Oracle began a new round of layoffs this week, sending early-morning termination emails to staff for the second time in six months.

The latest wave began Monday with affected staff being told, “After careful consideration of Oracle’s current business needs, we have made the decision to eliminate your role as part of a broader organizational change,” according to BusinessInsider. Termination was immediate.

That’s the same wording as in the previous wave of layoffs, which took place on March 31 and affected workers in the US, India, Canada, Mexico and Uruguay. In the 12 months to May 31, Oracle cut its global workforce from about 162,000 to about 141,000, a decline of roughly 13%.

Oracle has made no public statement confirming the latest round of job cuts, but in a regulatory filing days earlier the company said it had set aside a further $700 million for restructuring charges, bringing the total charges this year to roughly $2.8 billion.

What the new termination emails say

Staff receiving the latest termination emails were told termination and compensation details would follow by DocuSign, Business Insider wrote. An internal document reviewed by the publication said severance terms varied by role and region, and some teams facing double-digit percentage cuts.

Affected employees took to social media to vent.

Eric Brunson, a senior principal offensive security researcher at Oracle, described in a LinkedIn post how he had lost access to corporate communication tools before receiving any formal notice. “I woke up to not being able to log back into Slack,” he wrote. “No new emails or notification in email and I’m locked out of there. I was able to get ahold of my manager on LinkedIn and she confirmed.” Brunson said the timing fell two days before a scheduled RSU vesting date, adding, “Probably part of the plan.”

The filing that backs up the layoff accounts

While Oracle is not talking about the layoffs, its 10-Q quarterly report states that management approved and supplemented restructuring plans “to implement certain strategic measures and further improve operational efficiencies, including through the adoption and integration of artificial intelligence technologies across certain functions.” It adds that “subsequent to August 31, 2026, our management supplemented the 2026 Restructuring Plan by approximately $700 million to reflect additional actions that we expect to take.”

Oracle has already spent $1.97 billion of the $2.1 billion restructuring charges it originally budgeted, it reported.

Sanchit Vir Gogia, chief analyst at Greyhound Research, said the filing should be read carefully rather than as confirmation of a headcount. “The supplement is an estimate, not a bill,” he said, noting it raises the program’s estimated cost by about a third without committing Oracle to a timetable.

Gogia said the more significant shift is in the filing’s language rather than the dollar figure. Oracle’s August 2025 and February 2026 filings had described the plan as tied to “acquisitions and certain other operational activities.”

AI was named as a driver of restructuring for the first time in the Sept. 11 filing.

Why the headcount stays unconfirmed

Gogia said no verified figure exists yet for how many employees the September round affected.

He noted that 30,000 was a January forecast of the total 2026 program. Twenty-one thousand is the confirmed net decline in Oracle’s global workforce across the full fiscal year. A reported 3,000 job cuts in India on Sept. 1 remains unconfirmed by Oracle.

The $700 million restructuring supplement “cannot be divided into people,” Gogia said, since it covers termination benefits, contract termination costs and other exit costs across a program spanning multiple countries. “There is no solid headcount for the September round,” he said.

A pattern that began in March

Oracle’s first 2026 layoff wave began March 31, when the Revenue and Health Sciences unit, the SaaS and Virtual Operations Services group, and NetSuite’s India Development Centre saw some of the deepest reductions.

Figures published by Oracle for its fiscal year ending May 31, 2026, show research and development headcount fell from 50,000 to 43,000 employees during the year, sales and marketing fell from 31,000 to 25,000, and services fell from 37,000 to 34,000, according to Gogia’s analysis of the company’s own reporting.

International staff, at 92,000, saw a larger reduction than the 49,000-strong U.S. workforce, he said.

Oracle did not respond to a request for comment.

This article first appeared on CIO.

Among a range of factors leading to a wave of tech sector layoffs in 2026 is the rapid rise of artificial intelligence and automation. Companies are reconfiguring their workforces to leverage AI for increased efficiency and reduced operating costs. This realignment and reduction is implemented even by companies reporting strong financial performance.

But it’s not just AI leading to workforce cuts. Complementing this technological shift are ongoing economic uncertainty, inflation, and higher interest rates, compounded by a chip shortage and rising energy costs. This mix is driving companies to cut costs and streamline operations for increased efficiency.

According to data compiled by Layoffs.fyi, an online tracker that keep tabs on job losses in the technology sector, 123,941 tech employees were laid off at 269 companies in 2025. The site also reports that 71,981 government employees were laid off by DOGE alone, with 182,528 total federal workers laid off.

Here is a list — to be updated regularly — of some of the most prominent technology layoffs the industry has experienced recently.

Notable tech layoffs in 2026

• Oracle (again)
• Monday.com
• Microsoft
• Meta
• Cisco
• Cloudflare
• Oracle
• Atlassian
• Salesforce
• Amazon
• Ericsson

Sept. 15, 2026: Oracle forecasts 33% increase in restructuring costs as new round of layoffs hits

Oracle began a new round of layoffs this week, sending early-morning termination emails to staff for the second time in six months. Oracle has made no public statement confirming the latest round of job cuts, but in a regulatory filing days earlier the company said it had set aside a further $700 million for restructuring charges, bringing the total charges this year to roughly $2.8 billion.

July 22, 2026: Monday.com cuts 20% of its workforce to restructure for the AI era

The company says the decision to cut 620 jobs isn’t about margins, but about creating a flatter organization built around AI agents, autonomous teams, and deeper customer engagement.

July 6, 2026: Microsoft cuts 4,800 jobs, primarily in sales and Xbox teams

As the company trims thousands of jobs, it’s also investing in embedded engineering teams and AI infrastructure. The layoffs come several weeks after the company offered 8,750 US employees voluntary retirement buyouts.

June 5, 2026: Tech industry cut 38,242 jobs in May, worst since 2024

AI was blamed for 40% of the job cuts in May, up from 7% in January, according to research by employment placement company Challenger, Gray & Christmas.

May 20, 2026: Meta cuts 8,000 jobs, around 10% of workforce

The cuts are expected to expected to hit Meta’s engineering and product teams the hardest, arriving as Meta pivots toward AI to boost efficiency across its organization, according to Yahoo Tech.

May 13, 2026: Cisco to cut nearly 4,000 jobs despite strong growth in AI, enterprise networking

Despite reporting positive financial news — including record third-quarter revenue of $15.8 billion, a 12% year-over-year increase — Cisco said it will eliminate almost 4,000 jobs.

May 7, 2026: Cloudflare to cut 1,100 jobs in AI-focused restructuring

About 20% of Cloudflare’s global workforce will be culled as the company pivots for the agentic AI era, Reuters reported.

April 1, 2026: Oracle to cut up to 30,000 jobs globally, putting enterprise support and roadmaps at risk

Oracle began laying off employees on March 31 in what could be the largest workforce reduction in the company’s history. Employees received termination emails at 6 a.m. local time with immediate system lockouts and no prior warning. (Note: in June, CNBC put the final layoff tally at 21,000.)

March 12, 2026: Atlassian cuts 1,600 jobs to fund AI and enterprise expansion

Atlassian will reduce its global workforce by approximately 10%, eliminating around 1,600 roles, as the collaboration software maker redirects capital toward artificial intelligence development and enterprise sales.

March 11, 2026: Tech layoffs surpass 45,000 in early 2026

A recent analysis by RationalFX found 45,363 job cuts globally so far this year—with roughly 68% or more than 30,000 occurring in the U.S. — highlighting ongoing workforce cuts even as many tech companies report strong revenue growth.

Feb. 10, 2026: Salesforce lays off staffers as executive leadership churn continues

Salesforce has reduced close to 1,000 roles earlier this month across teams, including marketing, product management, data analytics, and its Agentforce AI unit, Business Insider reported, quoting employees familiar with the matter.

Jan. 23, 2026: Amazon layoffs expected to disproportionately hit AWS and tech talent

As the market slows down, AWS and other Amazon units are preparing for another round of layoffs, which is expected to overwhelmingly impact tech talent. An email from HR leader Beth Galetti on Jan. 28 confirmed 16,000 job cuts.

Jan. 15, 2026: Ericsson plans to shed 1,600 jobs in Sweden

 Ericsson lans to cut some 1,600 jobs in Sweden, the telecommunications equipment maker said doubling down on recent cost-saving measures that have helped it weather a prolonged downturn in telecoms spending, Reuters reports.

Jan. 13, 2026: Meta plans to cut around 10% of employees in Reality Labs business

Meta plans to cut around 10% of the employees in its Reality Labs division who work on products including the metaverse, according to three people with knowledge of the discussions, according to The New York Times.

Layoffs in 2025

• Cisco
• Oracle
• Windsurf
• Intel
• Microsoft
• Crowdstrike
• HPE
• Autodesk
• HPE
• CISA
• Workday
• Salesforce
• Meta

Global tech-sector layoffs surpass 244,000 in 2025

Economic uncertainty, elevated interest rates, and AI adoption have driven workforce reductions across tech companies worldwide, according to a RationalFX report.

October 28, 2025: Amazon to cut 14,000 jobs across company

Amazon will reduce its overall workforce by 14,000, cutting layers of management across the company and hiring in some areas to support its “biggest bets”.

August 18, 2025: Cisco and Oracle to cut hundreds of Bay Area jobs

Tech companies Cisco and Oracle are cutting hundreds of jobs across the Bay Area. Cisco will eliminate 221 positions at its Milpitas and San Francisco offices, effective Oct. 13. Oracle is reducing 101 positions in Santa Clara on the same date 

August 5, 2025: 3 weeks after acquiring Windsurf, Cognition offers staff the exit door

Cognition, the AI coding startup that acquired rival company Windsurf three weeks ago, laid off 30 employees last week and is offering buyouts to the roughly 200 remaining employees on the team, reports The Information.

July 25, 2025, Intel to lay off 22% of workforce, CEO Tan signals ‘no more blank checks’

Intel will reduce its workforce to 75,000 employees by the end of 2025 as new CEO Lip-Bu Tan implements sweeping changes designed to transform the struggling chipmaker

July 8, 2025, Intel layoffs begin: Chipmaker is cutting many thousands of jobs

Intel has begun laying off employees across the company. CEO Lip-Bu Tan told workers back in April to expect major layoffs at Intel in the coming months as the chipmaker slashes costs and overhauls its organization after years of technical setbacks and falling sales.

July 2, 2025: Microsoft will cut 9,000 workers

Microsoft will lay off about 9,000 employees, a source familiar with the workforce cut told CNBC.  The cuts will reportedly affect less than 4% of Microsoft’s global workforce and will impact different teams, geographies and levels of experience. This is the latest in a string of cuts the tech giant has made this year.

June 17, 2025: Intel looks to factory layoffs to return to profitability

Intel will lay off up to 20% of its manufacturing sector employees starting in July, according to media reports, as the company looks for options as it seeks a return to profitability. The cuts reportedly will be made around the world, but some of the layoffs will be closer to home, according to a report in The Oregonian citing an internal company memo from Intel manufacturing Vice President Naga Chandrasekaran.

May 7, 2025: CrowdStrike to lay off 5% of staff

CrowdStrike announced a plan to cut about 500 roles, roughly 5% of its workforce, to streamline operations and reduce costs. The cybersecurity company will incur about $36 million to $53 million in charges related to the layoffs

March 6, 2025: HPE cuts 2,500 jobs, remains committed to Juniper buy

CEO Antonio Neri told Wall Street analysts that HPE would begin implementing a cost-cutting program involving layoffs of about 2,500 employees over the next 18 months. HPE employs about 61,000 people worldwide.

Feb. 27, 2025: Autodesk to lay off 9% of workforce

Software maker Autodesk is laying off 1,350 staff. With the rise of subscription and multi-year contracts billed annually, and self-service enablement, it finds it needs fewer sales staff, CEO Andrew Anagnost said in a message to employees. And with its cloud, platform, and AI products proving most profitable, it’s concentrating its staff and investments there.

Feb. 27, 2025: HP to lay off 2,000 more

As part of an ongoing restructuring, HP plans to lay off up to another 2,000 workers. In recent weeks, the company has tried — unsuccessfully — to do away with telephone support staff by forcing callers to wait for at least 15 minutes if they refuse to use self-service support resources online. The company swiftly backtracked, but wider job cuts are still on.

Feb. 21, 2025: CISA lays off 130

Government employees get laid off too: In this case, 130 workers at the US Cybersecurity and Infrastructure Security Agency are being shown the door as a result of a DOGE decision. Cybersecurity experts are concerned that the cuts will harm the international collaborations that CISA has fostered, quite apart from their concerns about the security of the DOGE layoff process itself.

Feb. 5, 2025: Workday lays off 1,750

As it moves to invest more in AI and international growth, Workday is laying off 8.5% of its workforce and disposing of unused office space. Some analysts fear the cutbacks will affect the company’s customer service — unless AI can pick up the slack.

Feb. 4, 2025: Salesforce lays off over 1,000

At the same time as it’s hiring sales staff for its new artificial intelligence products, Salesforce is laying off over 1,000 workers across the company, according to Bloomberg. As of June, 2024, the company had over 72,000 employees, according to its website. Salesforce did not comment on the report. In 2024 the company reportedly laid off around 1,000 staff too, in two waves: January and July.

Jan. 14, 2025: Meta will lay off 5% of workforce

Mark Zuckerberg told Meta employees he intended to “move out the low performers faster” in an internal memo reported by Bloomberg. The memo announced that the company will lay off 5% of its staff, or around 3,600 staff, beginning Feb. 10. The company had already reduced its headcount by 5% in 2024 through natural attrition, the memo said. Among those leaving the company will be staff previously responsible for fact checking of posts on its social media platforms in the US, as the company begins relying on its users to police content.

Tech layoffs in 2024

• Equinix
• AMD
• Freshworks
• Cisco
• General Motors
• Intel
• OpenText
• Microsoft
• AWS
• Dell

Nov. 26, 2024: Equinix to cut 3% of staff

Despite intense demand for its data center capacity, Equinix is planning to lay off 3% of its workforce, or around 400 employees. The announcement followed the appointment of Adaire Fox-Martin to replace Charles Meyers as CEO and the departures of two other senior executives, CIO Milind Wagle and CISO Michael Montoya.

Nov. 13, 2024: AMD to cut 4% of workforce

AMD will lay off around 1,000 employees as it pivots towards developing AI-focused chips, it said. The move came as a surprise to staff, as the company also reported strong quarterly earnings.

Nov. 7, 2024: Freshworks lays off 660

Enterprise software vendor Freshworks laid off around 660 staff, or around 13% of its headcount, despite reporting increased revenue and profits in its fourth fiscal quarter. The company described the layoffs as a realignment of its global workforce.

Sept. 17, 2024: Cisco lays off 6,000

After laying off around 4,200 staff in February, Cisco is at it again, laying off another 6,000 or around 7% of its workforce. Among the divisions affected were its threat intelligence unit, Talos Security.

Aug. 20, 2024: General Motors lays off 1,000 software staff

More than 1,000 software and services staff are on the way out at General Motors, signalling that it could be rethinking its digital transformation strategy. In an internal memo, the company said that it was moving resources to its highest-priority work and flattening hierarchies.

August 1, 2024: Intel removes 15,000 roles

Intel plans to cut its workforce by around 15% to reduce costs after a disastrous second quarter. Revenue for the three months to June 29 stagnated at around $12.8 billion, but net income fell 85% to $83 million, prompting CEO Pat Gelsinger to bring forward a company-wide meeting in order to announce that 15,000 staff would lose their jobs. “This is an incredibly hard day for Intel as we are making some of the most consequential changes in our company’s history,” Gelsinger wrote in an email to staff, continuing: “Our revenues have not grown as expected — and we’ve yet to fully benefit from powerful trends, like AI. Our costs are too high, our margins are too low. We need bolder actions to address both — particularly given our financial results and outlook for the second half of 2024, which is tougher than previously expected.”

July 4, 2024: OpenText to lay off 1,200

OpenText said it will lay off 1,200 staff, or about 1.7% of its workforce, in a bid to save around $100 million annually. It plans to hire new sales and engineering staff in other areas in 2025, it said.

June 4, 2024: Microsoft lays off staff in Azure division

Microsoft laid off staff in several teams supporting its cloud services, including Azure for Operations and Mission Engineering. The company didn’t say exactly how many staff were leaving.

April 4, 2024: Amazon downsizes AWS in a fresh cost-cutting round

Amazon announced hundreds of layoffs in the sales and marketing teams of its AWS cloud services division — and also in the technology development teams for its physical retail stores, as it stepped back from efforts to generalize the “Just Walk Out” technology built for its Amazon Fresh grocery stores.

April 1, 2024: Dell acknowledges 13,000 job cuts

Dell Technologies’ latest 10K filing with the US Securities and Exchange Commission disclosed that the company had laid off 13,000 employees over the course of the 2023 fiscal year; it characterized the layoffs and other reorganizational moves as cost-cutting measures. “These actions resulted in a reduction in our overall headcount,” the company said. A comparison to the previous year’s 10K filing, performed by The Register, found that Dell employed 133,000 people at that point, compared to 120,000 as of February 2024. Dell announced layoffs of 6,650 staffers on Feb. 6, but it is unclear whether those cuts were reflected in the numbers from this year’s 10K statement.

See news of earlier layoffs.

The newest member of the corporate workforce never sleeps, never asks for a raise, and can be cloned before lunch. It can also confidently make the wrong decision thousands of times before anyone notices.

That helps explain why some technology leaders have started talking about AI agents as employees, co-workers, or interns rather than software. Once an agent can update records, issue refunds, send communications, or act across multiple enterprise systems, deploying it no longer looks much like installing another application.

Recent Harvard Business Review articles have pushed that analogy further. One argues that agents should be treated like a new workforce, with defined roles, authority, sources of truth, supervision, and audit trails. Another recommends giving agents names and job descriptions, onboarding them, evaluating their performance, and increasing their responsibilities after they prove themselves.

But there is a catch: People may start believing the metaphor.

A separate HBR study of 1,261 managers found that when AI was framed as an employee rather than a tool, managers with experience working around AI agents took less personal responsibility for results and assigned more responsibility to the AI. They also escalated more problems and caught fewer errors. In the study, 31% of respondents said their companies already framed AI as a teammate or employee, while 23% said agents appeared on organizational or work charts.

For IT leaders, the answer may therefore be to borrow freely from the employee-management playbook — without extending the metaphor too far.

Don’t put software on the org chart

Amy Loomis, group vice president at IDC, draws a hard line around one word: responsibility.

Humans, she says, have obligations to their companies and to one another, and they bring an understanding of corporate culture and values that an agent can mimic linguistically without possessing.

That makes calling an agent a co-worker potentially more than harmless anthropomorphism. The label suggests a peer relationship and can encourage people to cede judgment to a system that’s very good at giving what was requested, Loomis says, but not necessarily at recognizing what was actually needed.

“Accountability is something that has qualities associated with it that are uniquely human,” she says. “Agents may be given permission to access data, but the accountability for what they do with that access lies with the person who gave the agent access, not the agent itself.”

That distinction still leaves plenty to borrow from employee management. It makes sense to give an agent traceable access and tightly scoped permissions — and to institute a kill switch to prevent the agent from having continued access. But Loomis finds it more effective to think in terms of giving an agent an operations charter rather than a human identity: define what the system does, what it may access, and what humans remain responsible for.

In other words, give the agent a security badge. Just don’t put its picture on it.

The employee metaphor has a job to do

Raja Iqbal, founder of agentic AI governance company Ejento AI and co-author of the HBR article “To Scale AI Agents Successfully, Think of Them Like Team Members,” is closer to Loomis than the headline suggests.

Iqbal says the metaphor is intended to put CIOs, CISOs, and other technology leaders into the right “cognitive posture.” Thinking about an agent as a team member, he argues, can remind an enterprise to impose familiar management disciplines: a unique identity, clear human oversight, defined authority, spending limits, approved information sources, and an audit trail.

If another term produces the same discipline, he’s fine with that too.

In fact, Iqbal explicitly rejects synthetic employees with human personas and seats on the org chart. That creates exactly the accountability problem critics worry about: “Bob did it” becomes an excuse even though Bob is software.

“The metaphor is dangerous when it’s decorative,” Iqbal says. By that, he means companies get into trouble when they adopt the human trappings — names, personas, or the language of colleagues — without also imposing the supervision, limits, and accountability that make the analogy useful.

His preferred distinction is simpler: the agent needs a technical identity so the enterprise can reconstruct what it did, while a human must remain responsible for those actions. “The identity is the audit primitive, and the human owner is the accountability primitive,” he says. Put more plainly, the agent identity answers what acted; the human owner answers who is accountable.

The employee analogy becomes more useful again when deciding how much freedom an agent should receive. Iqbal recommends graduated autonomy. An agent might begin with a human approving every action, progress to performing low-risk actions independently, and eventually receive bounded autonomy if its observed performance justifies it. A serious error can send it back down the ladder — or out the door entirely.

That sounds a lot like a probation period for a new employee. It’s also simply good software governance for a probabilistic system.

At DXC, professional agents are software

Russell Jukes has had plenty of opportunity to test that distinction. As chief digital and information officer at DXC Technology, he oversees AI in an IT services organization with roughly 115,000 employees.

“We think about [an AI agent] as a superpower, not as a person,” he says.

DXC separates agents into two categories. Personal agents work for individual employees and generally operate using the employee’s identity and access. Professional agents are enterprise systems built for broader workflows. On one of DXC’s major AI platforms, employees have so far created roughly 8,000 personal agents, compared with about 100 professional agents.

The professional variety receives much stricter oversight. It can have its own nonhuman identity, credentials, permissions, and authority boundaries. Activity passes through control planes that allow DXC to see what agents are doing and, when necessary, shut them down.

Jukes thinks many of these agents will eventually disappear from users’ view altogether. An agent might scan internal resource requirements overnight and recommend employees for projects. Nobody needs to greet it in the morning or consider it a colleague; they simply receive the result.

That’s where he parts company with the worker metaphor.

Jukes says he learned early on that AI cannot be deployed like conventional SaaS. His first attempt followed the familiar software model: make the application available, let employees use it within the prescribed workflow, and expect adoption to follow. “I did that, and nobody used it,” he says. The experience convinced him that AI requires a different approach, and he vowed to “never deploy AI like it’s SaaS again.”

Conventional SaaS is largely deterministic: the software constrains users to a defined workflow and produces predictable outputs. Agentic AI is different. It can interpret a goal, choose among tools and data sources, and decide how to get to an outcome. For Jukes, that means CIOs have to design the policies, permissions, data access, guardrails, and authority around the agent rather than simply deploy another application.

That also creates a clearer chain of responsibility. If a person approves the agent’s action, Jukes says that person owns the decision. If an autonomous agent behaves according to a business policy, accountability belongs with the people responsible for that policy. If the technology fails to operate as designed, responsibility moves to IT.

The agent itself never gets handed the blame.

Maybe treat it like an intern after all

Nina Tatsiy, global CIO of Quadient, an automation technology company, takes a position somewhere between Iqbal and Jukes. She calls agents interns, but deliberately uses the term as an analogy, not an organizational designation.

Agents must be managed as software, with security, governance, and technical controls, while recognizing that their probabilistic behavior requires additional supervision. “You have to do both,” Tatsiy says.

An intern does not receive every password and authorization on the first morning. Neither should an agent. It has to be onboarded, trained, watched, retrained when its environment changes, and eventually retired when it’s obsolete.

Quadient generally avoids giving agents human names. Tatsiy worries that doing so encourages people to see them as real colleagues capable of judgment.

“Overtrust is a problem,” she says, particularly because AI tends to state conclusions with such assurance. Tatsiy prefers using AI to challenge a hypothesis or surface questions people haven’t considered rather than allowing it to make the conclusion for them.

Yet the intern analogy has proved useful operationally.

In one accounts-payable deployment, Quadient had an agent effectively shadow human workers and learn from their feedback across different scenarios. Only after its performance had been tested across increasing levels of complexity did it begin providing recommendations. Humans still made the final decision.

The agent, in other words, earned more trust. It didn’t earn accountability.

Borrow from HR, but keep humans in charge

The emerging divide may therefore be less about whether agents are employees or software than about which parts of each management model IT leaders should retain.

Agents need individual technical identities, but not human identities. They need defined responsibilities, but not jobs in the human sense. They need monitoring and evaluation, but not annual performance reviews. They can receive progressively greater authority, but not progressively greater accountability.

And the stronger they become, the more important that distinction becomes.

Treating an autonomous agent like ordinary SaaS ignores the fact that it can interpret, choose, and act in ways conventional software cannot. Treating it like Steve from Accounting creates a different problem: sooner or later somebody may start assuming “Steve” knows what he’s doing.

IT leaders may indeed need to borrow heavily from HR as agentic AI spreads across the enterprise. They just shouldn’t start issuing employee badges.

Related reading:

• 6 ways to make AI accountability stick
• From chatbots to colleagues: How agentic AI is redefining enterprise automation
• Why AI adoption keeps outrunning governance — and what to do about it
• AI is spreading decision-making, but not accountability

While the number of US jobs declined by 23,000 in July, employment in the tech sector rebounded as the AI revolution continues to gain steam.

The national unemployment numbers were reported Friday by the US Bureau of Labor Statistics. At the same time, research firms said July was a good month for IT hiring compared to June.

According to CompTIA, which analyzed the BLS data, tech sector jobs rose in July by 3,700. In June, the IT sector had lost 900 jobs.

Companies last month hired in the cloud, hosting, information processing, data, and semiconductor manufacturing sectors, CompTIA said in a statement. 

“We’re entering a labor market where opportunity is increasingly concentrated around specific skills, industries, and investments,” said Ger Doyle, regional president of North America at ManpowerGroup, a labor consulting firm.

For example, data center hiring was up 39% in July compared to the same period last year, Doyle said. Not surprisingly, the data-center growth has been fueled by AI infrastructure needs and demand for hardware. That has helped increase the number of jobs in ancillary sectors such as transportation.

July hiring data showed heavy truck driver demand, which surged by 181% from June, Doyle said.

According to the BLS data, employment went up by 2.4% in the “computing infrastructure providers, data processing, web hosting, and related services” sectors, which is listed under the information sector.

Jobs in the “computer and electronic product manufacturing” sector — which is bunched under manufacturing — rose by 2.9% from June to July.

But bad news continued for the telecommunications sector, where the number of jobs declined by 1.5% from June to July. That continued a downward slide in recent years.

Overall job layoffs slowed in July, with 33,429 cuts announced; that’s down from 45,849 cuts announced in June, and the lowest since July 2024, according to data from Challenger, Gray and Christmas.

“Hiring has also increased over last year by 25%, so while AI is shifting the labor market, it is not dismantling it,” said Andy Challenger, chief revenue officer for Challenger, Gray & Christmas.

The tech sector announced 9,867 cuts in July, bringing the year-to-date total to 149,023 so far in 2026, according to Challenger figures.

Tech sector hiring and job losses vary as organizations use different measurement techniques to gauge the overall hiring environment. 

The top-line US unemployment rate declined to 4.1% from 4.2%, in part because of  workers leaving the workforce or not looking for jobs, indicating a slow labor market.

Still, hiring demand exists across the US, despite declining labor force participation and longer job searches, Doyle said.

Because technology underpins many of the changes occurring across sectors such as healthcare and services, employers are rethinking hiring.  “That’s why the labor market many workers are experiencing doesn’t always match the one described by the headline numbers,” Doyle said.

ADP’s National Employment report said only 44,000 jobs were added to private payrolls in July, with choppiness across sectors.

But demand for AI skills continues to rise, according to research firms that track growth by analyzing job listings. CompTIA noted that about 14,000 new job listings in July sought AI and machine learning skills.

It’s not clear how the ongoing AI boom may be hurting or helping human jobs. Many recent job cuts have been attributed to AI, though some companies have been accused of using the technology as a rationale for cuts they made for other reasons.

A recent OECD report said that even manual jobs once thought immune to AI are at risk of being taken over by robots. The OECD report said creative jobs — typically management, arts, and social work — will be least threatened by AI.

There are also increasing indications that successful AI deployments will require humans in the loop. For example, more consulting firms are using forward-deployed engineers (FDEs) to implement agentic AI. And smaller consultancy firms are finding more productivity by automating mundane work with AI and spending more time meeting client requirements.

Among a range of factors leading to a wave of tech sector layoffs in 2026 is the rapid rise of artificial intelligence and automation. Companies are reconfiguring their workforces to leverage AI for increased efficiency and reduced operating costs. This realignment and reduction is implemented even by companies reporting strong financial performance.

But it’s not just AI leading to workforce cuts. Complementing this technological shift are ongoing economic uncertainty, inflation, and higher interest rates, compounded by a chip shortage and rising energy costs. This mix is driving companies to cut costs and streamline operations for increased efficiency.

According to data compiled by Layoffs.fyi, an online tracker that keep tabs on job losses in the technology sector, 123,941 tech employees were laid off at 269 companies in 2025. The site also reports that 71,981 government employees were laid off by DOGE alone, with 182,528 total federal workers laid off.

Here is a list — to be updated regularly — of some of the most prominent technology layoffs the industry has experienced recently.

Notable tech layoffs in 2026

• Monday.com
• Microsoft
• Meta
• Cisco
• Cloudflare
• Oracle
• Atlassian
• Salesforce
• Amazon
• Ericsson

July 22, 2026: Monday.com cuts 20% of its workforce to restructure for the AI era

The company says the decision to cut 620 jobs isn’t about margins, but about creating a flatter organization built around AI agents, autonomous teams, and deeper customer engagement.

July 6, 2026: Microsoft cuts 4,800 jobs, primarily in sales and Xbox teams

As the company trims thousands of jobs, it’s also investing in embedded engineering teams and AI infrastructure. The layoffs come several weeks after the company offered 8,750 US employees voluntary retirement buyouts.

June 5, 2026: Tech industry cut 38,242 jobs in May, worst since 2024

AI was blamed for 40% of the job cuts in May, up from 7% in January, according to research by employment placement company Challenger, Gray & Christmas.

May 20, 2026: Meta cuts 8,000 jobs, around 10% of workforce

The cuts are expected to expected to hit Meta’s engineering and product teams the hardest, arriving as Meta pivots toward AI to boost efficiency across its organization, according to Yahoo Tech.

May 13, 2026: Cisco to cut nearly 4,000 jobs despite strong growth in AI, enterprise networking

Despite reporting positive financial news — including record third-quarter revenue of $15.8 billion, a 12% year-over-year increase — Cisco said it will eliminate almost 4,000 jobs.

May 7, 2026: Cloudflare to cut 1,100 jobs in AI-focused restructuring

About 20% of Cloudflare’s global workforce will be culled as the company pivots for the agentic AI era, Reuters reported.

April 1, 2026: Oracle to cut up to 30,000 jobs globally, putting enterprise support and roadmaps at risk

Oracle began laying off employees on March 31 in what could be the largest workforce reduction in the company’s history. Employees received termination emails at 6 a.m. local time with immediate system lockouts and no prior warning. (Note: in June, CNBC put the final layoff tally at 21,000.)

March 12, 2026: Atlassian cuts 1,600 jobs to fund AI and enterprise expansion

Atlassian will reduce its global workforce by approximately 10%, eliminating around 1,600 roles, as the collaboration software maker redirects capital toward artificial intelligence development and enterprise sales.

March 11, 2026: Tech layoffs surpass 45,000 in early 2026

A recent analysis by RationalFX found 45,363 job cuts globally so far this year—with roughly 68% or more than 30,000 occurring in the U.S. — highlighting ongoing workforce cuts even as many tech companies report strong revenue growth.

February 10, 2026: Salesforce lays off staffers as executive leadership churn continues

Salesforce has reduced close to 1,000 roles earlier this month across teams, including marketing, product management, data analytics, and its Agentforce AI unit, Business Insider reported, quoting employees familiar with the matter.

January 23, 2026: Amazon layoffs expected to disproportionately hit AWS and tech talent

As the market slows down, AWS and other Amazon units are preparing for another round of layoffs, which is expected to overwhelmingly impact tech talent. An email from HR leader Beth Galetti on Jan. 28 confirmed 16,000 job cuts.

January 15, 2026: Ericsson plans to shed 1,600 jobs in Sweden

 Ericsson lans to cut some 1,600 jobs in Sweden, the telecommunications equipment maker said doubling down on recent cost-saving measures that have helped it weather a prolonged downturn in telecoms spending, Reuters reports.

January 13, 2026: Meta plans to cut around 10% of employees in Reality Labs business

Meta plans to cut around 10% of the employees in its Reality Labs division who work on products including the metaverse, according to three people with knowledge of the discussions, according to The New York Times.

Layoffs in 2025

• Cisco
• Oracle
• Windsurf
• Intel
• Microsoft
• Crowdstrike
• HPE
• Autodesk
• HPE
• CISA
• Workday
• Salesforce
• Meta

Global tech-sector layoffs surpass 244,000 in 2025

Economic uncertainty, elevated interest rates, and AI adoption have driven workforce reductions across tech companies worldwide, according to a RationalFX report.

October 28, 2025: Amazon to cut 14,000 jobs across company

Amazon will reduce its overall workforce by 14,000, cutting layers of management across the company and hiring in some areas to support its “biggest bets”.

August 18, 2025: Cisco and Oracle to cut hundreds of Bay Area jobs

Tech companies Cisco and Oracle are cutting hundreds of jobs across the Bay Area. Cisco will eliminate 221 positions at its Milpitas and San Francisco offices, effective Oct. 13. Oracle is reducing 101 positions in Santa Clara on the same date 

August 5, 2025: 3 weeks after acquiring Windsurf, Cognition offers staff the exit door

Cognition, the AI coding startup that acquired rival company Windsurf three weeks ago, laid off 30 employees last week and is offering buyouts to the roughly 200 remaining employees on the team, reports The Information.

July 25, 2025, Intel to lay off 22% of workforce, CEO Tan signals ‘no more blank checks’

Intel will reduce its workforce to 75,000 employees by the end of 2025 as new CEO Lip-Bu Tan implements sweeping changes designed to transform the struggling chipmaker

July 8, 2025, Intel layoffs begin: Chipmaker is cutting many thousands of jobs

Intel has begun laying off employees across the company. CEO Lip-Bu Tan told workers back in April to expect major layoffs at Intel in the coming months as the chipmaker slashes costs and overhauls its organization after years of technical setbacks and falling sales.

July 2, 2025: Microsoft will cut 9,000 workers

Microsoft will lay off about 9,000 employees, a source familiar with the workforce cut told CNBC.  The cuts will reportedly affect less than 4% of Microsoft’s global workforce and will impact different teams, geographies and levels of experience. This is the latest in a string of cuts the tech giant has made this year.

June 17, 2025: Intel looks to factory layoffs to return to profitability

Intel will lay off up to 20% of its manufacturing sector employees starting in July, according to media reports, as the company looks for options as it seeks a return to profitability. The cuts reportedly will be made around the world, but some of the layoffs will be closer to home, according to a report in The Oregonian citing an internal company memo from Intel manufacturing Vice President Naga Chandrasekaran.

May 7, 2025: CrowdStrike to lay off 5% of staff

CrowdStrike announced a plan to cut about 500 roles, roughly 5% of its workforce, to streamline operations and reduce costs. The cybersecurity company will incur about $36 million to $53 million in charges related to the layoffs

March 6, 2025: HPE cuts 2,500 jobs, remains committed to Juniper buy

CEO Antonio Neri told Wall Street analysts that HPE would begin implementing a cost-cutting program involving layoffs of about 2,500 employees over the next 18 months. HPE employs about 61,000 people worldwide.

Feb. 27, 2025: Autodesk to lay off 9% of workforce

Software maker Autodesk is laying off 1,350 staff. With the rise of subscription and multi-year contracts billed annually, and self-service enablement, it finds it needs fewer sales staff, CEO Andrew Anagnost said in a message to employees. And with its cloud, platform, and AI products proving most profitable, it’s concentrating its staff and investments there.

Feb. 27, 2025: HP to lay off 2,000 more

As part of an ongoing restructuring, HP plans to lay off up to another 2,000 workers. In recent weeks, the company has tried — unsuccessfully — to do away with telephone support staff by forcing callers to wait for at least 15 minutes if they refuse to use self-service support resources online. The company swiftly backtracked, but wider job cuts are still on.

Feb. 21, 2025: CISA lays off 130

Government employees get laid off too: In this case, 130 workers at the US Cybersecurity and Infrastructure Security Agency are being shown the door as a result of a DOGE decision. Cybersecurity experts are concerned that the cuts will harm the international collaborations that CISA has fostered, quite apart from their concerns about the security of the DOGE layoff process itself.

Feb. 5, 2025: Workday lays off 1,750

As it moves to invest more in AI and international growth, Workday is laying off 8.5% of its workforce and disposing of unused office space. Some analysts fear the cutbacks will affect the company’s customer service — unless AI can pick up the slack.

Feb. 4, 2025: Salesforce lays off over 1,000

At the same time as it’s hiring sales staff for its new artificial intelligence products, Salesforce is laying off over 1,000 workers across the company, according to Bloomberg. As of June, 2024, the company had over 72,000 employees, according to its website. Salesforce did not comment on the report. In 2024 the company reportedly laid off around 1,000 staff too, in two waves: January and July.

Jan. 14, 2025: Meta will lay off 5% of workforce

Mark Zuckerberg told Meta employees he intended to “move out the low performers faster” in an internal memo reported by Bloomberg. The memo announced that the company will lay off 5% of its staff, or around 3,600 staff, beginning Feb. 10. The company had already reduced its headcount by 5% in 2024 through natural attrition, the memo said. Among those leaving the company will be staff previously responsible for fact checking of posts on its social media platforms in the US, as the company begins relying on its users to police content.

Tech layoffs in 2024

• Equinix
• AMD
• Freshworks
• Cisco
• General Motors
• Intel
• OpenText
• Microsoft
• AWS
• Dell

Nov. 26, 2024: Equinix to cut 3% of staff

Despite intense demand for its data center capacity, Equinix is planning to lay off 3% of its workforce, or around 400 employees. The announcement followed the appointment of Adaire Fox-Martin to replace Charles Meyers as CEO and the departures of two other senior executives, CIO Milind Wagle and CISO Michael Montoya.

Nov. 13, 2024: AMD to cut 4% of workforce

AMD will lay off around 1,000 employees as it pivots towards developing AI-focused chips, it said. The move came as a surprise to staff, as the company also reported strong quarterly earnings.

Nov. 7, 2024: Freshworks lays off 660

Enterprise software vendor Freshworks laid off around 660 staff, or around 13% of its headcount, despite reporting increased revenue and profits in its fourth fiscal quarter. The company described the layoffs as a realignment of its global workforce.

Sept. 17, 2024: Cisco lays off 6,000

After laying off around 4,200 staff in February, Cisco is at it again, laying off another 6,000 or around 7% of its workforce. Among the divisions affected were its threat intelligence unit, Talos Security.

Aug. 20, 2024: General Motors lays off 1,000 software staff

More than 1,000 software and services staff are on the way out at General Motors, signalling that it could be rethinking its digital transformation strategy. In an internal memo, the company said that it was moving resources to its highest-priority work and flattening hierarchies.

August 1, 2024: Intel removes 15,000 roles

Intel plans to cut its workforce by around 15% to reduce costs after a disastrous second quarter. Revenue for the three months to June 29 stagnated at around $12.8 billion, but net income fell 85% to $83 million, prompting CEO Pat Gelsinger to bring forward a company-wide meeting in order to announce that 15,000 staff would lose their jobs. “This is an incredibly hard day for Intel as we are making some of the most consequential changes in our company’s history,” Gelsinger wrote in an email to staff, continuing: “Our revenues have not grown as expected — and we’ve yet to fully benefit from powerful trends, like AI. Our costs are too high, our margins are too low. We need bolder actions to address both — particularly given our financial results and outlook for the second half of 2024, which is tougher than previously expected.”

July 4, 2024: OpenText to lay off 1,200

OpenText said it will lay off 1,200 staff, or about 1.7% of its workforce, in a bid to save around $100 million annually. It plans to hire new sales and engineering staff in other areas in 2025, it said.

June 4, 2024: Microsoft lays off staff in Azure division

Microsoft laid off staff in several teams supporting its cloud services, including Azure for Operations and Mission Engineering. The company didn’t say exactly how many staff were leaving.

April 4, 2024: Amazon downsizes AWS in a fresh cost-cutting round

Amazon announced hundreds of layoffs in the sales and marketing teams of its AWS cloud services division — and also in the technology development teams for its physical retail stores, as it stepped back from efforts to generalize the “Just Walk Out” technology built for its Amazon Fresh grocery stores.

April 1, 2024: Dell acknowledges 13,000 job cuts

Dell Technologies’ latest 10K filing with the US Securities and Exchange Commission disclosed that the company had laid off 13,000 employees over the course of the 2023 fiscal year; it characterized the layoffs and other reorganizational moves as cost-cutting measures. “These actions resulted in a reduction in our overall headcount,” the company said. A comparison to the previous year’s 10K filing, performed by The Register, found that Dell employed 133,000 people at that point, compared to 120,000 as of February 2024. Dell announced layoffs of 6,650 staffers on Feb. 6, but it is unclear whether those cuts were reflected in the numbers from this year’s 10K statement.

See news of earlier layoffs.

OpenAI has introduced spend controls and enhanced usage analytics for ChatGPT Enterprise to enable organizations to monitor AI adoption, track consumption across teams, and set budgets for AI usage. But, analysts cautioned, it still can’t show how those costs lead to business benefits.

The new features provide administrators with centralized dashboards showing how ChatGPT is being used across an organization, enabling them to understand adoption patterns, and manage AI costs by setting budgets and tracking spending.

“The Global Admin Console brings ChatGPT and Codex credit usage into one view, so admins can see a more granular breakdown of credit consumption across users, products, and models — helping them understand where spend is coming from and how it maps to actual credit usage,” OpenAI said.

A shift toward AI cost governance

The introduction of budgeting and usage analytics reflects a broader change in enterprise priorities, according to Biswajeet Mahapatra, principal analyst at Forrester.

“Enterprises are clearly shifting from adoption-led enthusiasm to cost and value governance, but this is a natural maturity transition rather than a pullback,” Mahapatra said. “AI is no longer an adoption problem but a measurement and credibility problem, with productivity gains present but fragmented and hard to tie to financial outcomes.”

As AI expands across business units, spending becomes distributed across teams, tools and experiments, making visibility and governance increasingly important, he said.

“Budgeting, usage visibility and spend controls are therefore becoming foundational, not just operational concerns, as they enable alignment between technology usage and business outcomes,” Mahapatra added.

OpenAI is addressing those needs with its new dashboards and spending controls address, he said.

Agent sprawl will add to cost control challenges

Anushree Verma, senior director analyst at Gartner, said AI cost governance is becoming a focus for enterprises, as fragmented pricing models, vendor-defined consumption units and inconsistent pricing structures make it difficult for organizations to predict AI costs.

She expects the challenge to intensify over the next few years as enterprises scale up their use of AI.

“By 2028, an average global Fortune 500 enterprise will have over 150,000 agents in use, up from less than 15 in 2025, generating significant agent sprawl, IT complexity and management challenges,” she said.

Against that backdrop, OpenAI’s new administrative capabilities provide organizations with tools to monitor organizational usage and spending as AI deployments become larger and more distributed.

Measuring AI value beyond consumption

While OpenAI’s analytics emphasize adoption patterns and usage visibility, analysts say enterprises will ultimately need to connect AI consumption with business outcomes.

“Token consumption alone is insufficient because it measures activity rather than impact,” Mahapatra said.

Instead, organizations should evaluate AI initiatives using business metrics such as revenue growth, cost reduction and risk mitigation alongside operational indicators including productivity improvements and quality gains.

Verma said traditional cloud FinOps practices are also evolving to accommodate AI’s usage-based economics.

“Traditional FinOps practices were built around predictable, centralized cloud environments and are insufficient for handling unpredictable AI consumption metrics, such as token usage, LLM requests and GPU hours,” she said.

She added that real-time tracking is becoming increasingly important as multiagent systems scale, because misconfigurations can cause AI costs to rise rapidly across interconnected environments.

This article first appeared on CIO.

A federal judge has rebuffed Workday’s claim that it cannot be held liable under California anti-discrimination laws when its tools are used to screen (and potentially reject) job candidates in other states.

This week, US District Judge Rita Lin indicated that she will likely allow additional state discrimination claims against Workday to move forward. This would significantly expand the closely-watched case and likely ratchet up scrutiny of AI recruiting tools and their potentially inherent biases when it comes to age, race, sex, disabilities, and other factors.

Further, it could indicate that, even if a company is not the final employer, it may be held liable if its tools materially influence who gets rejected. This could set new legal standards for AI hiring systems, and have implications across industries, experts note.

“This case reinforces the importance of actually managing AI risks,” said Valence Howden, advisory fellow at Info-Tech Research Group. “If an AI-enabled model or ATS [Applicant Tracking System] is making decisions based on historical information, it can raise questions about whether bias in outcomes and datasets has been properly addressed.”

The case so far

Mobley v. Workday, Inc. alleges that Workday’s AI screening tools discriminate against job seekers based on age, race, and disability. The suit was filed in 2024 in the US District Court of California by Derek Mobley, a Black disabled man over 40, who claimed Workday’s algorithms continually screened him out as he applied for more than 100 positions on the platform.

The claims alleged discrimination prohibited by several US and California statutes: Race and sex under the Civil Rights Act of 1964 (Title VII); disability under the Americans with Disabilities Act of 1990 (ADA); age under the Age Discrimination in Employment Act of 1967 (ADEA); and race, gender, and age under California Fair Employment and Housing Act (FEHA).

Specifically, the suit centered around Workday’s use of automated, algorithm-driven tools for applicant screening. It alleged that these systems rely on historical data and statistical modeling that can make them susceptible to existing biases, even if protected characteristics like race, age, sex, or disability are not explicitly provided.

Bias may enter these systems in different ways, the plaintiffs argued, including via training data, model design, and evaluation criteria for candidate fit. The system could reproduce discriminatory outcomes by making correlations from data. For instance, years of experience on a resumé may indicate age; long employment gaps may infer a disability or caregiving responsibilities; educational and institutional affiliations could reflect race.

Workday has argued that it is not subject to liability under employment statutes because it does not qualify as the job applicants’ “employer.” But federal judges have allowed key parts of the lawsuit to move forward, ruling that Workday could potentially be treated as an employer’s “agent” for the purposes of anti-discrimination law.

The latest dispute centers on FEHA. According to legal sources, the California statute is among the strongest anti-discrimination laws in the US, in many cases providing broader protections than federal employment laws.

Workday asked the court to dismiss claims brought under California law, saying FEHA should not apply to the hiring decisions of out-of-state employers and applicants. The company’s lawyers argued that enforcing this would effectively allow California law to supersede that of other states, just because a company used their platform.

But Lin disagreed, saying FEHA does apply, and in fact, Workday is directly liable for its “own engagement in FEHA-regulated activities on the employer’s behalf.” Holding businesses liable for “their own discriminatory conduct” is within the scope and purposes of FEHA and consistent with public policy.

However, the issue is still to be decided; Lin did not indicate when she would release a final ruling.

Workday’s defense

A Workday spokesperson called the claims in the suit “false.”

“Workday’s AI recruiting tools don’t make hiring decisions and are designed with human oversight at their core,” the spokesperson told CIO. “Our technology looks only at job qualifications, not protected traits like race, age, or disability. We rigorously test our products as part of our responsible AI program to confirm our tools do not harm protected groups.”

Workday’s platform is meant to provide insights on how well a candidate’s qualifications match the requirements of a posted job, the company said. Those tools focus only on qualifications listed in a candidate’s application, which are compared to qualifications identified by the employer as important for the job.

Workday’s Chief Responsible AI Officer Kelly Trindel said its AI does not make employment decisions, automatically reject candidates, or determine who gets a job; further, she said, there is no evidence that the company’s tools result in harm to protected groups.

Trindel, who is former chief analyst of the Equal Employment Opportunity Commission (EEOC), leads a dedicated team composed of psychologists and PhD-level data scientists whose sole focus is to ensure that its AI is “responsible, fair, and ethical.” She said that the company’s AI systems undergo ongoing reviews throughout their lifecycle to help prevent unintended consequences, and Workday is “committed to accountability, transparency, and trust,” and invests “significant resources” into identifying and mitigating bias.

Further, she said, Workday has a company-wide commitment to ethical AI, and an independently-evaluated AI governance program based on standards from the National Institute of Standards and Technology (NIST) and the International Standards Organization (ISO).

“Workday builds AI to support people, not replace them, and this is of particular importance when it comes to hiring,” Trindel noted. Its platform is designed to help employers “manage high-volume processes more efficiently, surface relevant information, and reduce administrative work so teams can spend more time applying their expertise and judgement to hiring decisions.”

What this means for enterprise leaders

Workday isn’t alone in its legal challenges; other AI hiring tools are also being scrutinized over their methodologies, algorithms, and data-collecting practices. Eightfold, for one, is also facing a California class action lawsuit alleging that its tools unfairly rely on job candidates’ online data to predict whether they’d be a good fit for a position.

This means that enterprises, who are already feeling increased pressure to document hiring decisions, conduct AI bias audits, and maintain human oversight in recruitment and hiring, must be even more diligent in their vetting of AI tools.

Organizations must be actively defining how these recruitment tools should work, identifying bias in their algorithms, and setting up structures to test for bias across the tools’ decision-making logic, Info-Tech’s Howden advised.

“Validation of non-biased outcomes also needs to be active and ongoing, rather than a point-in-time exercise,” he said.

While Workday and others say human oversight is paramount, “it’s hard to incorporate humans into the process if the platform does the weeding out before humans have the ability to intervene,” Howden pointed out.

Discriminatory biases can exist in past hiring decisions, so it’s easy to forget that AI can “emulate and adapt those biases as part of its perspective,” he said. That includes how AI looks at language: Different cultures use different phrasing, and AI can capture that and use it to exclude candidates.

Ultimately, he called the case a “cautionary tale” illustrating how lightly some organizations have been treating AI risk. It also highlights the urgency involved in building out more advanced enterprise risk practices, “rather than relying on the limited capabilities they may have employed up until now.”

This article originally appeared on CIO.com.

While AI is proliferating across the workplace, it is introducing a new productivity paradox: While the technology makes work feel faster, it actually pushes more burden onto employees to provide context, perform quality checks, then rinse and repeat across numerous disparate tools.

This, according to a new survey of 6,000 full-time digital workers by Glean’s Work AI Institute, results in two emerging behaviors: “botsitting,” all the unrecognized work that goes into making AI actually usable; and “botshitting,” shipping AI-generated work that is unverified, not that well understood, or perhaps not even trustworthy. The survey report was co-authored by experts from Work AI Institute, Emory University, Stanford University, UC Berkeley, UC Santa Barbara, UNC Charlotte, University College London, and University of Notre Dame.

“It’s definitely in many ways a vicious cycle that feeds itself,” said Rebecca Hinds, head of Glean’s research center the Work AI Institute, a research collaborative of AI experts. Enterprises need to begin understanding and addressing the “massive, massive human labor that’s at the core of this.”

Workers are using AI more, getting more frustrated

There’s no doubt that AI is quickly becoming a central teammate in the workplace. Glean’s Work AI Institute found that 87% of digital workers are using AI: It is already automating more than a quarter of their work and saving about 11 hours a week.

Still, only 13% say the use of AI has significantly improved their company’s performance, and their time savings are being eaten up by the same technology that is producing them. Employees lose about one-third of their work week (6.4 hours) botsitting: feeding AI context, supervising outputs, debugging errors, cleaning up AI-generated work, and switching between AI tools.

“We’re seeing high, high rates of multiple tool usage, and often those tools aren’t connected,” said Hinds.

In terms of context-feeding, large language models (LLMs) are trained on the vast corpus of the internet, but not always on enterprise-specific data. Thus, employees often have to provide additional information around their company’s products, customers, services, or other details.

“They’re often feeling frustrated when the tools don’t understand enough about day to day work to be useful,” said Hinds. Also, because employees are using multiple tools, they often have to repeat the same prompt over and over.

“It’s exhausting for workers to not only do this, but to have the work be unrecognized, often unrewarded and unacknowledged within the organization,” she said.

Similarly, workers are having to catch outputs that might look polished and finished on the surface, but could be wrong, incomplete, or missing important context. Debugging is the biggest driver of exhaustion, because it is often conducted by people who didn’t necessarily contribute to the initial output, Hinds noted, so they first have to dig up background information.

However, “not all botsitting is bad,” Hinds emphasized. “Certainly, we want workers to have some level of ownership and oversight.”

But when it is unnecessary, it can lead to botshitting, where users ship AI-generated work they haven’t verified because they’re overwhelmed or time-constrained. Sixty-nine percent of users admit to doing so, and 41% say they sometimes deliver work they could not explain if asked. Another 28% blame AI for mistakes they themselves caused.

“Botshitting is offloading your critical human thinking, judgment, and understanding,” Hinds explained. “You’re offloading that work that absolutely needs to remain with the human.”

Workers using multiple AI agents are significantly more likely to do this, she added, because agents are so scalable, and can spiral out of control if they don’t have the right controls or permissions built around them, causing overwhelmed users to give up on their verification efforts.

“You don’t often see the negative impacts until 3, 4, 5, steps down the line,” said Hinds. “Then it requires all of this cleanup work, detective work, to understand where did the agent go wrong.”

Using AI … but not too much

Interestingly, more than half of the workers surveyed said they get more day-to-day help from AI than they get from their managers, and consider it easier to collaborate with than humans.

Still, they seem to be facing a Goldilocks problem when it comes to sharing their use of AI. Among self-identified high AI achievers, 54% are using unapproved tools or using approved tools in noncompliant ways, and 36% are hiding how much AI helps them.

As Hinds explained, depending on the context and the level of psychological safety an organization has provided, it can be “differentially beneficial or harmful” to show you’re using AI, and, on the flip side, to conceal that you’re using it too much, because that might make you less valuable, or perceived as less valuable, she said.

It’s a complicated balance, because, she noted, “there’s massive pressure in so many organizations to demonstrate AI fluency, to demonstrate you’re a power user.”

What successful organizations are doing differently

In fact, the report said, “The companies pulling ahead are doing something different. They aren’t spending a greater share of their AI time using AI. They’re spending a greater share on the work around it: setting context, defining what ‘good’ looks like, building judgment, and deciding what should never have been handed to a model in the first place.”

The most transformative organizations are addressing AI challenges proactively: Providing training and support, treating AI as an opportunity to redesign work, and formally rewarding AI skills. In addition, it noted, the hardest skill to build is knowing when not to use AI.

It is “not just clicks of the tool, not just tokens used, but real skills, real learning,” said Hinds. In addition to investing in workers, these organizations are clearly stating AI strategy and clarifying the “why” behind it. Governance should also be “living and breathing,” with companies continuously re-evaluating policies.

And it needs to happen at every level, top execs included, said Hinds: “It’s being able to see the executives use the technology, sharing both the success stories and the failures.”

Successful companies are also actively using metrics anchored in existing key performance indicators (KPIs). They are measuring quality, efficiency, and employee engagement in different ways, and putting data in the hands of employees so they can assess their own adoption and success.

“It’s less about surveillance and more about feedback in terms of how we work collectively,” said Hinds.

What’s “fascinating but perhaps not surprising,” she said, is that workers are increasingly using AI itself as a teacher, and prefer it over other learning channels. This speaks to the importance of low-code, no-code tools, with low learning curves and organizational context, that are embedded directly into workflows.

“It is starkly different from what we’ve seen with previous technologies,” she said.

This article originally appeared on CIO.com.

A US federal judge has ruled that the Trump administration’s $100,000 fee on new H-1B visa petitions was unlawful, giving technology companies temporary relief from a policy that threatened to raise the cost of hiring foreign skilled workers.

The decision removes, at least for now, a major cost burden for employers that use the H-1B program to fill roles in domains including software development, cloud computing, data science, and AI.

US District Judge Leo Sorokin in Boston found that the fee functioned as a tax that the administration did not have authority to impose without congressional approval. The ruling came in a lawsuit brought by 20 Democratic state attorneys general challenging the fee.

Standard employer costs for H-1B petitions typically range from about $2,000 to $5,000, making the proposed $100,000 payment a sharp increase for companies seeking foreign talent.

The ruling is unlikely to end uncertainty for employers, with the Trump administration expected to appeal. But it could allow companies that had paused international hiring plans to resume normal recruitment for the upcoming H-1B cycle, said Pareekh Jain, CEO of Pareekh Consulting. Still, he said, employers should remain cautious because the legal and policy concerns are likely to continue.

“This provides breathing room for CIOs, even though it’s temporary,” said Neil Shah, vice president for research and partner at Counterpoint Research. “They should make the necessary contingency plans, whether that means doing more with less by leveraging AI or relying more on local talent.”

How companies may rethink hiring

If higher H-1B costs return in another form, CIOs will have to be more selective about sponsorship, weighing the added cost against the strategic value of the role and the long-term potential of the employee, Shah said.

“Ultimately, the decision comes down to business unit P&L: whether the unit can absorb the cost of acquiring the talent for that role,” Shah added.

That uncertainty could also lead CIOs to compete for talent from other companies, potentially driving up salaries for skilled workers. Some CIOs may conclude that paying a one-time $100,000 fee, amortized over the employee’s tenure, is still more cost-effective than engaging in a bidding war for scarce local talent.

Danish Faruqui, CEO of Fab Economics, said that CIOs may reserve H-1B sponsorship for a narrower set of mission-critical roles if costs increase.

“If there is such a financial burden, CIOs will justify sponsoring very specific roles,” Faruqui said. “These would be principal enterprise architects, AI, ML, and deep-tech researchers, senior product managers, and regulatory and compliance experts.”

More routine or project-based roles are likely to be treated differently, Faruqui said.

“Junior to mid-level software engineers, entry-level business analysts, and entry-level data scientists would shift from H-1B to domestic hiring,” Faruqui said. “Cloud migration, DevOps, ERP, and CRM implementation could be done through contractors or consulting firms, while QA, product testing, tier-one help desk support, and legacy maintenance are roles that CIOs could prioritize for automation.”

Who would be most affected?

Startups, smaller companies, and enterprise IT departments would have faced the greatest pressure from the fee and stand to benefit most from the ruling, Jain said.

Large technology companies would have been better placed to absorb the $100,000 cost, he said. Meanwhile, companies with mature offshore delivery models may be less likely to increase their reliance on H-1B hiring.

The article originally appeared on CIO.

A report released Wednesday by Boston Consulting Group (BCG) indicates that many organizations are having difficulty converting efficiency gains that are AI-driven into any sort of measurable value.

The fourth edition of the consultancy’s annual Global AI at Work Survey reveals 42% of frontline employees who use AI on a regular basis save upwards of a full day each week; however, 66% are not given guidance on what to do with time they save, and “more than half don’t redirect it to strategic work.”

The report, AI at Work: Strategy Matters More Than Tools, is based on a global survey of 11,749 employees in 14 markets, from industries ranging from financial services to the healthcare sector.

David Martin, global leader of people and organization work at BCG, and the report’s lead author, said via email that the number of employees lacking the required guidance is surprising, “but it also tracks with what we see in many AI transformations. Companies have moved quickly to give people tools, but many have not yet redesigned the work around those tools.”

Saved time, he added, does not automatically become value. If a frontline employee saves a few hours a week, but has no direction on whether to use that time for customer service, quality improvement, innovation, or faster execution, “that value can simply leak out of the organization”

The fix is for leaders to change the scoreboard, Martin said: “Don’t just measure AI adoption or hours saved. Decide where that time should go, measure whether it is being reinvested, and give managers clear guidance on how to help teams use it. This is where AI transformation becomes a management challenge, not just a technology rollout.”

In fact, said Vinciane Beauchene, a managing director and partner at BCG and one of the report’s five co-authors, “the first wave of AI focused on individual productivity. The coming wave will need to transform collective work.”

“Everyone is talking about AI replacing work,” she said, “but it is in fact really about rethinking the human value-add inside.”

A managerial revolution underway

According to Beauchene, “this is the role of leaders. Our survey reveals a true managerial revolution in the age of AI; 65% of managers and leaders now believe agents will take over at least half of their job in the next three years, and frontline workers see their jobs evolving towards more managing and directing AI.”

A BCG release stated that the survey also highlights the continued emergence and maturity of AI agents, with 30% of respondents saying that agents are already integrated into workflows, more than double the number from last year’s report (13%).

Other key findings revealed that AI adoption among frontline workers has surged, with 74% saying they now use it daily or a few times a week, which is up 23 percentage points from a year ago. In addition, six out of 10 people believe that, within the next three years, AI agents could do at least half of their jobs.

And a survey slideshow released by the company pointed out, “the AI ‘honeymoon’ won’t last unless leaders bring strategic clarity driving sustained impact AI’s novelty and cognitive stretch fuel enjoyment early on. But sustained joy comes from strategic clarity. Employees thrive when the direction is real and the message reaches them with strong CEO involvement.”

Strategic clarity is a key differentiator

The report suggests that CEOs take a holistic approach to AI transformations by focusing on business outcomes as opposed to AI usage, investing in “redesigning work end-to-end, not in more tools,” placing people at the heart of that redesign, and governing AI not as a one-off program, but as a moving target.

Overall, BCG says that strategic clarity, “more broadly emerges from the survey as the most crucial differentiator in sustaining AI’s impact over time as organizations are moving past simply implementing AI tools in use case deployment initiatives.”

Increasingly, it adds, “the focus is shifting to redesigning end-to-end workflows and processes to reimagine functions, as well as to building and innovating new business models and products to drive growth, which have nearly doubled year-over-year.”

Global leader of BCG’s tech build and design unit BCG X Sylvain Duranton, also a report co-author, added, “employees don’t push back on AI intensity; they thrive when the strategy is clear, the direction is real, and the message reaches them.”

He added, “Business value and employee enjoyment aren’t trade-offs. The organizations capturing the greatest business value are the same ones where employees enjoy work the most.”

Despite the opportunity, the report notes that only one-third of frontline employees say that leadership’s communications about AI are clear, and only 28% “see a strong connection between what leaders say and what the organization actually does.”

However, Martin said, management can’t deal with this situation on its own. “CIOs have a critical role, but this is not a problem they can solve alone, and I would not frame it as something IT created by itself,” he noted.

Many organizations, he said, “started with the natural first step of getting tools into people’s hands safely and at scale. That was necessary, but it is not sufficient.”

The next phase “has to be much more cross-functional,” he said. “CIOs should help set the technology foundation, governance, data model, and measurement systems, but they also have an important role in creating strategic clarity. Employees need to understand why the organization is using AI, where it is meant to create value, and how it should change the work.”

Martin pointed out that CIOs should also pay close attention to cognitive load, especially on technology teams, as those teams are often the heaviest AI users.

“This means they may be among the most exposed to the mental strain that can come with reviewing outputs, managing AI tools, and keeping up with constant change,” he observed. The biggest gains come when technology strategy, workforce strategy, and employee experience move together. If AI remains only an IT program, companies will “undercapture” the value.

New expectations

The abundance of AI activity is also having another effect, in that 60% of respondents say the bar for work that counts as ‘good enough’ is now higher.

That, said Martin, is because AI is changing expectations. “If a tool can produce a first draft, summarize research, generate options, or automate a routine task, then ‘good enough’ moves up the value chain,” he said. “People are being asked to spend less time producing basic output and more time exercising judgment like checking quality, improving the answer, making decisions, and applying context.”

While that can be a good thing, he said, because it can make work more interesting and more valuable, “it also explains why employees are feeling more mental strain. The work that remains is often more complex. Leaders need to recognize that AI does not just make people faster, it changes what excellence looks like. That means companies need to update training, performance expectations, and management support accordingly.”

This article originally appeared on CIO.com.

Cloud computing has reached a crossroads. The high cost and data sensitivity of AI workloads are raising the appeal of private clouds, even as neoclouds and sovereign clouds shake up the cloud provider landscape. New cyberthreats, shifting compute requirements, and management complexity are adding to cloud complications.

Download the June 2026 issue of the Enterprise Spotlight from the editors of CIO, Computerworld, CSO, InfoWorld, and Network World, and learn how to navigate the latest cloud strategy developments.

A research project examining AI-driven recruitment hires across the US has revealed a systemic racial bias.

Researchers from Stanford University found a startling pattern of racial disparities when looking at the interview offers resulting from 4 million job applications submitted to 156 employers. The situation is aggravated by the “monoculture” in AI hiring software: More than 90% of US employers are screening job applicants with software, with 60% of Fortune 500 companies using the same tool, HireVue, the researchers found.

Applicants who applied to multiple companies using AI had all their applications rejected more often than would be expected if each company’s screening methods were independent. They calculated that Black and Asian candidates were rejected in greater numbers than baseline figures would suggest. According to the survey, 29,000 more Asians would have been interviewed if AI had not been deployed.

The researchers are concerned about the way in which AI is being used. “AI screening tools bring together three properties that should not co-exist in high-stakes decision-making: They are pervasively adopted, highly consequential, and opaque to the public,” they said in a news release presenting their work.

The effect of this will lead to workplaces dominated by a monoculture which may not be beneficial for companies going forward.

This article first appeared on CIO.