Monday.com Cuts 20% of Staff in AI-Focused Restructuring

Monday.com reached Google News after cutting about 620 jobs, or 20% of its workforce, while reorganizing around an AI work platform.

The company says AI is changing its products, operating model, and customer relationships. However, it denies that software directly replaced the departing employees. Monday.com plans to remove management layers, form smaller teams, and reinvest most expected savings in people, products, AI, and growth.

That distinction captures the central tension behind this year's technology layoffs. Companies increasingly describe AI as a reason to change their staffing mix without proving that a model or agent performed each eliminated job. Monday.com now joins Google, Microsoft, Amazon, Meta, Salesforce, and other employers using variations of that argument.

The result is not a simple story about machines replacing workers. It is a wider restructuring of budgets, teams, and expectations across the technology sector. Executives are asking fewer employees to operate faster while shifting spending toward infrastructure, models, agents, and specialized talent.

Monday.com Cut One-Fifth of Its Workforce

Monday.com's decision is a strategic reorganization with immediate human costs, not a theoretical prediction about future employment.

The company initiated its restructuring on July 22, 2026. Its regulatory filing says the plan will reduce its current workforce by approximately 20%.

That percentage represents about 620 employees worldwide. The company expects most restructuring work to finish during the second half of 2026.

Monday.com tied the plan to what it calls its AI Work Platform. This strategy moves the product beyond organizing tasks toward performing parts of the work through people and AI agents.

An AI agent is software that can pursue a defined goal by selecting and completing multiple actions. In a work platform, those actions might include updating records, routing requests, summarizing activity, or initiating another workflow.

Co-founder and co-CEO Eran Zinman said the company had changed its core vision during the previous nine months. Monday.com was moving from managing work to doing work for customers, he wrote.

The company's prior structure no longer suited that goal, according to Zinman. Monday.com therefore plans to reduce management layers and give smaller teams broader authority.

The restructuring also changes how the company sells and implements its products. Customers deploying agents need more configuration, governance, and operational support than customers purchasing a conventional project-management tool.

Monday.com plans to increase direct customer engagement and create roles in selected strategic areas. The filing says hiring will continue during 2026, even as hundreds of existing positions disappear.

This is the first important reversal. The company is cutting deeply while forecasting continued growth and recruitment.

Monday.com expects annual revenue to grow between 19% and 20% in 2026. It also increased its projected non-GAAP operating margin from approximately 13% to approximately 15%.

Management nevertheless insists that improving margins was not the purpose of the layoffs. Zinman said the vast majority of savings would be reinvested.

That claim deserves careful treatment. Reinvestment can still improve the company's economics if money moves from existing payroll toward models, computing capacity, product development, or different employees.

Monday.com has not published a role-by-role account showing which work AI can now perform. It also has not quantified the productivity gains that support a 20% reduction.

Its announcement instead presents an organizational thesis. Smaller teams, fewer approvals, and AI-assisted execution should move faster than the structure built for its earlier software business.

Whether that thesis works will depend on product adoption and customer outcomes. The size of the layoff does not verify the promised productivity improvement.

Google News Shows a Much Wider AI Layoff Pattern

Monday.com is the latest entry in a list of at least 21 major technology employers that cited AI during significant workforce changes in 2026.

The cases below appear in reverse chronological order. The language varies substantially across companies, so inclusion does not mean AI independently caused every lost job.

1. Monday.com, July 2026

Monday.com initiated a plan affecting approximately 620 employees, or 20% of its workforce. It linked the restructuring to its AI Work Platform, flatter management, autonomous teams, and a different customer-engagement model.

The company says it is not replacing people with AI. It is nevertheless redesigning the organization because management believes AI has changed how software companies should operate.

2. Microsoft, July 2026

Microsoft announced another workforce reduction affecting approximately 4,800 positions, with sales and gaming teams among those facing cuts. Company leadership said AI is changing work, but disputed a simple claim that AI directly caused the layoffs.

This distinction matters because Microsoft is also reallocating capital and talent toward AI infrastructure. Its reductions combine efficiency targets, organizational simplification, and investment priorities.

3. Salesforce, July 2026

Salesforce reportedly eliminated fewer than 1,000 positions across marketing, product management, analytics, and its Agentforce organization. The company had already reduced thousands of customer-support roles as AI agents handled more interactions.

Salesforce presents agents as both a product and an internal operating tool. That makes its own staffing decisions an important test of the efficiency story it sells customers.

4. Oracle, June 2026

Oracle disclosed that its workforce had fallen by 21,000 employees over the previous 12 months, a 13% decline. Its filing said adopting and deploying AI technologies had resulted, and might continue to result, in workforce reductions.

The disclosure covered a longer period than a single layoff event. It still provided one of the clearest formal acknowledgments that AI adoption influenced headcount.

5. GitLab, June 2026

GitLab cut roughly 350 employees, or about 14% of its staff. It said the restructuring would help fund infrastructure needed for rising activity from AI-driven development workflows.

GitLab's case differs from straightforward automation. AI is increasing demand on its platform, yet supporting that demand requires a different allocation of employees and capital.

6. Google, through May 2026

Google continued rolling reductions across Cloud and cybersecurity operations while investing heavily in AI. The company used reorganizations, performance reviews, and voluntary separation programs instead of announcing one comprehensive number.

For readers finding the story through Google News, this is an important reminder. A visible layoff event can be only one part of a longer staffing reset.

7. Intuit, May 2026

Intuit announced plans to eliminate roughly 3,000 jobs, representing about 17% of its workforce. Management described the move as a simplification that would redirect resources toward AI-based products.

Like Monday.com, Intuit framed the reduction as a change in organizational design. The company was not merely removing one automated function.

8. Meta, May 2026

Meta reduced its workforce while moving thousands of employees toward AI-focused assignments. Leadership argued that competition in AI required different skills, priorities, and execution speed.

Meta illustrates the reallocation pattern clearly. Jobs can disappear in one division while hiring or transfers continue elsewhere inside the same company.

9. Cisco, May 2026

Cisco announced cuts affecting nearly 4,000 positions, or approximately 5% of its workforce. Its finance leadership said the restructuring concerned resource alignment around silicon, optics, security, and AI rather than savings alone.

That explanation combines several priorities. AI was a stated factor, but not an isolated cause that explains every affected role.

10. General Motors, May 2026

General Motors eliminated between 500 and 600 jobs, primarily in information technology. Reporting indicated that AI contributed to the decision, although it was not the only reason.

GM continued advertising technology openings, including positions related to AI and autonomous vehicles. Its case again shows simultaneous layoffs and targeted recruitment.

11. Cloudflare, May 2026

Cloudflare cut approximately 1,100 employees, or 20% of its workforce, after reporting strong revenue growth. The company said rapidly increasing internal AI use had changed which roles it needed.

Cloudflare's leaders described major productivity gains among employees using agents. Yet those claims came from management and were not independently verified across every team.

The company expects to keep hiring. Its leaders have even said headcount could later exceed its 2026 peak, reinforcing that AI-related layoffs do not always produce permanent workforce contraction.

12. Coinbase, May 2026

Coinbase announced a reduction of roughly 700 employees, representing about 14% of its staff. It connected the plan to market conditions, flatter management, and increased use of AI.

Management also discussed smaller multidisciplinary groups that combine engineering, design, and product responsibilities. That model places broader demands on each remaining employee.

13. PayPal, May 2026

PayPal outlined a multiyear plan that could remove more than 4,500 positions, or around 20% of its workforce. Leadership described AI adoption and organizational simplification as central to the turnaround.

The company expects AI to influence software development, customer service, support operations, and risk management. Those are broad ambitions rather than evidence that every affected workflow already runs autonomously.

14. Snap, April 2026

Snap reduced its workforce by about 1,000 employees, or roughly 16%, and closed hundreds of open roles. CEO Evan Spiegel said AI advancements helped teams reduce repetitive work and increase execution speed.

Snap pointed to smaller teams working on subscriptions, advertising, and infrastructure. The claimed benefit came from changing team output, not only replacing isolated tasks.

15. IBM, through April 2026

IBM continued workforce reductions across selected operations while expanding recruitment for entry-level AI and hybrid-cloud roles. Reports also described the use of AI agents for some human-resources work.

IBM's changes illustrate occupational churn. The company can remove administrative work while increasing demand for employees who build, sell, or operate AI systems.

16. Atlassian, March 2026

Atlassian cut about 1,600 jobs, representing approximately 10% of its workforce. It said the company needed to rebalance toward AI and enterprise sales.

CEO Mike Cannon-Brookes rejected the slogan that AI simply replaces people. He also acknowledged that AI changes the skills and number of roles required in parts of the business.

17. Block, February 2026

Block announced approximately 4,000 layoffs, or about 40% of its workforce. CEO Jack Dorsey argued that smaller teams using AI could work faster with fewer organizational layers.

The scale made Block one of the year's most consequential cases. Contemporary reporting also noted that broader corporate evidence did not yet support an economy-wide AI employment collapse.

18. eBay, February 2026

eBay announced a reduction affecting around 800 roles, or approximately 6% of its workforce. Its plan arrived alongside wider pressure on technology companies to simplify operations and increase AI investment.

AI formed part of the strategic context, although eBay's case contained fewer public details connecting specific automation to specific eliminated work.

19. Amazon, January 2026

Amazon cut about 16,000 corporate jobs following a previous round affecting 14,000 positions. Management emphasized fewer layers, greater ownership, and reduced bureaucracy.

CEO Andy Jassy had previously said generative AI would reduce Amazon's corporate workforce over time. However, the company also said earlier cuts were not directly driven by AI.

The January announcement therefore belongs in the list with a qualification. AI influenced Amazon's longer-term workforce expectations, while pandemic hiring and management structure also shaped its reductions.

20. Pinterest, January 2026

Pinterest announced plans to eliminate less than 15% of its workforce. The company was redirecting resources toward AI-supported products and advertising capabilities.

Pinterest's situation reflects the commercial pressure facing consumer platforms. They must fund new recommendation and advertising systems while defending growth and controlling payroll.

21. Dell, disclosed in 2026

Dell's workforce declined by roughly 11,000 employees during its fiscal year, a reduction of about 10%. The company made the cuts while forecasting strong demand for servers optimized for AI workloads.

Dell demonstrates another version of the reversal. AI can increase demand for a company's hardware while contributing to internal pressure for a leaner workforce.

These examples belong to one trend, but they are not interchangeable. Some companies reported direct automation, while others cited capital allocation, flatter management, changing skills, or rising infrastructure demands.

The Real Conflict Is AI Investment Versus AI Replacement

The strongest common thread is not proven job replacement, but a transfer of spending from existing organizations into an expensive AI race.

Technology executives increasingly describe their companies as too slow for the agent era. They want fewer approval layers, smaller teams, and employees who can use AI across several functions.

That narrative offers a neat explanation for layoffs. It also helps management present reductions as preparation for growth instead of a retreat from earlier hiring decisions.

However, recent headcount data complicates the story. Amazon, Google, and Meta collectively employed roughly as many people in early 2026 as during the 2022 hiring surge, according to company disclosures analyzed by The Washington Post.

The largest technology groups also planned more than $700 billion in mostly AI-related capital projects during 2026. Those projects include computing equipment, data centers, networking, and energy capacity.

A critical workforce analysis argued that AI might influence layoffs through its cost rather than its automation. Companies under pressure to fund infrastructure can seek savings elsewhere before models eliminate entire occupations.

Monday.com's plan fits both explanations. Management expects agents to change how work happens, but the company is also financing a product transition in a fiercely contested market.

Its competitors include Asana, Atlassian, Microsoft, and ServiceNow. Each company is adding agents to established workflows, while larger platforms bring existing identity, security, and procurement relationships.

Monday.com therefore faces pressure from two directions. It must prove that agents create more value than conventional task automation while defending accounts against vendors with broader enterprise reach.

The company believes its structured boards, permissions, and workflows give agents a reliable environment for action. That may be an advantage over agents limited to documents and chat histories.

Yet some of Monday.com's agent capabilities have progressed through staged releases. Enterprise customers still need evidence that autonomous actions remain accurate, governed, and recoverable at scale.

The layoffs increase the stakes of that product test. Monday.com has reduced the organization before demonstrating that the new operating model can consistently deliver better customer outcomes.

Workers face a related test. Employers increasingly expect one person to supervise tools, interpret output, coordinate decisions, and cover work previously distributed across specialized roles.

That can improve productivity when tasks are well defined. It can also create hidden workload if employees must constantly check unreliable outputs or repair automated actions.

The distinction matters for anyone building a searchable knowledge base. AI systems need current, accessible, and well-structured information before they can safely act inside real workflows.

Cutting staff before those foundations exist can transfer costs rather than remove them. Delays may reappear as support queues, security reviews, implementation work, or employee burnout.

What the Layoff Numbers Do Not Prove

A company citing AI during layoffs does not establish that AI performed the eliminated jobs or improved the business afterward.

Corporate announcements rarely provide enough detail for a clean causal judgment. They usually combine automation, strategic priorities, skill changes, market conditions, and management simplification.

Monday.com explicitly says the move is not about asking fewer people to complete the same work. Management says the company will stop selected activities and give remaining teams more authority.

That promise can be tested only after the restructuring. Investors and customers should watch whether projects actually disappear, rather than quietly moving onto smaller teams.

Support quality is an early indicator. Enterprise software customers rely on account knowledge, escalation paths, implementation guidance, and rapid responses during failures.

If those services weaken, AI-generated efficiency may look better in financial statements than in customer operations. Experienced employees often hold contextual knowledge that is difficult to encode before departure.

Roadmap consistency is another indicator. Monday.com must continue developing its core work-management product while adding agents, governance, connectors, and implementation services.

A sharp focus can accelerate those priorities. A 20% reduction can also create dependencies, abandoned projects, and slower execution while teams rebuild responsibilities.

Employee retention matters as well. Large layoffs can prompt voluntary departures among people whose skills remain essential, especially when competitors are recruiting for similar AI roles.

There is also a measurement problem. Executives often cite output speed, code generation, or fewer meetings, but those measures do not automatically reflect reliability or customer value.

An agent that drafts work quickly still needs oversight. A coding assistant that produces more code can increase review, security, and maintenance demands.

Cloudflare offered unusually specific claims about internal adoption. It said AI use rose more than 600% over three months and described employees becoming several times more productive.

Those figures are striking, but the company did not publish an independent team-level evaluation. Its operating explanation remains a management account of a restructuring decision.

The wider labor-market evidence also remains mixed. Individual technology layoffs attract attention because the companies involved are prominent and profitable.

They do not establish that AI has reduced total employment across the economy. Some affected employers continue hiring, and AI infrastructure investment creates demand in engineering, construction, energy, operations, and sales.

The most defensible conclusion is narrower. AI has changed what executives believe an efficient technology company should look like, and that belief is already affecting employment decisions.

Whether those decisions produce lasting gains remains unsettled.

Why Software Workers and Buyers Should Care

The immediate risk is not that every knowledge job disappears, but that companies reset performance expectations faster than their systems mature.

Developers will face growing pressure to use assistants across coding, testing, documentation, and incident response. Employers may treat shorter task cycles as evidence that smaller engineering teams can handle the same roadmap.

Product managers may oversee wider scopes because agents can draft requirements, analyze feedback, and summarize meetings. Yet they remain responsible for prioritization, context, and the consequences of wrong decisions.

Customer-success teams face direct exposure because support work contains repetitive requests. Companies can automate triage and common answers before they can automate complex account relationships.

Design, marketing, finance, legal, and human-resources teams face similar task-level changes. AI can produce first drafts quickly, while accountability stays with employees.

This creates a new form of operational risk. A company can reduce headcount based on expected capability before it measures accuracy, adoption, or the cost of human review.

Workers should document where AI saves time and where it creates rework. That evidence helps separate real productivity from impressive demonstrations.

Teams should also preserve decision context when colleagues leave. Meeting records, customer history, technical reasoning, and project tradeoffs become more valuable when organizational memory shrinks.

A practical AI workflow can reduce repetitive synthesis. It cannot decide which business commitments should survive a restructuring.

Enterprise buyers should evaluate vendor layoffs as an operating signal, not only a financial headline. They should ask who owns their account, how escalations work, and whether implementation resources have changed.

They should also request clear controls for agent permissions, audit history, consumption, and rollback. An autonomous workflow needs safeguards because a fast incorrect action can create more damage than a slow manual process.

Buyers should avoid assuming that a leaner vendor is automatically weaker. Smaller teams can execute well when products, responsibilities, and customer segments are sharply defined.

They should also avoid assuming that AI guarantees continuity. Reduced headcount can expose gaps that appear only during migrations, outages, security reviews, or complex implementations.

The Google News pattern is therefore useful as a warning, not a verdict. It shows which companies have attached AI to workforce decisions, but it cannot establish the quality of those decisions.

What to Watch After the Google News Headlines

The next evidence will come from customer service, product adoption, and the direction of hiring, not another executive memo about efficiency.

First, watch Monday.com's service continuity through the second half of 2026. Response times, account-team changes, unresolved incidents, and implementation delays will reveal whether the company removed friction or essential capacity.

Stable service would support management's argument that the earlier organization contained unnecessary layers. Deteriorating service would suggest that savings arrived before the new model was ready.

Second, watch adoption of Monday.com's agents and AI-based builder. The company needs to report meaningful usage, retention, and expansion beyond initial product interest.

Customer adoption would strengthen the case that Monday.com is becoming a platform where software completes work. Weak adoption would leave a painful restructuring attached to an uncertain product transition.

Third, watch where Monday.com and the other 20 employers hire next. Job listings can reveal whether companies are permanently shrinking or replacing broad functions with specialized AI, infrastructure, sales, and implementation roles.

A return to headcount growth would not make the layoffs irrelevant. It would show that AI drove workforce reallocation more clearly than absolute elimination.

Readers should apply the same test whenever another layoff reaches Google News. Ask what work stopped, what work moved, and what evidence supports the claimed productivity gain.

The headline number describes the human impact immediately. The next several months will show whether these companies designed better organizations or simply gave an old cost-cutting cycle a new AI label.