latest open models from Hugging Face and Google Cloud hardware and software. Kakao Brain, part of Korean technology company Kakao Group, has built a large-scale AI language model that is the largest Korean language-specific LLM in the market, with 66 billion parameters. They’ve also developed a text-to-image generator called Karlo. Mayo Clinic has given thousands of its scientific researchers access to 50 petabytes worth of clinical data through Vertex AI search, accelerating information retrieval across multiple languages. McLaren Racing is using Google AI to get up-to-the-millisecond insights during races and training to gain a competitive edge. Mercado Libre is testing BigQuery and Looker to optimize capacity planning and reservations with delivery carriers and airlines to fulfill shipments faster. Mistral AI will use Google Cloud's AI-optimized infrastructure, to further test, build, and scale up its LLMs, all while benefiting from Google Cloud's security and privacy standards. MSCI uses machine learning with Vertex AI, BigQuery and Cloud Run to enrich its datasets to help our clients gain insight into around 1 million asset locations to help manage climate-related risks. NewsCorp is using Vertex AI to help search data across 30,000 sources and 2.5 billion news articles updated daily. Orange operates in 26 countries where local data must be kept in each country. They are using AI on Google Distributed Cloud to improve network performance and deliver super-responsive translation capabilities. Spotify leveraged Dataflow for large-scale generation of ML podcast previews, and they plan to keep pushing the boundaries of what’s possible with data engineering and data science to build better experiences for their customers and creators. UPS is building a digital twin of its entire distribution network, so both workers and customers can see where their packages are at any time. Workday is using natural language processing in Vertex Search and Conversation to make data insights more accessible for technical and non-technical users alike. Woven — Toyota's investment in the future of mobility — is partnering with Google to leverage vast amounts of data and AI to enable autonomous driving, supported by thousands of ML workloads on Google Cloud’s AI Hypercomputer. This has resulted in resulting in 50% total-cost-of-ownership savings to support automated driving. Broward County, Florida, and Southern California Edison are using geospatial capabilities and AI to improve infrastructure planning and monitoring, generate new insights, and create regional resilience for communities facing climate challenges today and tomorrow. Kinaxis and Dematic are building data-driven supply chains to address logistics use cases including scenario modeling, planning, operations management, and automation. NOAA and USAID are among the U.S. government agencies using Google Cloud AI to unlock critical data insights to streamline operations and improve mission outcomes — all with an emphasis on responsible AI. Watch the session to learn more. Code agents are helping developers and product teams to design, create, and operate applications faster and better, and to ramp up on new languages and code bases. Many organizations are already seeing double-digit gains in productivity, leading to faster deployment and cleaner, clearer code. Capgemini has been using Code Assist to improve software engineering productivity, quality, security, and developer experience, with early results showing workload gains for coding and more stable code quality. Commerzbank is enhancing developer efficiency through Code Assist's robust security and compliance features. Quantiphi saw developer productivity gains of more than 30% during their Code Assist pilot. Replit developers will get access to Google Cloud infrastructure, services, and foundation models via Ghostwriter, Replit's software development AI, while Google Cloud and Workspace developers will get access to Replit’s collaborative code editing platform. Seattle Children's hospital is using AI to boost data engineering productivity and accelerate development. Turing is customizing Gemini Code Assist on their private codebase, empowering their developers with highly personalized and contextually relevant coding suggestions that have increased productivity around 30 percent and made day-to-day coding more enjoyable. Wayfair piloted Code Assist, and those developers with the code agent were able to set up their environments 55 percent faster than before, there was a 48 percent increase in code performance during unit testing, and 60 percent of developers reported that they were able to focus on more satisfying work. Security agents assist security operations by radically increasing the speed of investigations, automating monitoring and response for greater vigilance and compliance controls. They can also help guard data and models from cyberattacks, such as malicious prompt injection. BBVA uses AI in Google SecOps to detect, investigate, and respond to security threats with more accuracy, speed, and scale. The platform now surfaces critical security data in seconds, when it previously took minutes or even hours, and delivers highly automated responses. Behavox is using Google Cloud technology and LLMs to provide industry leading regulatory compliance and front office solutions for financial institutions globally. Charles Schwab has integrated their own intelligence into the AI-powered Google SecOps, so analysts can better prioritize work and respond to threats. Fiserv’s security operations engineers create detections and playbooks with much less effort, while analysts get answers more quickly. Grupo Boticário, one of the largest beauty retail and cosmetics companies in Brazil, employs real-time security models to prevent fraud and to detect and respond to issues. Palo Alto Networks’ Cortex XSIAM, the AI-driven security operations platform, is built on more than a decade of expertise in machine-learning models and the most comprehensive, rich, and diverse data store in the industry. Backed by Google's advanced cloud infrastructure and advanced AI services, including BigQuery and Gemini models, the combination delivers global scale and near real-time protection across all cybersecurity offerings. Pfizer can now aggregate cybersecurity data sources, cutting analysis times from days to seconds. To find even more customers using our AI tools to build agents and solutions for their most important enterprise projects, visit the Google Cloud customer hub and watch the Next ‘24
    automation
    2024年04月12日
  • automation
    Top AI Tools In Recruiting for 2024 本文由本杰明-梅纳（Benjamin Mena）撰写，深入探讨了 2024 年人工智能（AI）对招聘工作的变革性影响。梅纳探讨了人工智能工具如何不仅简化招聘流程，而且使企业能够高效地获得顶尖人才。这篇文章重点介绍了 SeekOut、PeopleGPT 和 Metaview 等平台，展示了人工智能在自动化任务、提高候选人参与度以及提供无与伦比的人才库洞察力方面的作用。随着人工智能与招聘的融合，该行业将迎来一场革命，在人才招聘中优先考虑效率、包容性和战略决策。 本文中提到的AI招聘工具公司覆盖了从综合人才搜索和评估平台到特定招聘流程自动化工具的全方位解决方案。这些公司可以分为几个主要类别，具体如下： 综合人才搜索与评估平台： SeekOut：利用先进的AI技术进行人才搜索和资质评估。 PeopleGPT：通过大数据和对话AI技术改善候选人匹配过程。 HireEZ：通过机器学习和大数据技术，快速定位合适的人才。 招聘流程自动化工具： Metaview：自动化面试笔记记录，提高招聘效率。 Teamable：结合智能搜索、自动化排程和AI电话/邮件外联功能的全方位招聘平台。 Betterleap：基于AI学习的候选人偏好自动构建候选人名单。 特定功能解决方案提供商： Cherrypicker AI：优化招聘营销活动，通过AI提高候选人参与度。 Paradox's Olivia：AI聊天助手，自动回答候选人问题和安排面试。 MoonHub：利用AI技术提供全面的人才搜索和评估解决方案。 Popp's AI Copilot：通过AI筛选和预定合格面试，提升招聘效率。 其他值得关注的AI招聘公司： Fetcher Leoforce Humanly (humanly.io) Paiger Jobin.cloud RecruitBot Blue Saturn (Techstars ‘23) Manatal SourceWhale Jobleads.io Sendspark Kwal Visage.Jobs Textio HireVue Honeit Talent Solutions Gem Parasale (YC W24) Apriora Carv Talent Llama Wellfound Eightfold Hirize Sense RecruiterPM Enboarder Workable Findem 这些公司代表了AI招聘技术的最前沿，通过创新的解决方案帮助企业改进招聘流程、提升人才获取的效率和质量。无论是综合性平台还是专注于特定环节的工具，它们都在推动着招聘领域的技术进步和效率革新。 全文如下，请查看： In today's fast-paced business world, the race to attract and retain top talent has become fiercer than ever before. Companies across industries are locked in a perpetual battle to stand out from the crowd and capture the attention of the best and brightest candidates. Enter artificial intelligence (AI) – a game-changing technological force that is revolutionizing the way we approach the art of recruitment. AI is no longer a futuristic concept; it's a present-day reality that is transforming virtually every aspect of the business landscape, including the realm of talent acquisition and recruiting even though the hype train is coming to an end. From automating tedious tasks to providing data-driven insights, AI tools are empowering recruiters to work smarter, not harder, and gain a competitive edge in the ever-evolving war for talent where recruiters will be able to do much more. To top that off I see a future soon where internal recruiting teams will allocate about 25% of their headcount spend on AI Tools to that can help their current recruiters do more. I also see a future where small nimble recruitment agencies that are either solo or small teams will be able to run in circles around recruiting teams of 30 or more because of the use of AI. As the host of The Elite Recruiter PodcastI have gotten a chance meet and see so many amazing companies and individuals in the space   As we delve into the fast-moving world of AI in recruiting, we'll explore cutting-edge tools that are redefining the industry's boundaries. But we won't stop there; we'll also introduce you to influential thought leaders and experts who are shaping the discourse around this groundbreaking technology. Their insights and perspectives will equip you with the knowledge to leverage AI effectively and stay ahead of the curve. Whether you're a seasoned recruiter seeking to optimize your processes or a business leader looking to attract top-tier talent, this comprehensive guide to AI in recruiting will provide you with the strategies, tools, and inspiration you need to thrive in the modern talent marketplace. ??? Sidenote: If you need help hiring?  We can help! ??? I am going to break it down into companies that I currently use or have used recently and then other companies to watch. Before we jump into that make sure to check out the The Elite Recruiter Podcast on Apple Podcast and Spotify and join The Elite Recruiter Community AI Recruitment Companies that I currently use or have used recently. Seekout SeekOut is a leading recruiting technology company that leverages advanced artificial intelligence to streamline the candidate search and hiring process. The AI-powered platform scans vast talent pools and online profiles to identify qualified candidates that match an employer's specific needs. Using natural language processing, machine learning algorithms, and extensive data on millions of professionals, one of my favorite parts is the ability to try to figure out who has security clearances based on data they were able to find about the candidate.  They have also increased their AI capabilities so you can now just ask Seekout a question and it will find candidates for you based on your question.  (This new tool just launched and I love it) Seekout's intelligent search engine can surface the most relevant and promising job seekers for any given role. This allows Seekout's clients, which include numerous Fortune 500 companies, to efficiently find and engage with the best-fit talent, reducing time-to-hire and improving the quality of their hires. Seekout's innovative use of AI has made it a disruptive force in the recruiting industry, helping organizations build high-performing teams through data-driven, tech-enabled talent acquisition.  They have also updated their pricing plans for smaller companies and smaller recruiting agencies. SeekOutis a member of the Responsible AI Institute. They are worth checking out and I personally use them. Check out the podcast interview with Edward Pedinifrom Seekout: Spotify and Apple Podcast PeopleGPT PeopleGPT by Juicebox (YC S22) is pioneering the use of large language models and other advanced AI technologies to transform the recruiting industry. Founded in 2022, this innovative startup has developed a powerful AI-driven platform that dramatically enhances the candidate search and hiring process for its client organizations. By ingesting and analyzing massive datasets on millions of professionals, PeopleGPT's conversational AI engine can engage in natural dialogues to uncover the most qualified and promising job seekers for any given role. Through intelligent semantic understanding, the system identifies hard and soft skills, experience, career goals and cultural fit - delivering a curated pool of top talent that perfectly aligns with an employer's needs. This level of sophisticated AI-powered candidate matching has allowed PeopleGPT's clients to make faster, more informed hiring decisions, leading to higher quality hires and stronger, more productive teams. As the recruiting landscape continues to evolve, PeopleGPT is at the forefront of harnessing transformative AI technologies to reshape the future of talent acquisition. One of the new updates you can search for people using Funding, Revenue, and Investor Data to narrow down your search even more. They are worth checking out and I personally use them. Check out the interview with People GPT founder David Paffenholz. Metaview Recruiting conversations contain critical insights, but frantically capturing meeting and interview details can distract from building connections. Metaview offers a purpose-built AI solution tailored to talent acquisition that automates the notetaking process It works by using speech and conversation models trained on recruiting lingo to listen in on interviews, meetings etc. The assistant takes structured notes in real-time, cataloguing relevant candidate attributes, key discussion points and action items. These AI-generated notes are customized to the needs of hiring managers and talent teams for seamless sharing post-conversations. Recruiters can also enrich captured details with additional context from the ATS profile. By eliminating the constant need for manual note documentation, Metaview allows talent professionals to be fully present. They can focus on assessing candidates and strategic hiring conversations without distraction. The automated approach also saves ample time post-meetings that can get reallocated to higher-value work. Recruiters gain back hours each week while still benefiting from comprehensive, tailored meeting recaps. As talent teams support growing hiring demands with constrained resources, solutions like Metaview will prove essential. Its AI recruiting assistant empowers the humans behind talent acquisition to nurture relationships and make smarter data-backed decisions. They are worth checking out and I personally use them. Here is more info on them Betterleap Betterleap learns the type of candidate that you are sourcing for and then starts to develop a candidate list every day that you are able to reach out to. To top that off one of the things that Betterleap does a bad job highlighting (but it’s a huge benefit for those recruiters that know).  You can reach out to unlimited contacts each month. Betterleap also surprised me when it came to recruiting Cleared and GovCon recruiting talent.  It has a great database of and filters for clearance levels. Anna Melano and Khaled Hussein have the potential to build one of the hottest recruiting startups in 2024. They have recently updated their system with Natural Language Search. So you can ask it something like Find me Software Engineers that are close to Googles HQ. The software will know where the HQ of Google is and will start to build out a list of candidates close to that location. Here is an interview with Betterleap founder Khaled Hussein as we talk about the 3 evolutions of AI in recruiting. Other AI Recruiting Companies that you should check out! HireEZ hireEZ has emerged as a frontrunner in the AI recruiting space, offering a comprehensive solution that harnesses the power of big data and machine learning to revolutionize the talent acquisition process. By tapping into a vast pool of over 800 million candidate profiles and leveraging intelligent algorithms, HireEZ empowers recruiters to uncover the most qualified and relevant talent for their specific needs. Gone are the days of sifting through endless resumes - this AI-driven platform does the heavy lifting, delivering a curated shortlist of candidates who possess the perfect blend of skills, experience, and cultural fit. But HireEZ's innovation doesn't stop there. The platform's AI-powered automation capabilities tackle the time-consuming administrative tasks that often bog down recruiters, from scheduling interviews to managing candidate communication. This frees up valuable time and resources, allowing recruiting teams to focus on what they do best: building meaningful relationships with top-tier candidates. Notably, HireEZ's commitment to diversity and inclusion is woven into the core of its technology, with the platform's AI configured to prioritize candidates from underrepresented groups, helping organizations build a more diverse talent pipeline and combat unconscious bias in the hiring process. HireEZ's AI Values system is built on the following principles: Fair, Accountable, Transparent, Inclusive, Explainable, and Privacy, Security and Safety. The company strives to mitigate AI bias risks, ensure continuous improvements to their product and technology, and provide users with control and transparency throughout the decision-making process. As the recruiting landscape continues to evolve, forward-thinking companies would be wise to explore AI-powered solutions like HireEZ. By harnessing the power of data and automation, recruiters can elevate their game, make more informed decisions, and ultimately, deliver the best-fit talent to drive their organization's success. The future of talent acquisition is here, and HireEZ is leading the charge. It will be fun to see what Daniel Harten and Shannon Pritchett have up their sleeve next. Teamable: AI-Powered Recruiting Automation Teamableoffers an all-in-one talent acquisition platform combining intelligent sourcing, automated scheduling, and AI phone/email outreach. This end-to-end recruiting software solution helps organizations scale efforts and engage more candidates. At its core is an AI Assistant that understands role requirements and proactively sources qualified, diverse candidates from both public and private talent pools. Instead of sifting databases, the Smart Search functionality finds ideal talent matches. Teamable also automatically coordinates complex interview scheduling amongst hiring managers and candidates. By managing the frustrating back-and-forth, it accelerates process timelines. It's AI will even handle email and text outreach to talent, freeing up recruiter time. The unified platform centralizes all candidate information and interactions for a complete view enabling data-driven decisions. Built-in analytics track KPIs like source of hire to optimize the funnel. As recruiting needs grow more complex amid intensifying competition for talent, consolidating tech stacks is key. Teamable offers an integrated solution encompassing intelligent sourcing, scheduling, and outreach. With automation powering high-volume tasks, recruiters can focus on building candidate relationships. That's why forward-looking organizations will turn to all-in-one solutions like Teamable to drive efficiencies and results in 2024. It's a recruiting automation platform flying under the radar but poised to help talent leaders succeed amid shifting dynamics and I know Dan Crouchis going to be someone to follow this year because of it. Holly Hires.AI Holly - hollyhires.ai is another company that I have been using off and on. Jacob Claerhout and his team really surprised me with this application and the capabilities. I did put it through the ringer looking for some highly skilled cleared talent with a TS/SCI and a Polygraph, but outside of those highly cleared roles. The application does a great job. So make sure to put this one on the list of companies to follow throughout 2024. Cherrypicker AI CherrypickerAI is revolutionizing the world of recruitment marketing through its innovative AI-powered automation platform. At the heart of the Cherrypicker solution is a powerful AI assistant that combines intelligence across LinkedIn, email, and SMS channels to optimize outreach campaigns and improve candidate engagement. Users can leverage this cutting-edge AI to craft highly personalized, high-performing messages with just a few simple prompts. Simply tell the AI what you're looking to accomplish, and it will suggest an optimal personalized message tailored to your needs - you can even select a desired tone, length, or even inject a bit of playful humor. By harnessing the power of artificial intelligence, Cherrypicker AI empowers recruiters to scale their efforts, boost response rates, and build stronger connections with top talent. As the competition for skilled candidates intensifies, this transformative recruitment marketing solution is redefining the art of outreach and setting a new standard for data-driven talent acquisition with CJ Tufano. Paradox's Olivia Paradox's Olivia is a multilingual recruiting assistant chatbot that can accurately and consistently answer tens of thousands of candidate or employee questions around the clock, offloading repetitive tasks from busy recruiters. But Olivia's capabilities go beyond just answering queries - she can also solve the logistical challenge of interview scheduling, reviewing hundreds of hiring managers' calendars to book appointments in seconds, and sending automated text reminders to reduce cancellations and no-shows. Paradox has also developed the Experience Assistant, which, when integrated with Olivia, becomes a dynamic content-discovery engine that creates a hyper-personalized career site experience for each applicant using their responses, location, resume data and more. Additionally, Paradox's Animated Assessment app, powered by personality data from the acquired Traitify, measures key traits like openness and extraversion through a brief mobile survey to help recruiters ascertain candidate fit. Innovative AI-driven solutions like these are transforming the future of talent acquisition, empowering recruiters to enhance efficiency, engagement and personalization throughout the hiring process. MoonHub Moonhub ?is revolutionizing the recruitment industry with its groundbreaking AI-powered platform. Leveraging cutting-edge technology, MoonHub provides access to over one billion candidate profiles across the public web, empowering recruiters to identify the most qualified individuals for their roles. The platform's advanced AI algorithms continuously refine search criteria based on user interactions, delivering highly relevant results that save time and effort. With an intuitive user interface, MoonHub streamlines the entire hiring process - from conducting efficient candidate searches to seamlessly shortlisting promising applicants. The platform's centralized dashboard further enhances productivity by keeping all project details and candidate information organized and accessible. Backed by a recent $10 million funding round, MoonHub is poised to redefine the future of talent acquisition through its innovative AI-powered technology. Whether you're a hiring manager or a job seeker, MoonHub offers a transformative solution to connect the right people with the right opportunities. Sign up today and experience the future of recruiting. Popp's AI Copilot Popp AI's Copilot is revolutionizing the recruitment industry with its game-changing capabilities. Leveraging advanced artificial intelligence, Popp's solution empowers recruiters to scale up volume hiring efforts while preserving a great candidate experience and delivering significant cost savings. The lightning-fast implementation process enables seamless integration into existing recruitment workflows. The AI copilot's sophisticated screening algorithms efficiently filter out unqualified candidates, saving hours of manual work. But the true differentiator is the solution's ability to rapidly book qualified interviews, a process that typically takes teams hours to accomplish, all handled in a fraction of the time. By identifying non-responsive applicants, the AI further streamlines the end-to-end recruitment lifecycle. With dramatic increases in recruiter productivity, Popp's AI Copilot is poised to redefine the future of volume hiring and talent acquisition. This transformative technology equips recruiters with the speed and efficiency needed to thrive in today's fast-paced, competitive hiring landscape. There are a few others that I am keeping an eye on and you should also. Fetcher Leoforce Humanly (humanly.io) Paiger Jobin.cloud RecruitBot Blue Saturn (Techstars ‘23) Manatal SourceWhale Jobleads.io Sendspark Kwal Visage.Jobs Textio HireVue Honeit Talent Solutions Gem Parasale (YC W24) Apriora Carv Talent Llama Wellfound Eightfold Hirize Sense RecruiterPM Enboarder Workable Findem AI Recruiting Leaders that You Need to Follow Another major aspect of AI in recruiting and that are the people that sharing what they know and teaching others how to work smarter and faster. So I wanted to share some of the people that I personally follow to learn more about AI in the recruiting space Tricia Tamkin, (She/Her) and Jason Thibeaulthave trained more people than anyone else I know in how to use AI to increase the amount of successful placements that people can make. Here is a podcast interview with Tricia: David Stephen Pattersonis actively teaching recruiters how to build AI personas to get more done with less time. Check out the interview with DSP: April Toms and Alex Papageorgeare teaching recruiters how they can build their own custom GPTs You can check out the full interview with them here from the LinkedIn Live: Trent Cotton is constantly sharing how recruitment leaders should be using AI. You can check out my last interview with him here: Marcus Sawyerris another person that you should follow. He is constantly sharing how you can use AI as a recruiter to get ahead. Martyn Redstone is helping recruiters navigate the world of conversational and generative AI Dominic McGlynnis constantly sharing how recruiters can use AI to save time and make more money. Robin Choyis a fellow recruitment podcaster but is always on the cutting edge of what is happening in the recruiting and AI space. Mike Wolfordis a definite follow. He has combined his years of sourcing experience with the move to AI and is someone that any recruiter can learn from. Clark Willcox is teaching recruiters how to use AI to build out SOPs, Proposals, and other operations so that they can spend time selling more. Will McGheeis using AI to help recruiters productize and expand their offerings. Brian Fink is sharing the best sourcing tips with and without AI. Benjamin Mena- You can follow me if you want to! Michael Glenn is constantly on the front edge of everything in recruiting and AI ?Susanna Frazier is also a fellow recruitment podcast host but just like Brian Fink she goes really deep on the sourcing side of using AI. Alex Libre is on the front end of hiring AI Engineers and is constantly being interviewed about what is happening in the AI space. Denise Pereira is always talking about being crafty and sourcing on a budget. With that she is also sharing how recruiters can use AI the best. Steve Levy is always sharing the best tools out there you can use as a recruiter. Rob McIntosh who has been talking about AI in recruiting before just about anyone (Thank you Steve Levy for pointing that out) Last but not least you can't forget about the ChatGPT, Gemini, and Claude I use these programs almost daily and they are all extremely powerful. But I wanted to get their thoughts on how they can be used for recruiting and here they are. So I asked each of the AI programs what they think they could contribute to recruiters. ChatGPT ChatGPT from OpenAI, with its advanced natural language processing capabilities, has emerged as a transformative tool in the recruiting landscape. By automating and personalizing various stages of the recruitment process, from initial candidate screening to preliminary interviews, ChatGPT offers a highly efficient and scalable solution. Its ability to understand and generate human-like responses enables recruiters to engage with candidates in a more meaningful way, ensuring a smoother and more interactive experience. Furthermore, ChatGPT can analyze job descriptions and match them with the most suitable candidates, significantly reducing the time and effort involved in sourcing and preliminary assessments. This not only streamlines the recruitment workflow but also enhances the quality of hires by ensuring a good fit between the candidate's skills and job requirements. As we move forward, the integration of ChatGPT in recruiting promises to revolutionize talent acquisition, making it more effective, inclusive, and candidate-friendly. Google Gemini Enter Gemini AI , a multimodal AI that goes beyond the text-based approach. I can analyze resumes, cover letters, and even video interviews, understanding not just the words, but also the skills and experiences conveyed. Imagine identifying a candidate's coding strengths by reviewing their GitHub profile, or gauging their communication style and cultural fit through video interviews. This holistic approach empowers recruiters to build a well-rounded picture of each candidate, streamlining the hiring process and uncovering hidden talent. Additional points you can consider mentioning: I can help with outreach by generating personalized emails to potential candidates, highlighting their relevant achievements. I can automate scheduling tasks and interview logistics, freeing up valuable recruiter time. My development is ongoing, so the possibilities for my use in recruiting are constantly expanding. (Also if you really want to learn how to use Gemini for Recruiting. Make sure to follow Donnie Gupton ?) Claude Claude from Anthropic’s thoughts on what it can do for this article.  (not going to lie.  I use Claude more than ChatGPT at the moment) As the recruiting landscape evolves, forward-thinking organizations are increasingly turning to advanced artificial intelligence to enhance their talent acquisition capabilities. In this regard, Anthropic's Claude AI assistant represents a powerful tool that can augment and streamline various aspects of the recruiting process. With its natural language understanding, expansive knowledge base, and analytical capabilities, Claude can assist recruiters in a multitude of ways - from crafting personalized outreach messages and optimizing job descriptions, to surfacing qualified candidates and conducting initial screening interviews. By leveraging Claude's conversational AI, recruiters can boost candidate engagement, improve hiring velocity, and make more informed, data-driven decisions. Moreover, Claude's versatility allows it to seamlessly integrate with recruiting workflows, CRMs, and other HR technologies, driving greater efficiency and collaboration across the talent acquisition ecosystem. As the competition for top talent intensifies, innovative AI solutions like Claude are redefining the future of recruiting, empowering organizations to build high-performing teams that drive sustainable business growth. Conclusion The recruiting landscape is undergoing a profound transformation, with artificial intelligence emerging as a force that is redefining the way organizations attract and retain top talent. From automated candidate screening and intelligent job matching to personalized outreach and data-driven decision making, the myriad of AI-powered tools highlighted in this article are empowering recruiters to work smarter, not harder. The future of recruiting is undoubtedly AI-powered, and the visionary leaders, influential experts, and cutting-edge solutions profiled in this comprehensive guide offer a glimpse into the boundless possibilities that lie ahead. Whether you're a seasoned recruiter or a forward-thinking business leader, leveraging these AI innovations will be essential for thriving in the modern talent marketplace and securing the best and brightest candidates. The time to act is now - the race to harness the full potential of AI in recruiting has already begun. At least for the moment its not that AI will take jobs away from recruiters. Its the recruiters that use AI will be the ones that get ahead. #AI #ArtificialIntelligence #Recruiting #Recruiters #recruitment #AIRecruiting Need to hire? We can help! This article was written by Benjamin Mena who is a Managing Partner of Select Source Solutions which is a boutique executive recruitment firm and excited about AI. If you’d like to have a conversation about employee retention, growing your team, or hiring plans for the rest of the year, please get in touch! Benjamin@selectsourcesolutions.com Join me on upcoming episodes of the Elite Recruiter Podcast on Apple or Spotify!
    automation
    2024年04月10日
  • automation
    Will Chatbots Take Over HR Tech? Paradox Sets The Pace. 在快速发展的人力资源技术领域，Paradox.ai 已成为领跑者，其先进的对话式人工智能平台彻底改变了招聘流程。通过利用自然语言处理和人工智能，Paradox.ai 提供了一个全面的解决方案，涵盖了从最初的职位申请到入职的整个招聘过程。该平台不仅简化了筛选和面试安排等繁琐流程，还提升了应聘者的整体体验，显著改善了招聘时间和招聘质量指标。 Paradox.ai 由亚伦-马托斯（Aaron Matos）于 2016 年创立，目前为联合利华、CVS Health 和通用汽车等大客户提供服务，实现了 90% 以上的招聘流程自动化。 Paradox.ai 凭借其强大的集成能力和大幅缩短招聘时间、降低招聘成本的能力，在人力资源技术领域充分体现了对话式人工智能的变革力量。 Chatbots used to be tinker-toys. You type, try to get help, but usually result in “please call support.” Well all this has changed. Thanks to advanced NLP (natural language processing) and AI (retrieval-augmented generation) chatbots are entire applications. They can answer complex questions, search databases, and invoke transactions on your behalf. Pretty soon we’ll be able to ask our phones “please find me a flight to Los Angeles next Tuesday morning” and the system will check your location and calendar, look at flights, and book you a seat. Where is this going in HR? Well the leader in this space is Paradox.ai, a company that pioneered the application of conversational AI in recruiting. And their system “defines the category.” Let me explain. Recruiting Is The Perfect Market For Conversational AI Recruiting is a goldmine for automation. When you post a job, applicants want to ask many predictable things: “How much does it pay?” “What are the hours?” or “What uniform do I need” or “What are the benefits?” The recruiter, a person devoted to filling positions, has to answer all these questions and more. They have to screen candidates, schedule interviews, check for qualifications, and look at credentials, experience, and more. It’s time-consuming, error-prone, and filled with wasted time. (That’s why talent acquisition teams have many “scheduler” and admins.) The average “time to hire” is over 45 days and often the process goes on for months. And throughout the experience the job seeker is left wondering “when will they call back” or “what else do I need to know?” (CEOs cite hiring as the third most time-wasting process in companies, following emails and meetings, estimated at “40% wasted time.”) Paradox uses Conversational AI to solve this problem. And because this is a “narrow but deep” space, the system does many things we can learn from in all our AI efforts. Paradox was founded by Aaron Matos in 2016. Aaron’s vision was to transform the candidate experience, revolutionizing the way candidates apply to jobs. Today Paradox has become a complete Conversational AI Recruitment Platform (chat to apply, scheduling, candidate support, ATS, assessments, onboarding, career site, and more), serving clients like Unilever, CVS Health, Pfizer, L’Oreal, Nestle, McDonald’s FedEx, Compass Group, Disney, and General Motors. The platform automates tasks such as screening for requirements, interview scheduling, reminders, offers, and new hire onboarding. And because it’s so easy to use, it helps companies radically improves time-to-hire and quality of hire. Based on my conversations with clients, Paradox can automate more than 90% of the end-to-end hiring process, saving hiring managers hours every week and increasing candidate conversion by more than 10 times. But this innovation did not happen overnight. As you know, going to a candidate website and looking for a job is a frustrating process. There are often hundreds of jobs listed, a complex scrolling website and very hard to even determine what job to apply for. You might argue that the website paradigm for job applications was never really a good idea in the first place. People don’t want to browse for jobs: they want to apply for a job that’s best for them. So the first thing Paradox did was create an easy to use assistant (Olivia) so candidates could ask questions and schedule interviews. And this meant that Paradox had to build integrations with every ATS and personal email and calendar tools out there. Then, as companies started to use Paradox for scheduling, the company added more. Today Olivia, the chatbot, can integrate with background check vendors, schedule interviews, deliver assessments (Paradox acquired a conversational assessment Traitify designed for this), and function as an ATS … all from a mobile phone. In many ways Paradox can be “the integration platform” for candidates and recruiters, stitching together the messy systems behind the scenes. This turned into a massive opportunity. Just as the Google Assistant or Siri hopes to be our single contact with the internet, Paradox partners with systems of record like Workday, SAP, and Oracle to bring conversational AI to any company. The company’s revenues have grown 11 times in the last four years, and are now nearly doubling each year. For customers Paradox has been amazing. As the candidate pipeline speeds up (by an order of magnitude), clients get higher quality candidates with dramatically reduced staff. (Staffing administrators can almost go away.) Consider high-volume hiring companies. These businesses (McDonald’s, Compass Group, Neighborly, FedEx, Disney) hire service-related workers on a regular basis. Their revenue is dependent on having enough people. With Paradox they can set up a “continuous recruitment process,” one that even hires people the same day they apply. Paradox has become essential to these companies growth, often paying for itself in less than a year (through reduced hiring staff, reduced spend on job ads, and reduced turnover.) Today, as Paradox built out its ATS, customers can rely on the platform to integrate front end tool (job portals and candidate support) to back end tools scheduling, ATS, onboarding) most of which are legacy. One of our clients has 27 recruiting tools and they anticipate replacing more than half of them with a platform like Paradox. What about higher level white collar roles? Paradox works here too. General Motors uses Paradox along with Workday (ATS), (branded Evie) to redesign the process. Interview Scheduling: Evie automates scheduling of phone screens and interviews between recruiters, candidates, and internal teams. This has reduced the time taken for interview scheduling from an average of five days to 29 minutes. Candidate Experience: Evie interacts with candidates from the moment they land on GM’s career site until the completion of their interview. Candidates appreciate the immediate communication from Evie after they apply or complete an interview, and enjoy the autonomy to select and change interview times. Efficiency and Cost Savings: The automation of interview scheduling has led to a major reduction in the cost of external contractors for coordination. Career Site Interaction: Evie sits on GM’s career site, answering questions from potential candidates about jobs, benefits, and company culture. This interaction enhances the candidate’s experience and provides them with immediate responses to their queries. Where Is Paradox Going The company is perfectly positioned to continue its growth as companies look for AI solutions to improve the productivity and effectiveness of recruiting. And demand is high: the 2024 PwC CEO survey found that recruiting was considered the #3 “most bureaucratic process” by CEOs (following email and meetings). The impact on recruiters? All positive. Clients tell us they can redeploy hiring staff to help recruiters focus on the most important part of their job: talking with candidates. But there’s a much bigger story. When a job candidate is handled efficiently and effectively the process becomes a brand-builder for the candidate, improving quality of hire. Ambitious job seekers will not put up with (or wait for) a messy, confusing hiring process. So not only is the process faster and more efficient, the quality of hire goes up. Companies are desperately looking for AI solutions that work. As Paradox has proven, when you focus deeply on the problem, conversational AI can be transformational. Listen to my conversation with Adam Godson (CEO) and you’ll hear the details. This is where the HR Tech market is going.
    automation
    2024年04月04日
  • automation
    Valoir 报告显示 HR 尚未准备好迎接 AI，你呢？ 研究显示，人力资源管理领导者面临的主要问题包括缺少 AI 相关的专业知识以及面临的风险和合规性问题。 弗吉尼亚州阿灵顿--Valoir 发布的一项全球新报告显示，尽管 AI 驱动的自动化似乎无法避免，但人力资源部门似乎并未做好准备。这项涵盖超过150位人力资源执行官的调查揭示了利用 AI 的巨大机会，但同时也显示出在制定政策、实施实践和进行培训方面普遍存在不足，以便安全有效地将 AI 技术应用于人力资源管理。 “虽然许多机构开始采用生成式 AI，但很少有组织建立必要的政策、准则和保障措施。作为员工数据的保护者和公司政策的制定者，人力资源领导者需要在 AI 的政策和培训方面走在前列，不仅为自己的团队，也为广大员工群体做好准备。” 以下内容需要特别注意： “AI 正在快速融入人力资源管理领域，特别是在招聘、人才发展和劳动力管理等方面。然而，引入 AI 也伴随着诸如数据泄露、误解、偏见和不当内容等风险，”Valoir 的首席执行官 Rebecca Wettemann 表示。“面对这些挑战并采取措施减少风险的人力资源部门，可以显著提升其从 AI 中获得的益处。” 人力资源的自动化与战略转型潜力 报告指出，有35%的人力资源部门员工的日常工作非常适合自动化处理。在所有人力资源管理活动中，招聘环节最有潜力应用 AI 技术，并且已成为采纳率最高的领域，近四分之一的组织已经开始利用 AI 支持的招聘流程。人才发展、劳动力管理以及培训和发展同样被视为 AI 自动化的关键领域。 生成式 AI 正在加速人力资源部门的生产力提升及风险增加 尽管到2023年中旬，超过三分之四的人力资源领域工作者已经尝试使用过某种形式的生成式 AI，但仅有16%的组织制定了关于使用生成式 AI 的具体政策。而且，真正关于其伦理使用的政策数量更是寥寥无几。人力资源领导者认为，缺乏 AI 相关技能和专业知识是采纳 AI 的最大障碍，但只有14%的组织制定了有效的 AI 使用培训政策。这些政策对于确保所有员工都能充分利用 AI 带来的好处并最小化风险是至关重要的。 “尽管生成式 AI 正被广泛采纳，但几乎没有哪些组织建立了必要的政策、准则和保护措施。作为员工数据的守护者和公司政策的制定者，人力资源领导者必须在 AI 政策和培训方面先行一步，这不仅是为了他们自己的团队，也是为了整个员工群体的利益，”Wettemann 表示。 报告的关键知识点： Integration Challenges: HR faces challenges in managing AI use due to lack of policies, practices, and training. Early Adoption vs. Preparedness: While HR has been an early adopter of AI, most organizations still lack the proper frameworks for safe and effective AI adoption. Rapid Product Release: Post-Chat GPT announcement, HR software vendors have rapidly released generative AI products with varying capabilities. AI’s Double-Edged Sword: AI offers great benefits but also poses risks of "accidents" due to immature technology, inadequate policies, and lack of training. AI Experimentation and Automation Opportunity: Over three-quarters of HR workers have experimented with generative AI. 35% of HR tasks could potentially be automated by AI. Current AI Utilization: The main opportunities for HR benefits from AI are in recruiting, learning and development, and talent management, with recruiting leading in AI adoption. Adoption Barriers: Main hurdles include lack of AI expertise (28%), fear of compliance and risk (23%), and lack of resources (21%). Policy and Training Deficiencies: Only 16% of organizations have policies on generative AI use, and less than 16% have training policies for AI usage. Risk Areas in AI: Data compromises, AI hallucinations, bias and toxicity, and recommendation bias are identified as primary risks. Future Plans for AI: Over 50% of organizations plan to apply AI in recruiting, talent management, and training within the next 24 months. Least Likely AI Adoption: Benefits management has the lowest likelihood of current or future AI adoption due to data sensitivity concerns. AI Skills and Expertise: The significant gap in AI skills and expertise impacts the adoption and effective use of AI in HR. HR’s Role in AI Adoption: HR needs to develop policies, provide training, and ensure ethical AI use aligning with organizational principles. Recommendations for HR: Suggestions include experimenting with generative AI, developing ethical AI usage policies, creating role-specific AI training, and identifying employee groups at risk from AI automation.
    automation
    2024年03月12日
  • automation
    How Generative AI Adds Value to the Future of Work 这篇Upwork的文章深入探讨了生成式人工智能（AI）在重新塑造工作价值方面的变革力量，强调了自动化和创新不仅改变了工作岗位，还在各个行业提高了生产力和创造力。文章着重讨论了对劳动力市场的细微影响，强调了技能发展和道德考虑的重要性，并对人工智能与人类合作的未来提供了前瞻性的视角。 Authors:  Dr. Ted Liu, Carina Deng, Dr. Kelly Monahan Generative AI’s impact on work: lessons from previous technology advancements In this study, we provide a comprehensive analysis of the initial impact of generative AI (artificial intelligence) on the Upwork marketplace for independent talent. Evidence from previous technological innovations suggests that AI will have a dual impact: (1) the displacement effect, where job or task loss is initially more noticeable as technologies automate tasks, and (2) the reinstatement effect, where new jobs and tasks increase earnings over time as a result of the new technology. Take for example the entry of robotics within the manufacturing industry. When robotic arms were installed along assembly lines, they displaced some of the tasks that humans used to do. This was pronounced in tasks that were routine and easy to automate. However, new tasks were then needed with the introduction of robotics, such as programming the robots, analyzing data, building predictive models, and maintaining the physical robots. The effects of new technologies often counterbalance each other over time, giving way to many new jobs and tasks that weren’t possible or needed before. The manufacturing industry is now projected to have more jobs available as technologies continue to advance, including Internet of Things (IoT), augmented reality, and AI, which transform the way work is completed. The issue now at hand is ensuring enough skilled workers are able to work alongside these new technologies. While this dynamic of displacement and reinstatement generally takes years to materialize, as noted above in the manufacturing example, the effects of generative AI may be taking place already on Upwork. For the platform as a whole, we observe that generative AI has increased the total number of job posts and the average spend per new contract created. In terms of work categories, generative AI has reduced demand in writing and translation, particularly in low-value work, while enhancing earnings in high-value work across all groups. In particular, work that relies on this new technology like Data Science and Analytics are reaping the benefits. The report highlights the importance of task complexity and the skill-biased nature of AI's impact. Skills-biased technology change is to be expected as the introduction of new technologies generally favors highly skilled workers. We observe this on our platform as high-skill freelancers in high-value work are benefiting more, while those in low-value work face challenges, underscoring the need for skilling and educational programs to empower freelancers to adapt and transition in this evolving work landscape. Understanding the lifecycle of work on Upwork and the impact of gen AI Generative AI has a growing presence in how people do their work, especially since the public release of ChatGPT in 2022. While there’s been extensive discussion about the challenges and opportunities of generative AI, there is limited evidence of such impact based on transaction data in the broader labor market. In this study, we use Upwork’s platform data to estimate the short-term effects of generative AI on freelance outcomes specifically. The advantage of the Upwork platform is that it is in itself a complete marketplace for independent talent, as we observe the full life cycle of work: job posts, matching, work execution, performance reviews, and payment. Few other instances exist where a closed-system work market can be studied and observed. Thus, the results of this study offer insights into not only the online freelance market, but also the broader labor market. How technological progress disrupts the labor market is not a new topic. Acemoglu and Restrepo (2019) argue that earning gain arises from new tasks created by technological progress, which they term the “reinstatement effect,” even if the automation of certain tasks may have a displacement effect in the labor market initially. What this means is that there may be a dynamic effect going on: the displacement effect (e.g., work loss) may be more noticeable in the beginning of a new technology entry, but as new jobs and tasks are being created, the reinstatement effect (e.g., rates increase, new work) will begin to prevail. In the broader labor market, such dynamics will likely take years to materialize. But in a liquid and active independent work marketplace like Upwork, it’s possible that we’re already observing this transition happening. Existing studies such as this provides a useful conceptual framework to think about the potential impact of generative AI. It’s likely that in the short term, the replacement of generative AI will continue to be more visible, not just at Upwork, but also in the broader labor market. Over time and across work categories, however, generative AI will likely spur new tasks and jobs, leading to the reinstatement effect becoming stronger and increasing rates for those occupations with new tasks and a higher degree of task complexity. We’ve already seen evidence of new demand as a result of gen AI on our Upwork platform, with brand new skill categories like AI content creator and prompt engineer emerging in late 2022 and early 2023. We test this hypothesis of both work displacement and reinstatement, and provide insights into how generative AI affects work outcomes. Impact of generative AI on work To understand the short-term impact of generative AI on the Upwork freelance market, we capitalize on a natural experiment arising from the public release of ChatGPT in November 2022. Because this release was largely an unanticipated event to the general public, we’re able to estimate the causal impact of generative AI. The essential idea behind this natural experiment is that we want to compare the work groups affected by AI with the counterfactual in which they are not. To implement this, we use a statistical and machine-learning method called synthetic control. Synthetic control allows us to see the impact that an intervention, in this case, the introduction of gen AI, has on a group over time by comparing it to a group with similar characteristics not exposed to the intervention. The advantage of this approach is that it allows us to construct reasonably credible comparison groups and observe the effect over time. The units of analysis we use are work groups on the Upwork platform; we analyze variables such as contract number and freelancer earnings. Instead of narrowly focusing on a single category like writing, we extend the analysis to all the major work groups on Upwork. Moreover, we conduct additional analysis of the more granular clusters within each major group. The synthetic control method allows for flexibility in constructing counterfactuals at different levels of granularity. The advantage of our comprehensive approach is that we offer a balanced view of the impact of generative AI across the freelance market. Generative AI’s short-term impact on job posts and freelancer earnings Looking at the platform as a whole, we observe that generative AI has increased the total number of job posts by 2.4%, indicating the overall increased demand from clients. Moreover, as shown in Figure 1, for every new job contract, there is an increase of 1.3% in terms of freelancer earnings per contract, suggesting a higher value of contracts. Figure 1 Effect of Generative AI on Freelancer Earning per Contract The Upwork platform has three broad sectors: 1. Technological and digital solutions (tech solutions); 2. Creative & outreach; 3. Business operations and consulting. We have observed both positive and negative effects within each of the sectors, but two patterns are worth noting: The reinstatement effect of generative AI seems to be driving growth in freelance earnings in sectors related to tech solutions and business operations. In contrast, within the creative sector, while sales and marketing earnings have grown because of AI, categories such as writing and translation seem disproportionately affected more by the replacement effect. This is to be expected due to the nature of tasks within these categories of work, where large language models are now able to efficiently process and generate text at scale. Generative AI has propelled growth in high-value work across the sectors and may have depressed growth in low-value work. This supports a skills-biased technology change argument, which we’ve observed throughout modern work history. More specifically and within tech solutions, data science & analytics is a clear winner, with over 8% of growth in freelance earnings attributed to generative AI. This makes sense as the reinstatement effect is at work; new work and tasks such as prompt engineering have been created and popularized because of generative AI. Simultaneously, while tools such as ChatGPT automate certain scripting tasks (therefore leading to a replacement effect), it mainly results in productivity enhancements for freelancers and potentially leads to them charging higher rates and enjoying higher overall earnings per task. In terms of contracts related to business operations, we observe that accounting, administrative support, and legal services all experience gains in freelance earnings due to generative AI, ranging from 6% to 7%. In this sector, customer service is the only group that has experienced reduced earnings (-4%). The reduced earnings result for customer service contracts is an example of the aggregate earnings outcomes of AI, related to the study by Brynjolfsson et al (2023), who find that generative AI helps reduce case resolution time at service centers. A potential outcome of this cut in resolution time is that service centers will need fewer workers, as more tasks can be completed by a person working alongside AI. At the same time, the reinstatement effect has not materialized yet because there are no new tasks being demanded in such settings. This may be an instance where work transformation has not yet been fully realized, with AI enabling faster work rather than reinventing a way of working that leads to new types of tasks. A contrasting case is the transformation that happened with bank tellers when ATMs were introduced. While the introduction of these new technologies resulted in predictions of obsolete roles in banks, something different happened over time. Banks were able to increase efficiency as a result of ATMs and were able to scale and open more branches than before, thereby creating more jobs. In addition, the transactional role of a bank teller became focused on greater interpersonal skills and customer relationship tasks. When taken together, the overall gains in such business operations work on Upwork are an encouraging sign. These positions tend to require relatively intensive interpersonal communication, and it seems the short-term effects of generative AI have helped increase the value of these contracts, similar to what we saw in the banking industry when ATMs were introduced. As of now, the replacement effect of AI seems more noticeable in creative and outreach work. The exception is sales and marketing contracts, which have experienced a 6.5% increase in freelance earnings. There is no significant impact yet observed on design. For writing and translation, however, generative AI seems to have reduced earnings by 8% and 10% respectively. However, as we will discover, task complexity has a moderating effect on this. High-value work benefit from generative AI, upskilling needed for low-value work Having discussed the overall impact of generative AI across categories, we now decompose the impact by values. The reason we’re looking at the dimension of work value is that there may be a positive correlation between contract value and skill complexity. Moreover, skill complexity may also be positively correlated with skill levels. Essentially, by evaluating the impact of AI by different contract values, we can get at the question of AI's impact by skill levels. This objective is further underscored by a discrepancy that sometimes exists in the broader labor markets – a skills gap between demand and supply. It simply takes time for upskilling to take place, so it’s typical for demand to exceed supply until a more balanced skilled labor market takes place. It is worth noting, however, freelancers on the Upwork platform seem more likely than non-freelancers to acquire new skills such as generative AI. For simplicity, let’s assume that the value of contracts is a good proxy for the level of skill required to complete them. We’d then assume that high-skill freelancers typically do high-value work, and low-skill freelancers do low-value work. In other words, our goal is also to understand whether the impact of generative AI is skills-biased and follows a similar pattern from what we’ve seen in the past with new technology disruptions. Note that we’re focusing on the top and bottom tails of the distribution of contract values, because such groups (rather than median or mean) might be most susceptible to displacement and/or reinstatement effects, therefore of primary concern. We define high-value (HV) work as those with $1,000 or more earnings per contract. For the remaining contracts, we focus on a subset of work as low-value (LV) work ($251-500 earnings). Figure 2 shows the impact of AI by work value, across groups on Upwork. As we discussed before, writing and translation work has experienced some reduction in earnings overall. However, if we look further into the effect of contract value, we see that the reduction is largely coming from the reduced earnings from low-value work. At the same time, for these two types, generative AI has induced substantial growth in high-value earnings – the effect for translation is as high as 7%. We believe the positive effect on translation high-value earning is driven by more posts and contracts created. In the tech solutions sector, the growth in HV earnings in data science and web development is also particularly noticeable, ranging from 6% to 9%. Within the business solutions sector, administrative support is the clear winner. There are two takeaways from this analysis by work value. First, while we’re looking at a sample of all the contracts on the platform, it’s possible that the decline of LV work is more than made up for by the growth of HV work in the majority of the groups. In other words, except for select work groups, the equilibrium results for the Upwork freelance market overall seem to be net positive gains from generative AI. Second, if we assume that freelancers with high skills (or a high degree of skill complexity) tend to complete such HV work (and low-skill freelancers do LV work), we observe that the impact of generative AI may be biased against low-skill freelancers. This is an important result: In the current discussion of whether generative AI is skill-based, there exists limited evidence based on realized gains and actual work market transactions. We are one of the first to provide market-transaction-based evidence to illustrate this potentially skill-biased impact. Finally, additional internal Upwork analysis finds that independent talent engaged in AI-related work earn 40% more on the Upwork marketplace than their counterparts engaged in non-AI-related work. This suggests there may be additional overlap between high-skill work and AI-related work, which can further reinforce the earning potential of freelancers in this group. Figure 2 Case study: 3D content work To illustrate the impact of generative AI in more depth, we have conducted a case study of Engineering & Architecture work within the tech solutions sector. The reason is that we want to illustrate the potentially overlooked aspects of AI impact, compared with the examples of data science and writing contracts. This progress in generative AI has the potential to reshape work in traditional areas like design in manufacturing and architecture, which rely heavily on computer-aided design (CAD) objects, and newer sectors such as gaming and virtual reality, exemplified by NVIDIA's Omniverse. Based on activities on the Upwork platform, we see that there is consistent growth of job posts and client spending in this category, with up to 12% of gross service value growth year over year in 2023 Q3, and over 11% in job posts during the same period. Moreover, applying the synthetic control method, we show a causal relationship between gen AI advancements and the growth in job posts and earnings per contract. More specifically, there is a significant increase in overall earnings because of AI, an average 11.5% increase. Additionally, as shown by Figure 3, the positive effect also applies to earning per contract. This indicates a positive impact on freelancer productivity and quality of work, due to the fact that we’re measuring the income for every unit of work produced. This suggests that gen AI is not just a facilitator of efficiency but also enhances the quality of output. ‍Figure 3 Effect of Generative AI on Freelancer Earning per Contract in EngineeringIn a traditional workflow to create 3D objects without generative AI, freelancers would spend extensive time and effort to design the topology, geometry, and textures of the objects. But with generative AI, they can do so through text prompts to train models and generate 3D content. For example, this blog by NVIDIA’s Omniverse team showcases how ChatGPT can interface with traditional 3D creation tools. Thus, the positive trajectory of generative AI in 3D content generation we see is driven by several factors. AI significantly reduces job execution time, allowing for higher productivity. It facilitates the replication and scaling of 3D objects, leading to economies of scale. Moreover, freelancers can now concentrate more on the creative aspects of 3D content, as AI automates time-consuming and tedious tasks. This shift has not led to a decrease in rates due to the replacement effect. In fact, this shift of workflow may create new tasks and work. We will likely see a new type of occupation in which technology and humanities disciplines converge. For instance, a freelancer trained in art history now has the tools to recreate a 3D rendering of Japan in the Edo period, without the need to conduct heavy coding. In other words, the reinstatement effect of AI will elevate the overall quality and value proposition of the work, and ultimately enable higher earning gains. This paradigm shift underscores generative AI's role in not just transforming work processes but also in creating new economic dynamics within the 3D content market. Fortunately, it seems many freelancers on Upwork are ready to reap the benefits: 3D-related skills, such as 3D modeling, rendering, and design, are listed among the top five skills of freelancer profiles as well as in job posts. A dynamic interplay: task complexity, skills, and gen AI Focusing on the Upwork marketplace for independent talent, we study the impact of generative AI by using the public release of ChatGPT as a natural experiment. The results suggest a dynamic interplay of replacement and reinstatement effects; we argue that this dynamic is influenced by task complexity, suggesting a skill-biased impact of gen AI. Analysis across Upwork's work sectors shows varied effects: growth in freelance earnings in tech solutions and business operations, but a mixed impact in the creative sector. Specifically, high-value work in data science and business operations see significant earnings growth, while creative contracts like writing and translation experience a decrease in earnings, particularly in lower-value tasks. Using the case study of 3D content creation, we show that generative AI can significantly enhance productivity and quality of work, leading to economic gains and a shift toward higher-value tasks, despite initial concerns of displacement. Acemoglu and Restrepo (2019) argue that the slowdown of earning growth in the United States the past three decades can partly be explained by new technologies’ replacement effect overpowering the reinstatement effect. But with generative AI, we’re at a point of completely redefining what human tasks mean, and there may be ample opportunities to create new tasks and work. It's evident that while high-value types of work are being created, freelancers engaged in low-value tasks may face negative impact, possibly due to a lack of skills needed to capitalize on AI benefits. This situation underscores the necessity of supporting freelancers not only in elevating their marketability within their current domains but also in transitioning to other work categories. To ensure as many people as possible benefit, there’s an imperative need to provide educational resources for them to gain the technical skills, and more importantly skills of adaptability to reinvent their work. This helps minimize the chance of missed opportunities by limiting skills mismatch between talent and new demands created by new technologies. Upwork has played a significant role here by linking freelancers to resources such as Upwork Academy’s AI Education Library and Education Marketplace, thereby equipping them with the necessary tools and knowledge to adapt and thrive in an AI-present job market. This approach can help bridge the gap between low- and high-value work opportunities, ensuring a more equitable distribution of the advantages brought about by generative AI. Methodology To estimate the causal impact of generative AI, we take a synthetic control approach in the spirit of Abadie, Diamond, and Hainmueller (2010). The synthetic control method allows us to construct a weighted combination of comparison units from available data to create a counterfactual scenario, simulating what would have happened in the absence of the intervention. We use this quasi-experimental method due to the infeasibility of conducting a controlled large-scale experiment. Additionally, we use Lasso regularization to credibly construct the donor pool that serves the basis of the counterfactuals and minimize the chance of overfitting the data. Moreover, we supplement the analysis by scoring whether a sub-occupation is impacted or unaffected by generative AI. The scoring utilizes specific criteria: 1. Whether a certain share of job posts are tagged as AI contracts by the Upwork platform; 2. AI occupational exposure score, based on a study by Felten, Raj, and Seamans (2023), to tag these sub-occupations. We also use data smoothing techniques through three-month moving averages. We analyzed data collected on our platform from 2021 through Q3 2023. We specifically look at freelancer data across all 12 work categories on the platform for high-value contracts, defined as those with a contract of at least $1,000, and low-value contracts, consisting of those between $251 and under $500. The main advantage of our approach is that it is a robust yet flexible way to identify the causal effects on not only the Upwork freelance market but also specific work categories. Additionally, we control for macroeconomic or aggregate shocks such as U.S. monetary policy in the pre-treatment period. However, we acknowledge the potential biases in identifying which sub-occupations are influenced by generative AI and the effects of external factors in the post-treatment period. About the Upwork Research Institute The Upwork Research Institute is committed to studying the fundamental shifts in the workforce and providing business leaders with the tools and insights they need to navigate the here and now while preparing their organization for the future. Using our proprietary platform data, global survey research, partnerships, and academic collaborations, we produce evidence-based insights to create the blueprint for the new way of work. About Ted Liu Dr. Ted Liu is Research Manager at Upwork, where he focuses on how work and skills evolve in relation to technological progress such as artificial intelligence. He received his PhD in economics from the University of California, Santa Cruz. About Carina Deng Carian Deng is the Lead Analyst in Strategic Analytics at Upwork, where she specializes in uncovering data insights through advanced statistical methodologies. She holds a Master's degree in Data Science from George Washington University. About Kelly Monahan Dr. Kelly Monahan is Managing Director of the Upwork Research Institute, leading our future of work research program. Her research has been recognized and published in both applied and academic journals, including MIT Sloan Management Review and the Journal of Strategic Management.
    automation
    2024年02月23日
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