Breslow cofounded Bolt in 2014 out of his Stanford dorm room, building it into a major player in online checkout before it soared to an $11 billion valuation in 2022. He stepped down as CEO that same year amid allegations of misleading investors and inflating metrics during the company’s 2021 fundraising. The SEC subpoenaed both Breslow and Bolt over potential securities law violations, TechCrunch reported.

By early 2025, with revenue at a $28 million, Bolt, now 31, returned as CEO with unanimous board approval. It’s been reported that he has since reduced the company’s headcount by approximately 30%, including the full HR team.

Bolt now operates with about 100 employees, according to reports.

Read more: IBM: CEOs have a new top priority (and HR is key)

‘We did get rid of our HR team’

On LinkedIn after the event, Breslow posted: “I can confirm. We did get rid of our HR team. It needed to happen. Anyone who loves creating problems versus solving problems has no role at a startup.”

He also distinguished what he shed and what he kept. In a prior LinkedIn post, he wrote that “HR is the wrong energy, format and approach. People ops empowers managers, streamlines decision making and keeps the company moving at lightning speed.”

At the Fortune summit, he confirmed Bolt has since brought on a smaller people operations team to handle required training and serve as an employee resource.

Some HR pros in the comments didn’t see the value in this announcement. “So basically, people ops is just human resources with a new name,” said one user. Another responded that “this increases an organization’s risk and turnover will escalate.” And: “Shell game. Changing the name doesn’t make the work HR does go away.”

An organizational turnaround

The move reflects a broader workforce reset, which Breslow says was necessary to survive. When he returned, he gave employees hired under prior leadership 60 days to adapt to what he described as a “wartime,” startup-style culture. The turnaround also included ending four-day workweeks and unlimited PTO policies the firm had previously offered as a “conscious leadership” strategy, according to his LinkedIn posts.

By his own account, 99% of those employees could not make the adjustment. He attributed the breakdown to what he called a culture of “entitlement” that developed during Bolt’s high-spend growth years, when employees “didn’t have to get their hands dirty.”

“We need a group of people who are very oriented around getting things done, and there is just a culture of not getting things done and complaining a lot,” Breslow said at the conference.

The post ‘HR is the wrong energy’: Bolt CEO defends eliminating the entire department appeared first on HR Executive.

Cisco announced fewer than 4,000 layoffs alongside fiscal Q3 2026 results showing $15.8 billion in revenue, up 12% year over year. The stock jumped roughly 15% to 17% on the news. “While we are reducing roles in some areas, we are making clear, strategic investments—particularly in silicon, optics, security and in our employees’ use of AI across the company,” wrote Cisco CEO Chuck Robbins in a memo to employees.

A few days later, British multinational bank Standard Chartered said it plans to cut more than 15% of its corporate function roles by 2030, about 7,800 positions, as the org expands AI and automation, while moving some workers into other roles.

Both Cisco and Standard Chartered referenced opportunities for affected workers to reposition or retrain. “We will provide support in finding new opportunities, whether internal or external, through Cisco’s placement services—a program that has seen 75 percent of participants discover their next role,” according to the memo from Robbins.

Read more: The hidden risks of AI-driven layoffs

Transparent reasons for layoffs

In many cases, companies announcing AI investments are careful to frame the technology as additive. Many leaders say that AI will create new roles, boost productivity and free workers for higher-value work. Layoffs are largely attributed to market conditions, restructuring or strategic pivots but rarely to automation directly. However, messaging from Cisco and Standard Chartered is more deliberate about the reasons for cuts.

Cisco

“The companies that will win in the AI era will be those with focus, urgency and the discipline to continuously shift investment toward the areas where demand and long-term value creation are strongest,” said Robbins. “I’m confident Cisco will be one of those winners. This means making hard decisions—about where we invest, how we’re organized, and how our cost structure reflects the opportunity in front of us.”

Standard Chartered

Reuters reported that layoffs at Standard Chartered are tied to automation and AI as some staff reskill, according to statements CEO Bill Winters during a press conference.

“It’s not cost-cutting. It’s replacing in some cases lower-value human capital with the financial capital and the investment capital we’re putting in,” Winters said, according to reports. “We are investing in the capabilities that will compound our competitive advantages and drive sustainable growth and higher quality returns over time, with clear targets in place.”

More layoffs to come?

A growing list of executives are now citing AI adoption explicitly as the driver of headcount reduction. While it hasn’t manifested yet, another financial institution, HSBC, is reportedly weighing one of its biggest workforce reductions in years. Bloomberg reports that the bank could cut around 20,000 roles, or about 10% of its total staff, over the next three to five years as it leans more heavily on AI to streamline middle- and back-office functions.

The post Cisco, Standard Chartered latest to cite AI as explicit driver of layoffs appeared first on HR Executive.

Recruiting firms have spent the last decade layering technology onto their workflows. What may have begun as a simple combination of an applicant tracking system and a CRM has evolved into a fragmented stack that includes sourcing tools, outreach platforms, contact databases, spreadsheets and a growing number of AI-powered point solutions. Each tool is introduced to solve a specific problem. Over time, those solutions accumulate into a system that is difficult to manage and even harder to evaluate.

See also: Recruiting firms say AI and automation drive revenue growth

At the recruiter level, the symptoms are obvious. Workflows span multiple systems, often with eight or more tools open at once. Data gets copied, re-entered and reconciled manually. Two systems rarely reflect the same information simultaneously. Even basic questions can require jumping between tools to answer.

For years, this fragmentation was tolerable. In strong hiring markets, searches moved quickly, and most roles were easily filled.

But in the current sluggish job environment, this dynamic has changed. Hiring cycles have slowed, roles are more competitive, and clients are more selective. Searches that once closed in 60–90 days now take months, increasing the labor required per placement. At the same time, firms are operating with larger and more expensive tech stacks than ever before. What was once a hidden inefficiency is now directly affecting how work translates into revenue.

And the explosion of AI tools has ironically made the problem worse. Built on LLMs like ChatGPT or Gemini, these tools promise automated sourcing, outreach, email and scheduling across platforms with just a single prompt.

AI can often be the problem for companies with job searches

The issue is that these tools rarely work as intended. Studies of large language models have found that the same query can return different answers across repeated runs, often in different orders. That inconsistency makes it difficult to rely on these tools for structured, repeatable workflows, especially in environments where capturing and tracking data accurately is critical. Not only are these tools inconsistent, but they’re also producing structurally different outputs—a nightmare for professionals trying to quantify and capture critical business data.

It’s a recipe for inefficiency for recruiters, who waste not only money on tech tools they don’t need, but countless man-hours switching back and forth between systems, trying to figure out where data has been properly updated and which system is most accurate. Some firms report spending five to 10 hours per week per recruiter simply duplicating effort across systems.

This tech bloat (AI-enabled or not) is compounded by data quality concerns, as recruiting databases degrade quickly, with roughly 70% of company and candidate data becoming outdated each year. When that data is spread across multiple systems, it becomes inconsistent and unreliable, reducing the effectiveness of outreach and forcing recruiters to rebuild information that should already exist.

For recruiting firms, the impact shows up in performance metrics. Fragmented workflows slow sourcing and outreach, extend time-to-fill, and reduce the number of searches each recruiter can manage. Firms operating with more than five recruiting tools report lower placement rates meaningfully, while those that simplify their stacks recover lost productivity and increase billable time within months. At a structural level, high-performing firms generate significantly more revenue per recruiter than their peers, reflecting the time recruiters actually spend on placement-driving activities.

Tech bloat hurts overall success

Tech bloat is doing more than hampering placement efforts; it’s hampering firms’ overall success.

This is a dangerous dynamic—firms may appear very busy (full pipelines, active searches, constant activity), but genuine productivity is declining because more work is performed without matching financial results. Costs accumulate quietly in time and process, not as obvious expenses. Leaders end up treating symptoms rather than addressing the root cause: a lack of insight into how work translates into profit.

Continuing to stack tech tools on top of one another will only drive further confusion; firms need to respond by restoring visibility into how their businesses actually operate and measuring what actually matters. That starts with reducing unnecessary tool overlap and consolidating systems where possible. It requires standardizing workflows so that recruiters follow consistent processes rather than individual preferences. Most importantly, it requires capturing data in a single, reliable system of record that allows leaders to trace how work performed today translates into outcomes tomorrow.

Leaders should be able to answer basic operational questions with precision: how recruiter time is allocated, where delays occur, and how each stage of a search contributes to revenue and margin. Without that visibility, performance cannot be managed effectively, regardless of how many tools are added to the stack—and a fragmented stack makes the challenge even harder.

Now that hiring has slowed, that lack of visibility is becoming harder to ignore. The firms that adapt will clearly connect activity to economics—not just measuring work, but linking it to revenue. Those who cannot will absorb unseen costs until the gap between effort and outcome is unsustainable.

The post Why tech bloat is no longer a hidden inefficiency appeared first on HR Executive.

Many employers are performing or announcing layoffs this year; however, there are lessons for HR teams embedded in the moves the social media giant is making during the layoff process.

Employees don’t trust silence

Rumors of mass layoffs at Meta began circulating in early 2026. For more than a month after Reuters first reported the cuts, Meta leadership stayed largely quiet. However, this approach has pitfalls. Employees in 2026 do not wait for official memos; they read industry news, talk to peers at other companies and they synthesize signals on their own. Saying nothing in that environment allows the rumor mill to fill the vacuum.

HR Executive has covered how other big tech firms handle layoff rumors. For example, when Microsoft faced unfounded layoff rumors in January, its communications lead quickly took the unusual step of calling the speculation “100% wrong.”

Patrick McCue, senior vice president of Americas at Right Management, told HR Executive that advance indicators of layoffs without specifics create their own damage. “That tension alone drives anxiety up,” he said. Employees in a holding pattern are less productive, he noted, and the rumor mill runs harder the longer clarity is withheld.

Severance options matter

Meta’s U.S. severance formula is 16 weeks of base pay plus two additional weeks per year of service. This positions the company above some peers, including Oracle’s recently reported package of four weeks’ base pay plus one week per year of service, capped at 26 weeks.

However, Meta’s arrangement falls below Jack Dorsey’s severance package for Block’s March 2026 layoffs, which offers affected employees 20 weeks of salary plus one additional week per year of tenure. It also includes six months of healthcare, vested equity through the end of May, retention of corporate devices and a $5,000 transition stipend.

Read more: As companies use AI to justify layoffs, Josh Bersin says HR is solving the wrong problem

Internal transfers and team changes

Meta’s Chief People Officer Janelle Gale described moving employees to new AI-focused initiatives, according to Reuters. “As org leaders worked on the changes, many of them incorporated AI native design principles ⁠into their new org structures,” wrote Gale, as reported by Reuters. “We’re now at the stage where many orgs can operate with a flatter structure with smaller teams of ​pods/cohorts that can move faster and with more ownership.”

Additionally, Meta’s restructuring reportedly eliminates some manager roles. This is a pattern HR Executive has tracked in other tech-industry layoff actions. Amazon, Block and others have framed cuts resulting in flatter teams enabled by AI.

The post Meta’s restructuring strategy offers lessons for HR appeared first on HR Executive.

AI agents are no different.

The conversation has already moved from experimentation to integration and companies are digging into where agents can support customer service, compliance, HR operations, marketing, finance and internal knowledge work. The ambition is understandable, as AI agents can carry out tasks, coordinate workflows and reduce the amount of repetitive work sitting on human teams.

But there is a deeper question that many organizations are not asking early enough: Who inside the business is actually capable of supervising this new layer of work?

That question belongs partly to technology leaders, but it also very clearly belongs to CHROs.

See also: Why every AI agent needs a human manager and clear job description

McKinsey has described the rise of the agentic organization as a new operating model where humans work alongside virtual and physical AI agents to create value. Its analysis identifies workforce, people and culture as one of the core pillars of this shift. That matters because AI agents will not only change tools, they will change responsibility, judgment, accountability and the shape of human work.

If HR treats this as another software rollout, it will miss the point.

What is human capability and how does it help AI agents?

The more useful starting point is human capability. Before companies scale AI agents, they need a clear map of the people who understand the work deeply enough to direct it, challenge it and carry accountability for the result.

A human capability map is different from a skills inventory. A skills inventory shows what people say they can do, which courses they have completed or which roles they have held. A capability map goes further. It shows where judgment sits,  who carries institutional knowledge, who can connect work across functions and who can supervise digital output without losing sight of risk, quality or context.

Most organizations already have job descriptions, competency models, performance reviews and succession plans. These systems are useful, but they often describe the structure of work better than the behavior of people. They show who occupies a role, but they do not always show how someone thinks when the answer is unclear, how they respond to weak information or how they make decisions when speed and responsibility collide.

AI will expose that gap.

When routine output becomes easier to generate, the value of work changes. A first draft, a summary, a report or a recommendation may take minutes instead of hours. That does not mean the work has been done well; it only means the first version arrived faster.

The real value moves to the person who can define the task correctly, review the result, notice what is missing and decide whether the output is strong enough to act on. This is not just AI literacy, it’s supervision.

That distinction matters for HR.

Many employees will need basic AI fluency. They will need to understand the tools, the risks and the acceptable boundaries of use. But the people who shape the next organization will need a higher order capability. They will need to orchestrate work across humans and AI systems.

This is where T-shaped and M-shaped talent becomes more important. T-shaped employees have deep expertise in one area and enough understanding of adjacent areas to work across boundaries. M-shaped employees have several areas of deeper expertise and can connect different domains with greater independence.

These people are valuable because AI-enabled work rarely stays inside one clean function. A customer issue may touch service, legal, product and brand. A finance decision may involve data, compliance, operations and people. A hiring process may involve automation, candidate experience, assessment quality and bias risk. Agents may support each step, but humans still need to understand the whole system.

Deloitte’s 2026 Global Human Capital Trends report makes a similar point. It argues that advantage is shifting from allocating talent in static structures to orchestrating people, skills, data and technology in real time. For HR leaders, this is a useful warning. The old workforce model was built around roles. The next one will be built around capability that can move.

Without that map, AI transformation becomes fragile.

A company may automate tasks without understanding the judgment behind them. It may remove roles that look administrative while losing people who quietly held the context that made the process work. It may reward employees for using AI often, while failing to see whether they are using it responsibly. It may create faster workflows with weaker ownership.

That is the risk CHROs need to prevent.

Agentic AI projects could be in trouble soon

Gartner has predicted that more than 40% of agentic AI projects will be cancelled by the end of 2027 because of escalating costs, unclear business value or inadequate risk controls. This should not be read only as a technology warning; it is also an organizational warning. AI agents need ownership, governance and human oversight. They need people who can define what good looks like and intervene when the system moves in the wrong direction.

The CHRO should be involved before the organization decides where agents will sit. HR needs to help answer several questions.

Where must human judgment remain close to the work?

Who understands the process beyond the task list?

Who has the institutional knowledge that should be protected before a workflow is redesigned?

Who can review AI output with enough context to challenge it?

Who has the cross-functional thinking needed to coordinate people, systems and agents?

These questions are more useful than asking only who needs AI training. Training matters, but training without a talent architecture becomes activity. It may produce course completion and confidence, but not necessarily better judgment.

The organizations that handle this well will not treat human capability as an afterthought. They will identify their future AI orchestrators early. They will build development paths for people who can supervise digital work. They will make institutional knowledge more visible before it disappears into informal networks. They will redesign performance systems around responsibility, not just speed.

This also changes how employees experience AI. If AI is introduced as a replacement story, people will naturally protect themselves. They may resist, hide knowledge or treat every new tool as a threat. If AI is introduced as a way to scale human expertise, the conversation becomes more constructive.

That does not mean pretending every role will stay the same. Many tasks will change. Some will disappear. New ones will emerge. The point is to avoid reducing people to the tasks they currently perform.

A person’s value inside an organization is often larger than their job description. It includes judgment, memory, relationships, standards and understanding of how work actually gets done. AI makes it more important to see those qualities clearly.

For CHROs, this is the strategic opportunity. AI agents may change how work moves through the business, but HR can help decide whether that change strengthens or weakens the organization.

The companies that scale AI responsibly will start with a human map. They will know which capabilities must be protected, which people can carry more autonomy and which parts of the organization need deeper development before agents are added.

AI will not remove the need for human capability. It will make weak talent architecture harder to hide.

The post CHROs need a human capability map before scaling AI agents appeared first on HR Executive.

Threat assessment relies on a model called the “pathway to violence,” which traces how a person can move from internal distress (a grievance) to destructive action.  What it makes clear is that nobody crosses from employee to insider threat in a day. There are observable steps along the way, and HR sits closer to them than any other function in the organization.

See also: 7 steps HR needs to take today to beef up cybersecurity

The warning signs when it comes to layoffs and security

A finance manager mentions bankruptcy during a benefits call. A high-performing team lead stops engaging with colleagues after a divorce. An employee fixates on perceived injustices her manager cannot redirect. HR professionals occupy the room for all these conversations and more, but they almost never make it to security.

The risk factors for insider threats mirror the leading predictors of suicide: financial strain, loss of identity, mental health difficulties, isolation and a perceived betrayal. That overlap means workplace safety and employee wellness are inextricably linked. The same instincts that make a strong HR practitioner—earning trust, reading emotional cues, navigating tense dialogue—make early threat identification possible.

Why HR and security operate in silos

HR and security report to different leaders, operate under different incentives and share little professional vocabulary. Insider threats take root in the space between them.

When HR treats threat assessment as someone else’s job, no one intervenes early enough to change the outcome. By the time security receives the call, the window for a supportive, low-stakes conversation with a struggling employee has closed.

HR need not become a security function. It simply needs to share what it already observes with the people trained to interpret those observations through a security (or safety) lens. This collaboration must happen before a crisis forces them.

What happens inside the separation room

The gap between HR and security grows most dangerous during involuntary separations. Many organizations treat termination meetings as encounters to finish quickly, assuming speed limits exposure. Speed, however, only compounds risk.

Think about what you have just compressed into a few minutes. You have taken a person who may already resent the organization and stripped away income, health insurance, professional identity, daily routine and social belonging in a single conversation. For someone already navigating a personal crisis, that meeting can land as confirmation of something they have feared for months.

Many managers walking into separation conversations have never fired anyone. They need coaching on specific language and protocol before they sit across from a departing employee.

In one case I reference often, a security representative swept a conference room before a scheduled separation meeting and removed a large knife left over from an employee’s birthday celebration earlier that day. HR had not noticed it. That is not incompetence, but a gap in perspective that only advance coordination between the two departments can close.

Empathy backed by concrete action, resumé help, extended health coverage and outplacement support all give the person leaving reason to see the experience as painful but survivable. A meeting that feels rushed or adversarial adds another grievance to a pile that may already be dangerously tall.

After the door closes

Every departed employee becomes an alumnus of the organization. How they remember that final conversation greatly influences how they think of the organization, whether they move on quietly, speak bitterly about the organization or, in rare and extreme cases, become a genuine safety concern. Remaining staff draw their own conclusions, as well. The way a company treats people on their worst professional day sends a durable message to everyone who stays.

HR and security should debrief together after high-risk separations and coordinate on monitoring concerning post-departure communications. The weeks immediately following a termination carry the highest vulnerability. Remaining team members need honest, measured communication so that rumors do not fill the silence a sudden departure leaves behind.

The year ahead

Layoffs with no doubt continue through 2026. HR teams across the country face more involuntary separations than many practitioners have managed in an entire career. Every one of those conversations will be difficult. Whether they become dangerous depends on whether HR and security prepare for them together, with shared awareness of the risks, a rehearsed plan for the meeting and a genuine commitment to the dignity of the person across the table.

In many organizations, HR holds more influence with the C-suite than security does. If HR leaders claim this responsibility as their own, they can drive the cross-departmental coordination and funding that have historically lost out to competing priorities. The time to build that partnership is now, before the next round of notices goes out.

The post When layoffs become a safety risk, HR is the first line of defense appeared first on HR Executive.

The complaint, filed May 11 in Santa Clara Superior Court, alleges Meta tracks about 15 billion fraudulent ads and earns roughly $7 billion a year in internal “violating revenue,” according to reporting based on the filing and Reuters investigations.

Reuters reported that internal Meta documents estimated scam and banned-goods ads could account for about 10% of the company’s 2024 revenue. The complaint also cites internal materials suggesting Meta’s platforms played a role in a large share of consumer scams in the U.S. “Meta has a serious problem with scam ads,” according to the filing.

According to Reuters, Meta’s internal systems reportedly remove advertisers when it’s “automated systems predict the marketers are at least 95% certain to be committing fraud.” Suspected scammers below that threshold may instead be charged more to keep running ads.

“Meanwhile, Meta has declined to implement universal advertiser verification,” according to the filing, “a proven, cost-effective process that would require Meta to verify the identities of all advertisers on its platforms.”

The complaint, which lays out specific stories of how victims were damaged, alleges that Meta’s AI tools help scammers test deceptive ad variations. It also claims that the social media giant’s tools target users who have engaged with scam content and push ads for fraudulent financial products, cryptocurrency schemes, fake cures, ineffective supplements and celebrity impersonation scams. The county suit comes amid other consumer litigation targeting Meta over scam ads.

Read more: Amid layoff surge, why new Meta suit could raise red flags

How do Meta lawsuit accusations impact HR teams?

Many organizations use Meta’s advertising platforms for recruitment marketing and employer brand campaigns. If Meta’s ad review systems are as compromised as the complaint alleges, it could mean HR and talent acquisition teams are participating on a platform where scam content competes alongside their legitimate messaging.

This could erode trust with the candidates and employees that hiring teams are trying to reach. The filing also states that “in 2023, Meta laid off the entire team investigating scam ads that were hurting legitimate brands.” The filing also alleges that even after Meta had laid off one anti-scam team in 2023, disbanded another in 2024 and refused to implement universal advertiser verification, the company posted in December 2025 that “we’re expanding our advertiser verification efforts.”

Santa Clara County Counsel Tony LoPresti is seeking civil penalties, restitution for California residents who lost money to scams allegedly facilitated by Meta’s systems and court-ordered changes to the company’s business practices. Local reporting describes it as the first of its kind, brought by a local civil prosecutor rather than a state attorney general.

Meta denied the allegations, saying they “misrepresent the reality of our work,” and said it would fight the lawsuit, according to reporting by CBS News. The company also said it removed more than 159 million scam ads in 2025.

Meta also said it has been taking legal action against scam advertisers and described a broader effort to disrupt fraudulent activity across its platforms, including Facebook and Instagram. In its February 2026 newsroom post, the company said it works to remove scam ads, deploy protective tools and coordinate with law enforcement.

The post Meta sued over scam ads: Why HR should pay attention appeared first on HR Executive.

However, there is another layer that makes this finding harder to dismiss. More than one in four leaders say it can take weeks to access connected talent insights. By the time an HR leader can assemble the numbers needed to flag a problem, the drain is often already built into the quarter.

Talent data can point to an underutilized workforce

The survey, which drew responses from 1,600 C-suite and senior HR leaders across 10 countries, points to workforce underutilization as a primary driver of the financial impact. Thirty-one percent of leaders report that more than a quarter of their workforce is underutilized, identifying employees who are not deployed in ways that match their full capability.

However, underutilization rarely surfaces as a line item. It shows up in productivity gaps, inconsistent performance and high-potential employees who leave for roles that use more of what they can do.

“When workers’ potential is missed, the business loses out,” said Matias Spinetta, senior vice president of North America Commercial at Korn Ferry, in the report. “They end up buying what they might not need or missing innovations that could lead to growth. And their staff turnover rises, too, as those people get bored and look to spread their wings elsewhere.”

Often, data to catch those patterns exists somewhere inside the organization, but it doesn’t connect in a way that lets leaders act on it.

‘Too late to do something about it’

Across most organizations, the talent information needed to make workforce decisions sits across multiple platforms that aren’t designed to work together. The Korn Ferry survey found that 84% of leaders operate between three and 10 different talent platforms, yet just 5% have fully connected systems. Sixty-eight percent operate with only partial or minimal data integration.

The result is a workflow that looks less like analysis and more like an assembly line. Before an HR leader can surface a workforce insight, they often have to pull data from multiple systems and reconcile it manually. For more than a quarter of leaders, according to the report, that process takes weeks. Unfortunately, workforce decisions tied to reorganizations, market shifts or leadership changes don’t pause while HR waits on reports. When insights arrive late, leaders make calls without them.

“As an executive, if you don’t have a clear picture of your own workforce, that should keep you up at night,” said Jan Machtelinckx, growth leader for digital assessment, succession and development at Korn Ferry EMEA, in the report. “It might be too late to do something about it when decisions need to be made.”

The credibility cost when talent data can’t be trusted

There’s a secondary consequence that HR leaders may feel more directly. When data is slow or inconsistent, the function that produces it loses standing. The survey found that 55% of leaders say they rely less on HR for decisions when they don’t trust the talent data. Fragmented insights erode confidence in HR’s analysis, and eroded confidence means HR may be consulted less when high-stakes decisions are being made.

“The business doesn’t believe HR because they don’t believe the data can be trusted,” said Roger Philby, global lead of the People Strategy and Performance Practice at Korn Ferry U.K., as part of the report. “And that’s because HR isn’t always great at being data practitioners and communicators.”

The research does offer a point of contrast. Among organizations that have integrated their talent data, confidence in workforce decision-making rises from 4% to 55%. Those organizations also report gains in productivity, faster hiring and stronger employee engagement.

The post Disconnected talent data: a 3% cost to payroll appeared first on HR Executive.

A new study from INTOO shows a disconnect when it comes to workplace AI adoption, with workers rapidly embracing AI but often doing so without clear guidance, transparency or support. In fact, the survey, conducted by The Harris Poll, shows that 52% of employees consider themselves experts at using AI for work-related tasks, while 63% think their AI knowledge for work makes them more valuable employees.

Interestingly, 20% of employees say they are unclear about what is acceptable when using AI for work-related tasks and 25% say they would not feel comfortable telling their colleagues they’ve used AI.

“The obvious risks that come to mind for most are data security and privacy,” says Mira Greenland, Chief Revenue Officer at INTOO. “But employers should also be concerned about the quality of work output when AI use isn’t governed. Not because the information may be incorrect, but because when employees outsource their work to AI without oversight or guardrails, deep analysis and collaboration decrease, and imposter syndrome increases.

“Employees aren’t necessarily taking the time to immerse themselves in an organization’s problems to find creative solutions, since they can instead assign the challenge to ChatGPT or Claude without spending time to assess the value and relevance of the output,” Greenland adds. “And in an organization where the rules aren’t clear, employees who secretly or discreetly use AI may develop a fear that they will not be credited for their work if they are ‘found out’.”

See also: Employees still fear AI. What CHROs are doing about it

Workers also fear asking for help with AI, survey says

Not only are there fears of not being credited, 42% of workers also say it would be embarrassing to ask co-workers for help with new technology, including AI, which could limit collaboration and shared skill-building, according to the study.

But Greenland says there are ways to mitigate these fears. “One of the most effective ways to overcome that fear is to reframe asking questions as part of the learning process rather than a sign of weakness. The most successful employees aren’t the ones who never ask questions—they’re the ones who ask before small problems become bigger ones. It can also help to shift their mindset from ‘asking for help’ to ‘seeking perspective,’ validating an approach, or accelerating learning,” she adds.

INTOO’s report emphasizes that organizations must create environments where employees can use tools like AI openly and collaboratively. These goals can be achieved by establishing clear AI guidelines to reduce ambiguity, normalizing transparency by encouraging leaders to model AI usage openly, and fostering psychological safety so employees feel comfortable asking questions and sharing work.

The post 52% of employees call themselves AI experts—but are they? appeared first on HR Executive.

AI is moving from policy talk to legal obligation

The clearest signal for HR leaders is that AI governance is no longer theoretical. Ireland published a draft AI Regulation Bill implementing the EU AI Act, and it draws a direct line to employers. Under the bill, companies are classified as “deployers” of AI systems even when they purchase off-the-shelf HR technology. That means employers (not just vendors) are directly responsible for risk management, transparency and human oversight requirements under the EU AI Act.

Meanwhile, Germany is navigating similar territory through the European Commission’s Digital Omnibus proposal, which attorneys say will increase transparency and explainability obligations for AI-driven employment decisions. Additionally, Australia’s Fair Work Commission is moving toward requiring disclosure when AI generates legal filings, with proposed guidance that would require human review and sign-off on AI-assisted submissions. In addition, Ireland published the General Scheme of the Regulation of Artificial Intelligence Bill 2026, implementing the EU AI Act.

In the U.S., the Trump administration released a non-binding framework in March recommending Congress lean on existing law rather than enact AI-specific rules, and calling for federal preemption of state AI laws. Attorneys advise that near-term federal legislation aligned with that framework appears unlikely, meaning U.S. employers should continue monitoring state and local AI laws and apply baseline principles of transparency, training and ongoing auditing of AI-driven outcomes.

Pay transparency deadlines are real, even where laws aren’t ready

The EU Pay Transparency Directive carries a June 7, 2026, transposition deadline, and many member states face delays in meeting the deadline, as noted in Littler’s resources.
The attorneys suggest that Belgium is unlikely to meet the deadline, with no private sector drafts despite a looming close date. Ireland has indicated it is planning a phased approach. Meanwhile, Denmark’s draft targets a Jan. 1, 2027, due date and the Czech Republic anticipates reforms soon, but lacks firm pre-deadline action. France also has an initial draft, but no confirmed timeline.

Littler attorneys warn against waiting on compliance, due to existing equal pay obligations, court alignments and retroactive risks. Littler’s overview stresses preparation now amid “rushing” or “delays in roll-out.”

Equal pay and anti-discrimination obligations are already in effect, and national courts may begin interpreting existing law in line with the directive before formal adoption occurs. Retroactive reporting obligations are possible, but the reputational exposure from being caught unprepared is out there.

Denmark’s draft bill, published in late February, requires employers to disclose starting salaries to job applicants, ban inquiries into prior pay history and give employees the right to request pay data disaggregated by gender for comparable roles.

Meanwhile, France’s draft goes further, requiring companies with 50 or more employees to publish pay gap indicators and placing the burden of proof on employers for certain transparency violations.

Read more: New DOL rule targets worker misclassification

Who counts as a worker (and an employer) is being redefined

Worker classification is under pressure in multiple markets simultaneously.

Malaysia’s Gig Workers Act took effect March 31, 2026, giving platform (gig) workers statutory protections, including notice of pay terms and protection from termination without just cause.

South Korea’s “Yellow Envelope Act” amendments, effective March 10, expand the definition of “employer” to include any entity exercising substantial control over working conditions, regardless of whether a direct employment contract exists.
Poland expanded its labor inspector’s power to reclassify civil law contracts (aka freelance or service contracts) as official employment contracts, with employers carrying the burden of appeal.

Also, the Netherlands is developing a new framework for self-employed classification that preserves a legal presumption of employment for workers earning 38 euros or less per hour.

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