美国联邦贸易委员会（FTC）FTC 宣布全国范围内禁止竞业协议，详细请看
美国联邦贸易委员会（FTC）于2024年4月23日发布最终规定，全国范围内禁止非竞争协议。此举旨在通过保护工人更换工作的自由来促进竞争，增加创新，并推动经济增长。根据FTC的预测，新业务的形成将每年增加2.7%，预计每年将新增超过8500家新企业。此外，预计工人的平均收入将增加524美元，未来十年内医疗费用预计将减少高达1940亿美元。同时，预计该规定还将在未来十年内每年新增17000至29000项专利。
详情以英文版为准：
FTC Announces Rule Banning Noncompetes
FTC’s final rule will generate over 8,500 new businesses each year, raise worker wages, lower health care costs, and boost innovation
Today, the Federal Trade Commission issued a final rule to promote competition by banning noncompetes nationwide, protecting the fundamental freedom of workers to change jobs, increasing innovation, and fostering new business formation.
“Noncompete clauses keep wages low, suppress new ideas, and rob the American economy of dynamism, including from the more than 8,500 new startups that would be created a year once noncompetes are banned,” said FTC Chair Lina M. Khan. “The FTC’s final rule to ban noncompetes will ensure Americans have the freedom to pursue a new job, start a new business, or bring a new idea to market.”
The FTC estimates that the final rule banning noncompetes will lead to new business formation growing by 2.7% per year, resulting in more than 8,500 additional new businesses created each year. The final rule is expected to result in higher earnings for workers, with estimated earnings increasing for the average worker by an additional $524 per year, and it is expected to lower health care costs by up to $194 billion over the next decade. In addition, the final rule is expected to help drive innovation, leading to an estimated average increase of 17,000 to 29,000 more patents each year for the next 10 years under the final rule.
Noncompetes are a widespread and often exploitative practice imposing contractual conditions that prevent workers from taking a new job or starting a new business. Noncompetes often force workers to either stay in a job they want to leave or bear other significant harms and costs, such as being forced to switch to a lower-paying field, being forced to relocate, being forced to leave the workforce altogether, or being forced to defend against expensive litigation. An estimated 30 million workers—nearly one in five Americans—are subject to a noncompete.
Under the FTC’s new rule, existing noncompetes for the vast majority of workers will no longer be enforceable after the rule’s effective date. Existing noncompetes for senior executives - who represent less than 0.75% of workers - can remain in force under the FTC’s final rule, but employers are banned from entering into or attempting to enforce any new noncompetes, even if they involve senior executives. Employers will be required to provide notice to workers other than senior executives who are bound by an existing noncompete that they will not be enforcing any noncompetes against them.
In January 2023, the FTC issued a proposed rule which was subject to a 90-day public comment period. The FTC received more than 26,000 comments on the proposed rule, with over 25,000 comments in support of the FTC’s proposed ban on noncompetes. The comments informed the FTC’s final rulemaking process, with the FTC carefully reviewing each comment and making changes to the proposed rule in response to the public’s feedback.
In the final rule, the Commission has determined that it is an unfair method of competition, and therefore a violation of Section 5 of the FTC Act, for employers to enter into noncompetes with workers and to enforce certain noncompetes.
The Commission found that noncompetes tend to negatively affect competitive conditions in labor markets by inhibiting efficient matching between workers and employers. The Commission also found that noncompetes tend to negatively affect competitive conditions in product and service markets, inhibiting new business formation and innovation. There is also evidence that noncompetes lead to increased market concentration and higher prices for consumers.
Alternatives to Noncompetes
The Commission found that employers have several alternatives to noncompetes that still enable firms to protect their investments without having to enforce a noncompete.
Trade secret laws and non-disclosure agreements (NDAs) both provide employers with well-established means to protect proprietary and other sensitive information. Researchers estimate that over 95% of workers with a noncompete already have an NDA.
The Commission also finds that instead of using noncompetes to lock in workers, employers that wish to retain employees can compete on the merits for the worker’s labor services by improving wages and working conditions.
Changes from the NPRM
Under the final rule, existing noncompetes for senior executives can remain in force. Employers, however, are prohibited from entering into or enforcing new noncompetes with senior executives. The final rule defines senior executives as workers earning more than $151,164 annually and who are in policy-making positions.
Additionally, the Commission has eliminated a provision in the proposed rule that would have required employers to legally modify existing noncompetes by formally rescinding them. That change will help to streamline compliance.
Instead, under the final rule, employers will simply have to provide notice to workers bound to an existing noncompete that the noncompete agreement will not be enforced against them in the future. To aid employers’ compliance with this requirement, the Commission has included model language in the final rule that employers can use to communicate to workers.
The Commission vote to approve the issuance of the final rule was 3-2 with Commissioners Melissa Holyoak and Andrew N. Ferguson voting no. Commissioners’ written statements will follow at a later date.
The final rule will become effective 120 days after publication in the Federal Register.
Once the rule is effective, market participants can report information about a suspected violation of the rule to the Bureau of Competition by emailing noncompete@ftc.gov.
The Federal Trade Commission develops policy initiatives on issues that affect competition, consumers, and the U.S. economy. The FTC will never demand money, make threats, tell you to transfer money, or promise you a prize. Follow the FTC on social media, read consumer alerts and the business blog, and sign up to get the latest FTC news and alerts.
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2024年04月23日
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EEOC Issues Final Regulation on Pregnant Workers Fairness Act美国平等就业机会委员会（EEOC）发布了《怀孕工作者公平法案》（PWFA）的最终规则，该规则自2023年6月27日生效，要求15名以上员工的雇主为怀孕、分娩或相关医疗条件的员工提供合理的工作调整，除非这种调整给雇主带来过大困难。此规则进一步加强了1964年民权法案和美国残疾人法案下的保护措施，提供了关于合理调整、雇主责任及孕期工作者权利的更清晰指导。
Aids Implementation of Civil Rights Law Expanding Protections and Accommodations for Pregnant Workers
WASHINGTON -- The U.S. Equal Employment Opportunity Commission (EEOC) today issued a final rule to implement the Pregnant Workers Fairness Act (PWFA), providing important clarity that will allow pregnant workers the ability to work and maintain a healthy pregnancy and help employers understand their duties under the law. The PWFA requires most employers with 15 or more employees to provide “reasonable accommodations,” or changes at work, for a worker’s known limitations related to pregnancy, childbirth, or related medical conditions, unless the accommodation will cause the employer an undue hardship.
The PWFA builds upon existing protections against pregnancy discrimination under Title VII of the Civil Rights Act of 1964 and access to reasonable accommodations under the Americans with Disabilities Act. The EEOC began accepting charges of discrimination on June 27, 2023, the day on which the PWFA became effective.
The final rule will be published in the Federal Register on Apr. 19. The final rule was approved by majority vote of the Commission on Apr. 3, 2024, and becomes effective 60 days after publication in the Federal Register.
The final rule and its accompanying interpretative guidance reflect the EEOC’s deliberation and response to the approximately 100,000 public comments received on the Notice of Proposed Rulemaking. It provides clarity to employers and workers about who is covered, the types of limitations and medical conditions covered, how individuals can request reasonable accommodations, and numerous concrete examples.
“The Pregnant Workers Fairness Act is a win for workers, families, and our economy. It gives pregnant workers clear access to reasonable accommodations that will allow them to keep doing their jobs safely and effectively, free from discrimination and retaliation,” said EEOC Chair Charlotte A. Burrows. “At the EEOC, we have assisted women who have experienced serious health risks and unimaginable loss simply because they could not access a reasonable accommodation on the job. This final rule provides important information and guidance to help employers meet their responsibilities, and to jobseekers and employees about their rights. It encourages employers and employees to communicate early and often, allowing them to identify and resolve issues in a timely manner.”
Highlights from the final regulation include:
· Numerous examples of reasonable accommodations such as additional breaks to drink water, eat, or use the restroom; a stool to sit on while working; time off for health care appointments; temporary reassignment; temporary suspension of certain job duties; telework; or time off to recover from childbirth or a miscarriage, among others.
· Guidance regarding limitations and medical conditions for which employees or applicants may seek reasonable accommodation, including miscarriage or still birth; migraines; lactation; and pregnancy-related conditions that are episodic, such as morning sickness. This guidance is based on Congress’s PWFA statutory language, the EEOC’s longstanding definition of “pregnancy, childbirth, and related medical conditions” from Title VII of the Civil Rights Act of 1964, and court decisions interpreting the term “pregnancy, childbirth, or related medical conditions from Title VII.
· Guidance encouraging early and frequent communication between employers and workers to raise and resolve requests for reasonable accommodation in a timely manner.
· Clarification that an employer is not required to seek supporting documentation when an employee asks for a reasonable accommodation and should only do so when it is reasonable under the circumstances.
· Explanation of when an accommodation would impose an undue hardship on an employer and its business.
· Information on how employers may assert defenses or exemptions, including those based on religion, as early as possible in charge processing.
More information about the PWFA and the EEOC’s final rule, including resources for employers and workers, is available on the EEOC’s “What You Should Know about the Pregnant Workers Fairness Act” webpage.
For more information on pregnancy discrimination, please visit https://www.eeoc.gov/pregnancy-discrimination.
The EEOC prevents and remedies unlawful employment discrimination and advances equal opportunity for all. More information is available at www.eeoc.gov. Stay connected with the latest EEOC news by subscribing to our email updates.
头条
2024年04月19日
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The 10 golden rules for establishing a people analytics practice十大黄金法则：
战略适配性：确保人力资源分析项目与组织的战略目标对齐，以实现最大的价值和影响。
持续的员工倾听：通过整合员工和业务的声音，优先处理正确的战略人力资源问题。
证据基础的HR服务整合：将所有基于证据的HR服务整合到一个功能中，提升人力资源分析的交付速度和质量。
清晰的人力资源分析操作模型：建立一个目标操作模型，明确客户、可交付服务、服务水平和交付时间。
数据隐私合规性：遵守数据隐私法规，同时考虑数据分析在文化和业务连续性方面的影响。
数据驱动决策的HR能力提升：通过提升HR社区的数据和洞察力使用，将业务机会转化为分析服务。
管理HR数据：建立集中的企业级数据基础设施，改善数据的组合、共享和分析能力。
产品设计和思维：确保人力资源分析服务的用户设计友好，易于导航，并激励用户在决策中使用数据。
实验与最小可行产品：通过实验和最小可行产品，逐步评估和改进解决方案，避免大规模实施失败。
利用人工智能的潜力：构建和实施基于机器学习的AI功能，确保模型的性能和有效性，同时控制数据偏见和合法性。
这些法则展示了通过系统方法创建并采纳人力资源分析实践的重要性，强调了以数据和证据为基础支持人力资源功能的必要性。
It is time for an update on my previous posts on the 10 golden rules of people analytics, simply because so much has happened since then. For example, continuous employee listening, artificial intelligence (AI in HR), agile HR, employee experience, strategic workforce management, and hybrid working are just a few emerging topics in recent years listed in Gartner's hype cycle for HR transformation (2023).
In the last year, I have spoken to many people working in different organisations on establishing people analytics as an accepted practice. I have also joined some great conferences (HRcoreLAB, PAW London & Amsterdam) where I learned from excellent speakers. I also (re)engaged with some excellent people analytics and workforce management vendors, such as Crunchr, Visier, eQ8, AIHR, One Model, Mindthriven, and Agentnoon. Finally, I also enjoyed having multiple elevating discussions with some thought leaders who influenced my thinking (e.g., David Green, Rob Briner, Jonathan Ferrar, Dave Millner, Sjoerd van den Heuvel, Ian O'Keefe, Brydie Lear, Jaap Veldkamp, RJ Milnor, and Nick Kennedy).
These encounters and my ongoing PhD research on adopting people analytics resulted in a treasure trove of new ideas and knowledge that confirmed my experience and beliefs that it is all about creating an embraced people analytics practice using a systemic approach in supporting HR in becoming more evidence-based. So, like I said, it's time for an update. I hope you enjoy and appreciate the post, and I invite you to engage and react in the comments or send me a direct message.
Create a strong strategy FIT.
It is obvious but not a common practice that your people analytics portfolio needs to align or fit with your strategic organisational goals. A strong strategic FIT ensures you execute people analytics projects with the most value and impact on your organisation. It is, therefore, important to integrate the decision-making on where to play in people analytics with your periodic HR prioritisation process.
Strategic workforce management and continuous employee listening are pivotal in prioritising the right strategic workforce issues
The bigger picture is that two people analytics-related HR interventions, strategic workforce management and continuous employee listening, are pivotal in prioritising the right strategic workforce issues. By blending the insights from these HR interventions, you ensure you are prioritising based on the voice of the business and the voice of the employee. See also my previous post on strategic workforce management. Because people analytics is at the core of these HR interventions and provides many additional strategic insights, I argue we need a new HR operating model where the people analytics practice is positioned at the centre of HR.
I argue that we need a new HR operating model where the people analytics practice is positioned at the centre of HR
Grow and integrate evidence-based HR services.
Based on my experience and research, I strongly advise integrating all evidence-based HR services into one function. See also my previous post on establishing a people analytics practice. This integration will enhance the speed and quality of your people analytics delivery, make you a trusted analytical strategic advisor, and make you a more attractive employer for top people analytics talent. All other people analytics function setups seem like compromises.
With evidence-based HR services, I refer to activities such as reporting, advanced analytics, survey management, continuous employee listening, organisational design and strategic workforce management. It is hardly ever that a strategic question is answered by only one of these services. In most cases, you will need to combine survey management (i.e., collecting new data), perform advanced analytics (i.e., build a predictive model), and share the outcomes in a dashboard (i.e., reporting) or build new system functionality based on the models (e.g., vacancy recommendation).
You will need to combine various people analytics services to provide real strategic value
Create a clear people analytics operating model.
Because the people analytics practice is maturing, it deserves a clear target operating model. In a target operating model, you clarify to the organisation whom you consider your clients, what services or solutions you can deliver, what service levels your clients can expect, and when and how you will deliver the solution.
Being transparent about your target operating model will build trust and legitimacy in your organisation. Inspired by the work of Insight222, a people analytics target operating model consists of a demand engine (understanding and prioritising demand), a solution engine (e.g., data management, building models, designing surveys), and a delivery engine (e.g., dashboards, advisory with story-telling, bringing models to production), ideally covering all the evidence-based HR services mentioned under rule 2 in this post. Additionally, more practices are applying agile principles to increase time-to-delivery and are using some form of release management to balance capacity.
Built trust and legitimacy
Compliance with data privacy regulations has been an important topic since the early days of people analytics ten years ago. Even before the GDPR era, organisations did well to understand when personal data could be collected, used, or shared. Legislation such as GDPR offers guidance and more structure to organisations on how to deal with data privacy issues.
Being fully compliant is not where responsible data handling ends
However, being fully compliant is not where responsible data handling ends. Simply because you can, according to data privacy regulations, doesn't mean you should. There are also contextual and ethical elements to take into account. For example, being able and regulatory-wise allowed to build an internal sourcing model matching internal employees with specific skills with internal vacancies doesn't mean you should. From a cultural or business continuity perspective, creating internal mobility may not be beneficial or desired in specific areas of your organisation. Assessing the implications of using data analytics in a broader context than just regulations will also enhance the needed trust and legitimacy.
Upskill HR in data-driven decision-making
Having a mature people analytics practice that delivers high-quality, evidence-based HR services is not enough to ensure value creation for your organisation. Suppose your organisation, including your HR community, struggles to translate business opportunities into analytical services or finds it hard to use data and insights on a daily basis in their decision-making. In that case, upskilling is a necessary intervention.
HR upskilling in data-driven decision-making is a necessity in growing towards a truly evidence-based HR culture
Creating awareness of the various analytical opportunities, developing critical thinking, creating an inquisitive mindset, identifying success metrics for HR interventions and policies, evaluating these metrics, and understanding the power of innovative data services, such as generative AI, is essential. When upskilling, be sure to recognise the different HR roles and their needs and preferences. For example, your HR business partners will likely want to develop their skills in identifying strategic workforce metrics and strategic workforce management. However, your COE lead (i.e., HR domain leads) wants to develop their ability to collect and understand internal clients' feedback and improve their HR services (e.g., recruitment, learning programs, leadership development). So, diversify your learning approach to make it more effective.
Manage your HR data
There is enormous value in integrating your HR and business data in a structured matter. Integrated enterprise-wide data allows you to combine, improve, share, and analyse data more efficiently. More organisations are using data warehouse and data lake principles to create this central enterprise-wide data infrastructure based on, for example, Microsoft Azure or Amazon Web Services technology.
A mature people analytics team is best equipped to create an HR data strategy and manage the corresponding data pipeline.
HR would do well to improve its capability to manage the data pipeline by hiring data engineers. It is an interesting discussion about where to position this data management capability and related skill set. The first thought is to position this capability close to the HR systems and infrastructure function. This setup might work perfectly. However, based on your HR context and maturity, I argue that the people analytics practice is a good and sometimes better alternative. Mature people analytics teams are likely more able to think about data management and creating data products and services built with machine learning models. Traditional HR systems and infrastructure teams may tend to focus too much on the efficiency of the HR infrastructure (e.g., straight-through processing, rationalising the HR tech landscape).
Excel in product design and thinking
Successful people analytics or evidence-based HR services excel in product design. Whether built with PowerBI or vendor-led BI platforms (e.g., Crunchr, Visier, One Model), dashboards must be user-friendly, easy to navigate, and motivate users to work with data in their decision-making. The same applies to functionality based on machine learning models, such as chatbots, learning assistants, or vacancy recommendations. The user design, the functionality provided, and the flawless and timely delivery all contribute to maximising the usage of these analytical services and, ultimately, decision-making.
Strong product design and thinking requires product owners to have a marketing mindset
As important as the product design is product thinking by the product owner. A product owner for, e.g., recruitment or leadership programs, should be constantly interested in hearing what internal clients think about their products. This behaviour requires product owners to have a marketing mindset. As part of a larger continuous listening program, an internal client feedback mechanism should provide the necessary information to improve your products and services continuously. A product owner should be curious about questions like: Are your internal clients satisfied? Should we tailor the products for different user types? What functionality can we improve or add?
Allow yourself to experiment
When a solution looks good and makes sense based on your analytics, management tends to go for an immediate big-bang implementation. However, don't be afraid to experiment and learn before rolling out your solution to all possible users. Starting with a minimum viable product (i.e., MVP) allows you to evaluate your product among a select group of users early in the development process. Based on feedback, you can enhance your product incrementally (i.e., agile) manner.
It also enables you, when valuable, to compare treatment groups with non-treatment groups. These types of experiments (i.e., difference-in-difference comparisons) help you to evaluate the effect the new product intends to have. People analytics services can support this incremental approach, testing a minimal viable product (MVP) and obtaining feedback to provide additional insights that may avoid a big implementation failure of your new products.
Embrace the potential of AI in HR
Today, artificial intelligence (AI) is predominantly based on machine learning (ML). These AI-ML models provide powerful functionality such as vacancy and learning recommendations, chatbots, and virtual career or work schedule assistants. There is no need to fear these applications, but having a deeper understanding of them is necessary. However, implementing these types of functionality without checking and validating them is risky and, therefore, unwise.
A mature people analytics practice allows you to build your own machine-learning-based AI functionality
A mature people analytics practice allows you to create and build these AI functionalities internally. You can also buy AI functionality by implementing a vendor tool, but please ensure you do not end up with a new vendor for each AI functionality you desire. If you choose to buy AI functionality, the people analytics team should act as a gatekeeper. Internally built machine learning models are subject to checks and balances. And rightfully so. However, the same should apply to ML-based AI functionality from external providers. The people analytics team should check the performance and validity of the model and control for biases in the data and legal and ethical justification.
The people analytics leader can make the difference
If you are the people analytics leader within your organisation, it might be daunting or reassuring to hear that you can make the difference between failure and success. You bring the people analytics practice alive by reaching out to stakeholders, developing your team, understanding your clients, learning from external experts, and building a road map to analytical maturity.
A successful people analytics practice starts with the right people analytics leader
As a people analytics leader, you should excel in business acumen, influencing skills, strategic thinking, critical and analytical thinking, understanding the HR system landscape, understanding the possibilities of analytical services, project management, and, last but not least, people management (as all leaders should). The result of having all these capabilities is that a people analytics leader, together with the people analytics team, becomes a trusted advisor to senior management, understands the most pressing issues within an organisation, can effectively manage the HR data pipeline, and can build new analytical services to enhance decision-making and ultimately drive organisational performance and employee well-being.
I hope you enjoyed my update on the 10 golden rules for establishing people analytics practice. If you enjoyed the post, please hit ? or feel invited to engage and react in the comments. Send me a direct message if you want to schedule a virtual meeting to exchange thoughts one-on-one.
Thanks to Jaap Veldkamp for reviewing.
作者 ：Patrick Coolen
https://www.linkedin.com/pulse/10-golden-rules-establishing-people-analytics-practice-patrick-coolen-85use/
头条
2024年04月15日
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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
头条
2024年04月12日
头条
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!
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