Microsoft’s April 2026 Rule of 70 program was open to U.S. employees at senior director level and below whose age and years of service added up to 70 or more, HR Executive reported at the time. The retirement offer covered about 8,750 eligible U.S. employees, per CNBC, excluding sales incentive-plan staff.

Amy Coleman, Microsoft’s chief people officer, framed the program positively in the memo announcing it, which CNBC obtained. “Our hope is that this program gives those eligible the choice to take that next step on their own terms, with generous company support,” Coleman wrote.

Buyouts before layoffs

This sequence suggests that Microsoft used the buyouts to measure the acceptance rate, then calculate the remaining headcount gap and cut to close it. Age plus tenure, rather than age alone, can be a design choice for reaching tenured, higher-paid employees while possibly avoiding age discrimination exposure.

HR Executive reported in March on an age discrimination suit against Meta alleging that workers over 50 were 2.5 times more likely to lose their jobs than those under 40 during a 2025 layoff round, with the suit pointing to salary-based selection criteria as a driver. Age-plus-tenure formulas like Microsoft’s are, in part, a response that doesn’t use age as a direct criterion.

The uptake numbers suggest the choice wasn’t an easy one for many eligible employees. Roughly two-thirds of eligible employees appear to have turned the offer down, based on the acceptance rate Business Insider reported. The structure was capped at 39 weeks of pay, with up to five years of continued health coverage and employees with 24 or more years of service also received 12 months of accelerated stock vesting, according to reports.

The post Microsoft’s workforce reduction strategy: Buyouts first, layoffs second appeared first on HR Executive.

One such coalition, RAISE US, was recently unveiled as a joint effort from state governments, AI firms and major employers, including Amazon, Anthropic and Microsoft, as “anchor partners.”

According to press materials announcing the nonprofit organization, other supporting employers include: ADP, AMD, Autodesk, Bank of America, Blackstone, Boston Consulting Group, Cisco, Cognizant, Deloitte, Eli Lilly and Company, General Motors, IBM, Infosys, Mastercard, Rockwell Automation, ServiceNow, UPS and Workday.

Building the workforce of the future

RAISE US will build the “workforce response to AI,” the organization says, with a focus on helping American talent “train, transition and thrive” in an AI-powered economy. Specifically, RAISE US pilot partners are working with the coalition to launch reskilling and redeployment programs, and create opportunities for displaced workers. The employers will also work closely with partners as they explore regulatory shifts like updates to unemployment insurance and potential employer incentives to navigate retention amid AI disruption, according to The Wall Street Journal.

“Coalition members are champions for workforce transition and co-design the pilots that build a shared understanding of what effective worker transition looks like in practice,” the organization says.

In a press release announcing its involvement in RAISE US, Amazon pointed to its own history of investing in workforce development—such as through its $2.5 billion commitment to a Future Ready 2030 project, which has already upskilled 31 million people worldwide, including 700,000 Amazon employees. The RAISE US partnership comes after Amazon itself cut about 10% of its workforce over the last year, amid massive AI investment.

“We believe this commitment to people is one of the most important investments we can make—both right now and for the workforce of the future, and we’re optimistic about what [AI] can do for people,” Amazon says. “But we also recognize that optimism without action isn’t enough. The transition to an AI-driven economy will create enormous opportunity, but only if we invest now in helping workers develop the skills to seize it.”

Meeting a rising need

RAISE US estimates that more than three-quarters of employers intend to upskill their current workforce amid AI disruption, with 50 million American jobs estimated to be “vulnerable” to AI, while the tech is expected to create 78 million net new jobs worldwide by 2030.

The demand for such massive transformation necessitates outside-the-box responses, such as through partnerships that unify government entities, employers and other stakeholders. Walmart took a similar approach in organizing its inaugural Opportunity Summit, a 2024 venture that convened experts across education, employment, government and more to create a “shared language” for in-demand frontline worker skills.

Donna Morris, chief people officer of Walmart and 2025 HR Executive of the Year, told HR Executive last year that the concept of bringing employers together to share knowledge, ideas and their vision for the future is going to become even more integral as AI disruption advances.

“Work gives a lot of people purpose—and if employers can come together to talk about how we reshape for the future, how we equip our workforces for the future, it not only strengthens one company, it strengthens the workforce more broadly,” she says.

The post Amazon, Microsoft help lead push to reskill workers displaced by AI appeared first on HR Executive.

In reality, most organizations are still struggling to answer a much simpler one: Can AI actually make work better?

Despite billions invested into AI transformation, many companies are still using these tools for surface-level productivity gains: drafting emails, summarizing meetings or generating generic content that employees often rewrite anyway.

The real opportunity is much bigger.

At Super.com, one of the most impactful applications has been within human resources—specifically, the administrative systems that quietly consume thousands of hours inside people and talent teams every year.

Internally, we often say our “second language” is AI. Not because we view it as a replacement for people, but because we see it as a capability embedded into how we operate, solve problems and scale the business.

That mindset led us to what we call “agentic HR.”

Not because AI is replacing human judgment, but because we are removing the operational friction that prevents HR leaders from spending time where they create the most value: retention, coaching, leadership development and culture.

That distinction matters.

See also: How HR execs can use operational excellence to compete on hiring

AI’s true future: Augmented execution, and building the culture around that

The future of HR is not automated empathy. It’s augmented execution.

One example has been compensation analysis. Historically, pay band reviews required manually parsing thousands of market data points across spreadsheets and benchmarking systems. What once took roughly 12 hours of manual work can now be completed in seconds using AI-supported workflows analyzing more than 5,000 data points simultaneously.

The impact is not simply speed.

It fundamentally changes the role of the HR team itself. Instead of acting as spreadsheet administrators, teams can spend their time designing better retention strategies, identifying compensation risks earlier and advising leadership with greater precision.

The same shift is happening in performance management.

Performance review preparation has traditionally been one of the most time-intensive processes for managers and HR teams alike. At scale, collecting examples, synthesizing feedback and drafting thoughtful evaluations can take hours per employee.

By securely analyzing internal work signals such as Slack discussions, Jira tickets and project contributions, AI-assisted workflows now help reduce first-draft review creation from roughly three hours to under one.

Importantly, the manager still makes the final judgment. Human context, emotional intelligence and leadership discretion remain essential.

But AI removes the administrative burden that often causes these processes to become rushed, delayed or inconsistent in the first place.

How AI has dramatically changed recruiting

Recruiting has also evolved dramatically.

In fast-growing companies, speed matters. Yet hiring processes are frequently slowed down by operational lag between initial planning conversations and actual execution.

By automating interview plans, scorecards and role descriptions, our talent acquisition team is working toward reducing the timeline from strategy meeting to live job posting from approximately three days to one.

That acceleration creates real business value. The best candidates move quickly, and organizations that cannot operationalize hiring efficiently often lose talent before interviews even begin.

But perhaps the most important outcome of agentic HR is not efficiency.

It’s sustainability.

HR teams are experiencing the same burnout pressures affecting the broader workforce. They are expected to manage organizational transformation, employee wellbeing, recruiting, culture, and increasingly, AI adoption itself—all while handling enormous administrative complexity behind the scenes.

AI, when implemented thoughtfully, can remove that hidden operational weight.

And ironically, that may be what preserves the human side of leadership in the AI era.

Because the more operational complexity AI helps manage, the more space leaders have for the work machines cannot do: building trust, coaching future leaders, navigating conflict, understanding nuance and creating cultures where people actually want to stay.

The companies that benefit most from AI will not necessarily be the ones that automate the fastest.

They will be the ones who become more human as a result of it.

The post Why HR must lead the AI culture shift appeared first on HR Executive.

“AI can make benefits simpler, more personalized and easier to use, but employees won’t embrace it unless they trust it,” said Michael Estep, president of Prudential Group Insurance. “That means helping people understand how these tools work, how their data are protected and how AI can strengthen the human support they still want and need when making important benefits decisions.”

Benefits may be one of the most practical places to build confidence in AI, helping employees navigate complex decisions with more clarity and support, according to the 2026 Benefits & Beyond study from Prudential Financial.

See also:

Among the key findings of the study:

• Trust and privacy are the biggest barriers. Although both employers (49%) and employees (52%) cite privacy and security as top concerns, employees are twice as likely to say they simply don’t trust AI (25% vs. 12%) in general. Concerns about inaccuracy, moral and ethical issues, and job loss are also more pronounced among employees.
• Adoption varies by workforce segment. Forty percent of unionized employees, 27% of salaried employees and 27% of sole decision-makers already use AI for benefits guidance, compared to lower rates among their peers.
• Employees are open to sharing data for personalization. Sixty-five percent of employees are comfortable with their employer managing their personal data for benefits purposes, rising to 75% among employees in technology-related roles.

In the company’s 2024 study, nearly seven in 10 employees said they wanted more personalized support during open enrollment. About nine in 10 were willing to share personal information such as age, health status, tobacco use and family history to receive tailored benefits recommendations. Although AI now has the potential to deliver that level of personalization, trust in how the technology is used remains a critical variable. As organizations look to close the gap between employer enthusiasm and employee confidence in AI, the research underscores the need for clear communication and hands-on education.

“Employee benefits are one of the clearest applications for AI, given how complex and individual these decisions can be,” said Scott Roth, vice president and chief technology officer for Prudential Group Insurance. “Many employees still struggle to navigate their benefits options. AI can help simplify that, but they need confidence in the guidance they receive and how their information is handled. When that trust is in place, it can drive stronger engagement and better outcomes.”

This article was originally published on BenefitsPRO, a sister site of HR Executive. For more content like this delivered to your inbox, sign up for BenefitsPRO newsletters here.

The post Employers want AI benefits support, but workers aren’t sold yet appeared first on HR Executive.

“Throughout his career, Keith has proven his dedication to delivering strong results for the hardworking people of our country, and I know he will do an incredible job in his new role,” Trump wrote. Sonderling’s nomination now moves to the Senate for confirmation.

Before Sonderling took over the DOL on an interim basis, he was Deputy Secretary of Labor, a role for which the Senate confirmed him in a 53-46 vote.

“I am deeply grateful to President Trump for his trust and confidence, for nominating me as the next United States Secretary of Labor,” Sonderling wrote Monday on his LinkedIn page. “Serving in both of President Trump’s administrations has been one of the greatest privileges of my life.”

If confirmed, he writes, he looks forward to “continuing that service … and advancing the president’s agenda on behalf of America’s workers, families, unions and job creators.”

Keith Sonderling’s HR connections

Before the Deputy Commissioner nod, Sonderling served as a commissioner with the Equal Employment Opportunity Commission, a role that made him a known entity within HR tech communities, as he weighed in frequently—including through involvement in the HR Tech Conference—on AI risk. He has publicly criticized the growing patchwork of state AI laws and emphasized employer liability alongside vendor responsibility in AI-driven discrimination.

“Whether it’s designed improperly or used improperly, employers are going to be 100% liable for whatever decisions these tools are making,” Sonderling told the audience at HR Tech in 2024.

He has also made moves to create more uniform support for workers amid AI disruption, including through the creation of the AI Literacy Framework and accompanying text-based AI training for American workers.

When Sonderling was nominated to the Deputy Secretary position, Bradford J. Kelley and Lorenzo Riboni at labor and employment law firm Littler wrote that he had exhibited a preference for deregulation and compliance assistance, both of which could shape the coming priorities for the DOL on AI and other issues.

During his time at the helm of the Wage and Hour Division at DOL, Sonderling authored an opinion letter classifying gig workers as employees for purposes of the FLSA. The accompanying rule was overturned when President Biden took office, but has since been revised under Trump. In his WHD time, Sonderling was also credited with the creation of the Payroll Audit Independent Determination Program as a means of driving self-audit compliance with FLSA among employers, which he again rolled out over the last year.

The post Trump’s Labor Secretary pick could reshape AI enforcement appeared first on HR Executive.

“For the first time, organizations can increase output, accelerate decision-making and expand market reach without scaling headcount at the same rate,” says Ronni Zehavi, CEO and co-founder of HR technology platform HiBob. He predicts that the organizations that pull ahead will be the ones that can redeploy talent quickly, pair human judgment with machine intelligence and out-adapt their competitors—not necessarily the ones with the largest workforces.

Workforce design wins

He suggests that the companies realizing AI ROI have paired technology investment with organizational redesign. “Too many organizations are approaching AI as a technology implementation rather than a workforce transformation initiative,” Zehavi says. “They’re investing in tools while leaving the underlying operating model unchanged.”

Zehavi isn’t alone in this insight. His view echoes Josh Bersin’s long-running argument that companies are moving toward flatter, team-based structures as technology and work patterns change. In his HR Tech Europe 2026 keynote, Bersin suggested the real opportunity is to raise performance, not simply reduce costs, and that some companies are focusing on the wrong goal.

Zehavi says the companies getting it right are organizing around skills, capabilities and outcomes rather than static job descriptions. They are also pushing decision-making closer to where work actually happens. That kind of redesign is harder for large enterprises due to decades of governance layers, rigid role structures and fragmented systems that create drag, according to Zehavi.

Mid-sized companies often have an advantage because they have fewer legacy structures to unwind, according to Zehavi. He says orgs in this size range can often move from experimentation to execution faster. “The winners of the AI era won’t necessarily be the organizations with the biggest AI budgets,” Zehavi says. “They’ll be the organizations that can translate technological capability into organizational agility.”

Layoffs aren’t the big story

Though the headlines highlight the recent wave of enterprise layoffs tied to AI, this outlook may miss the more consequential story. “The debate around AI has focused too heavily on job elimination and not enough on work transformation,” Zehavi says. “AI is changing the composition of work itself. Tasks are being automated, accelerated and redistributed. The boundaries of traditional roles are beginning to blur.”

Leading organizations are using disruption as a talent strategy through unlocking capacity, elevating higher-value work and redeploying people toward emerging priorities. The real divide won’t be between workers who are replaced and workers who aren’t, Zehavi says. “It will be between organizations that build adaptive workforces and those that fail to.” He points to internal talent marketplaces, continuous reskilling and clearer pathways for people to evolve alongside the business as the levers that will separate leading organizations from lagging ones.

The company of the future

“The company of the future is not simply leaner. It is fundamentally more dynamic,” he says. In his view of the future, fixed jobs, rigid hierarchies and annual planning cycles give way to fluid structures organized around skills, capabilities, projects and outcomes. “Skills are becoming the new currency of work,” he says.

In that model, leaders have real-time visibility into workforce capabilities, emerging skills gaps and future talent needs. Teams form and reform around business priorities and talent moves more easily across functions. “Managers become coaches, orchestrators and capability builders rather than supervisors of process,” Zehavi says. “Their role is increasingly focused on enabling performance, accelerating development and helping teams navigate constant change.”

The most successful companies won’t be those that automate the most, Zehavi says. They will be the ones who build the strongest partnership between humans and machines. “The future of work isn’t defined by AI replacing people,” he says. “It’s defined by organizations becoming dramatically better at understanding, developing and deploying human potential at scale.”

The post The death of the megacorporation may be a bigger story than layoffs appeared first on HR Executive.

AMS strengths

Korn Ferry announced the agreement on June 29. Once it closes—expected in the company’s second fiscal quarter of FY2027 pending regulatory clearance—the combined firm will have more than 16,000 employees and will place a candidate roughly every 90 seconds, according to the company.

The release indicated that AMS brings about $650 million in annual fee revenue, operations across 120 countries and a service mix spanning RPO, early careers and campus recruiting, contingent workforce solutions and skills creation. According to the announcement, AMS’s long-term agreements add more than $1.5 billion in estimated fees remaining under existing contracts.

Read more: The legal landscape for AI in hiring is shifting, and HR leaders need to think ahead

‘Very happy clients’

Industry analyst Josh Bersin told HR Executive that the demand picture remains strong even as AI tools proliferate across sourcing and screening. “AMS is a very well-run, successful talent acquisition outsourcing and advisory company, with $1.5 billion in backlog and very happy clients.”

For talent acquisition leaders weighing build-versus-buy decisions, the deal suggests continued consolidation among the firms that manage hiring at scale.

“Despite the growth in AI, there remains a massive demand for recruitment outsourcing and services, plus AMS One is one of the only integrated platforms to manage a heterogeneous recruiting stack,” Bersin said. “I think Korn Ferry has acquired a very valuable company and now, coupled with [its own] consulting and executive search, the company has the potential to grow in many new markets.”

Korn Ferry expects the deal to boost its earnings per share within the first full year after integration costs, according to the release. Founder Rosaleen Blair will continue as chair, and AMS CEO Gordon Stuart will stay on through the transition.

The post Korn Ferry buys AMS in $1.1 billion bet on recruitment outsourcing appeared first on HR Executive.

Date & Time: Thursday, July 23, 2026 at 3:00 pm ET

Speaker:

Allie K. Miller, Artificial Intelligence Business Leader and International Speaker

Description:

What is human-centered AI in the workplace? It’s a question challenging leaders across industries, and your answer may determine if your organization will leverage these tools to succeed in the future.

In this exclusive webinar, we’re joined by Allie K. Miller, one of Time’s 100 most influential people in AI for 2025 and an adviser to companies like Samsung, Google, OpenAI and Anthropic. By examining documented cases, Miller helps us examine human-centered AI in a way that goes far beyond the don’t-get-left-behind approach that’s so prevalent in AI discussions. Miller explains possible outcomes of AI implementation and how to develop strategies that are both scalable and metric-driven.

Change isn’t easy, so Miller discusses ways to prove AI ROI to a CFO as she challenges some of the biggest misconceptions about adding AI to your tool stack. For anyone eager to be truly effective in the age of AI, this webinar is one you can’t miss.

You will learn:

• How to demonstrate clear ROI from AI investments, equipping you with the tools to build a compelling business case for leadership and finance teams
• Common misconceptions about integrating AI into your tool stack
• Strategies for HR professionals to integrate AI ethically and responsibly

Register Now

The post AI for HR Professionals: How to Build an AI-First Business That Empowers Employees appeared first on HR Executive.

The data was tied to an AI training program that collected keystrokes, mouse movements and screen content from U.S. employees. “We have carefully designed ​this program with privacy safeguards and while we have no indication at this ⁠time ⁠that any data was ⁠improperly accessed ​by Meta employees, we’re pausing it while we investigate,” said company spokesperson Tracy Clayton, as reported by U.S. News and World Report.

Employees don’t trust monitoring

An AI program built around employee behavior can raise concerns from employees, even if a security event never occurs. When workers believe their activity is being watched, recorded or repurposed, the stakes move beyond technology enhancements into trust and culture. Studies on electronic monitoring show that employee acceptance depends on perceived purpose and fairness, and that intrusive tracking can undermine trust and create conflict.

According to a 2023 i4cp study, only 6% of large companies reported they use employee surveillance tools. “No one likes the idea of Big Brother,” said Katheryn Brekken, senior research analyst at i4cp, in a SHRM article on the topic. “i4cp research shows that productivity flourishes in environments of high trust, and out of all the dimensions of trust we studied last year, employees’ trust in senior leadership was the most impactful.”

Read more: Inside Meta, layoffs and AI shakeups have pushed morale to the edge

What’s the risk for HR?

In Meta’s case, the reported exposure included prompts, transcriptions, private conversations and information tied to people and performance. That kind of content is difficult to separate from HR concerns, especially if employees believe the data could influence evaluations or support surveillance.

Recent 2026 roundups suggest monitoring is now common across many organizations, but those figures are broader than the 2023 i4cp estimate, which referred specifically to employee surveillance tools in large companies.

Meta has already faced internal pushback over the monitoring program before this latest issue surfaced, according to reporting in Reuters. Employees objected to a system that tracked keystrokes and mouse activity to train AI models, and the company later adjusted parts of the program, including offering limited pause windows and exemption requests.

The post Meta’s AI training program sparks new employee data, trust concerns appeared first on HR Executive.

What followed was six weeks of the most specific security scrutiny we’d ever faced.

Because the platform’s proprietary AI layer helps managers and recruiters make compensation-related decisions, their team classified our agents as “Tier 1,” the highest internal risk category. The scrutiny was especially intense because the system processes confidential pay data and employee personal data in an employment context that is increasingly treated as high-risk under emerging AI governance frameworks.

From there, the questions got granular fast. Could the system produce a recommendation without using the candidate’s name? How is test data segregated from production? What does the human override mechanism look like, and is every override logged? How do we demonstrate that protected-class data is excluded from model inputs before any calculation runs? What frameworks govern our AI risk reviews, and how often do they happen?

See also: Buying AI? The questions HR leaders should be able to answer

These weren’t gotcha questions. They were the questions every serious enterprise security team should be asking about an AI system that supports or materially influences compensation-related decisions. We answered all of them—with evidence.

Spoiler: We cleared the review.

The reason I’m sharing this is because that review is coming for every AI agent in your stack, and most companies aren’t ready for it.

Not all AI vendors move with governance in mind

The AI vendors moving fastest right now are, almost by design, the ones that haven’t done this work. Shipping a product that demos well takes weeks. Building the infrastructure that survives a Tier 1 security review takes far longer.

That infrastructure includes SOC 2 Type II and ISO 27001 certifications, tenant-level data isolation and bias controls that exclude protected-class attributes from production decision inputs where appropriate and use testing and monitoring to detect and mitigate bias, including proxy effects. It includes an explainability layer that produces a plain-language rationale for every output, one that holds up when a regulator, a board member or an employee’s attorney asks why the system recommended that number. It means human-in-the-loop design baked into the architecture, not bolted on afterward. Audit logs that capture every input, output and override. Quarterly AI risk reviews aligned to ISO 42001 and the NIST AI Risk Management Framework. And more. Much more.

Most point solutions don’t have this infrastructure. Vendors are failing AI reviews because they can’t explain the outcomes. One HR tech platform went through a similar Tier 1 review for talent matching. The matching worked. But when the compliance team asked why two similar candidates ranked differently, the answer wasn’t reproducible. The model’s skills inference introduced variability that they couldn’t document or defend. They could not satisfy the buyer’s AI governance review.

This level of explainability is the bar every AI system touching HR decisions is about to be measured against: not just whether the output was right, but whether you can explain consistently why the system produced it.

The trail to AI governance may be rigorous, but it’s worth it

The rigor looks different depending on the organization, but the bar is the same. A large global technology distributor required that we clear reviews across seven separate internal committees: Cybersecurity, Ethics and Compliance, Tech Infrastructure, Architecture, Data Privacy, Legal and Internal Audit. Each one had its own requirements. We cleared them all.

Clearing these reviews requires infrastructure that many organizations aren’t yet equipped to build on their own, though the instinct to try is understandable. You control the roadmap, l the data and you don’t have to negotiate AI terms with a vendor. But it doesn’t exempt you from the regulatory burden. It means you carry it alone.

And that burden keeps growing. The EU AI Act classifies pay-related AI systems as high-risk, with new obligations for both providers and deployers taking effect between mid-2026 and December 2027. Colorado and Texas already have their own AI laws on the books.  Maintaining this infrastructure isn’t a project. It’s an ongoing organizational commitment to a landscape that keeps moving underneath it.

If you’re asking an AI vendor you’re evaluating, “Does it use AI?,” you’re asking the wrong question. What you need to ask is: “Has the platform been built for governance?”

That difference doesn’t show up in a demo. It shows up when your IT security team starts asking questions.

The post The one question worth asking every AI vendor appeared first on HR Executive.