Why Worker Confidence Is Cratering as CEOs Plan AI Layoffs in 2026

Worker confidence is cratering in 2026 because the people who run companies and the people who staff them are now reading the same situation in two very different ways. According to Mercer's Global Talent Trends 2026 report, which surveyed 825 C-suite leaders and 1,650 HR leaders, 99 percent of CEOs expect AI-driven layoffs within the next two years, even as the share of employees who say they are thriving at work has fallen from 66 percent in 2024 to just 44 percent in 2026. That gap between executive intent and employee security is the engine behind the collapse in morale. At Metaintro, we track how the labor market is shifting so you can see these signals early and act before they reach your desk.

Why Is Worker Confidence Falling So Sharply in 2026?

The headline number is hard to ignore. In 2024, two out of three employees told Mercer they were thriving at work. By 2026, fewer than half said the same, a drop from 66 percent to 44 percent in just two years. A 22-point slide of that size does not usually come from a single cause. It comes from an accumulation of pressure that builds quietly and then breaks all at once.

The biggest source of that pressure is the question of whether a person's job will still exist. Mercer found that employee concern about losing a job to AI rose from 28 percent in 2024 to 40 percent in 2026. That means the share of workers actively worried about automation grew by roughly 12 points in the same window that thriving collapsed. The two trends move together for an obvious reason: it is very difficult to feel like you are flourishing in a role when you suspect that role may be automated out from under you.

Confidence is also a function of trust, and trust erodes when employees sense that decisions about their future are being made above them without much input. When 99 percent of CEOs anticipate AI-driven cuts, that intent rarely stays secret. It shows up in hiring freezes, in reorganizations, in quiet messaging about "doing more with less." Workers read those signals fluently. They do not need a memo to understand that the ground is shifting, and the uncertainty itself becomes corrosive long before any actual layoff occurs.

Finally, confidence depends on whether people believe their employer has a credible plan. That is where the picture gets bleakest. Only 32 percent of executives believe their own companies can effectively combine human labor with AI systems. When fewer than a third of leaders are confident in their own integration strategy, employees are left to absorb the consequences of a transition that even the people directing it admit they have not figured out. For more on how that uncertainty plays out, our look at why a confused AI rollout is hurting companies and staff traces the same fault line.

What Does Mercer's Data Reveal About the CEO Layoff Plans?

The most striking figure in the report is the near-unanimity among chief executives. Ninety-nine percent of CEOs expect AI-driven layoffs within the next two years. Numbers that close to total are rare in survey research, and they tell you something important: the question is no longer whether AI will reshape headcount, but how fast and how deep.

It is worth being precise about what that 99 percent does and does not mean. It is a measure of expectation, not a guarantee of scale. CEOs are saying they anticipate some level of AI-driven workforce reduction, not that they will eliminate a fixed percentage of staff. The expectation can still be enormously consequential even if the eventual cuts are uneven, because expectation shapes budgets, hiring plans, and investment decisions today. A company that believes AI will let it run leaner will start behaving that way well in advance.

Mercer's survey weight comes from its scope. The findings draw on 825 C-suite leaders and 1,650 HR leaders, a sample large enough to capture how the people setting strategy and the people implementing it are thinking in parallel. That dual perspective matters, because HR leaders are the ones who translate executive intent into actual workforce decisions, and their alignment with the C-suite tells you how likely those layoff expectations are to become reality.

There is also a regional wrinkle worth flagging carefully. In a Bloomberg discussion of the report, a Mercer leader noted that most Australian firms expect AI to cut up to 20 percent of jobs within two years. That 20 percent figure is specific to Australia and should not be read as a global number. It is a useful illustration of how aggressive some markets expect the cuts to be, but it is a local data point, not a worldwide forecast. The broader, defensible takeaway is simpler: across the executives Mercer surveyed, the expectation of AI-driven reductions is essentially universal, while the magnitude varies by country and sector.

Who Is Most Exposed to AI-Driven Job Cuts?

Not everyone faces the same risk, and the report is clear about where the exposure concentrates. Entry-level and junior workers are widely cited as facing the biggest hit. The logic is uncomfortable but straightforward: the tasks most readily automated tend to be the structured, repeatable, learn-the-ropes work that traditionally fell to people early in their careers.

This is a meaningful shift in how the career ladder works. For decades, junior roles served two purposes at once. They got necessary work done, and they functioned as training grounds where new workers built judgment, context, and relationships. When AI absorbs the routine portion of that work, the first rung of the ladder gets thinner, and the path from entry-level to mid-career grows harder to climb. Our coverage of the looming 2026 crisis for entry-level work and job seekers digs deeper into how this squeeze is forming.

The exposure is not limited to the most junior tier, though. Anyone whose role is dominated by predictable, rules-based tasks sits closer to the automation line than someone whose work hinges on judgment, relationship-building, or navigating ambiguity. That distinction is becoming one of the most important variables in career security. The Federal Reserve has even warned that AI job costs may hit faster than the benefits, which is precisely the timing problem that makes the entry-level squeeze so acute.

It is also important to hold two ideas at once. The same forces cutting some roles are creating others. There is a credible case that AI will create more engineering jobs, not fewer, as automation raises the value of the people who can build, direct, and supervise these systems. Exposure is real, but it is unevenly distributed, and the workers who understand where they sit on that map are in a far stronger position than those who assume the risk is uniform.

Why Is There Such a Gap Between Executive Plans and Worker Reality?

The most revealing tension in Mercer's data is not any single statistic but the distance between two of them. On one side, 99 percent of CEOs expect AI-driven layoffs. On the other, only 32 percent of executives believe their companies can effectively combine human labor with AI systems. In other words, almost every leader plans to cut, while only about a third are confident they can actually make the human-plus-AI model work.

That gap explains a great deal of the anxiety on the ground. When leaders are sure about the cuts but unsure about the integration, the cuts tend to arrive first and the integration gets figured out afterward, often messily. Employees experience that sequence as instability: roles disappear before any clear new structure replaces them, and the people who remain are left to absorb the workload and the uncertainty at the same time.

It also raises a fair question about whether AI is the real reason or a convenient explanation. Some leaders may be using automation as cover for cost-cutting decisions they would have made anyway, a dynamic explored in our piece on why one tech CEO calls AI a scapegoat for 2026 layoffs. Whether the motivation is genuine transformation or simple cost discipline, the effect on worker confidence is the same: people stop believing that effort and performance reliably protect them.

There is a more constructive path, and some leaders are taking it. Nearly half of CEOs say they plan to retrain workers rather than simply replace them, a stance we cover in our report on why nearly half of CEOs plan to retrain workers for AI. Retraining will not erase the disruption, but it signals that the executive-worker gap is not destiny. Where leaders invest in the transition rather than just announcing the cuts, the confidence damage is far less severe. Even at the top, the message is muddled. The Wells Fargo CEO has said the AI effect on jobs is complicated, which is itself a kind of honesty that workers rarely hear.

How Can Workers Rebuild Confidence and Protect Their Careers?

The data is sobering, but it is not a verdict on any individual career. The same report that documents the confidence collapse also points toward where the leverage sits, and most of it is within reach for workers who decide to act early rather than wait for clarity that may never come.

The first move is to understand your own exposure honestly. If your role is heavy on structured, repeatable tasks, the automation risk is higher and the case for adapting is more urgent. If your work depends on judgment, relationships, or handling ambiguity, you have more durable ground to build on. Either way, the goal is to shift the balance of your day toward the parts of the job that are hardest to automate and to make those contributions visible to the people who decide on headcount.

The second move is to treat AI as a tool to master rather than a threat to dread. Workers who can direct, supervise, and improve AI systems become more valuable as those systems spread, not less. The fear documented in Mercer's data is rational, but fear and fatalism are not the same thing. It is entirely possible to be clear-eyed about the risk and still position yourself on the right side of it, a framing we lay out in why AI does not have to mean layoffs for your job.

The third move is to protect your own well-being while you adapt, because chronic uncertainty takes a real toll. The pressure to constantly prove your value can tip into exhaustion, and burned-out workers make worse career decisions, not better ones. Our look at the high-achiever habits that lead to burnout is a useful reminder that resilience is part of the strategy, not separate from it.

It also helps to keep the macro picture in perspective. For all the layoff anxiety, the broader labor market is not in freefall. Recent data shows US jobless claims ticking up while layoffs stay near historic lows, a reminder that the AI narrative and the actual hiring environment are not always the same story. Confidence is partly informational. The workers who stay closest to real signals, rather than headlines, tend to make calmer and better decisions.

People Also Asked

Q: How many CEOs expect AI-driven layoffs in 2026?

A: According to Mercer's Global Talent Trends 2026 report, 99 percent of CEOs expect AI-driven layoffs within the next two years. The report draws on a survey of 825 C-suite leaders and 1,650 HR leaders, so the near-unanimous figure reflects a broad sample of senior decision-makers rather than a narrow slice. It is a measure of expectation rather than a fixed promise of how deep the cuts will go, but expectations of that scale tend to shape budgets and hiring well before any layoff is announced.

Q: Why has employee confidence dropped so much?

A: Mercer found that the share of employees who say they are thriving at work fell from 66 percent in 2024 to 44 percent in 2026. The decline tracks closely with rising automation fear: concern about losing a job to AI climbed from 28 percent to 40 percent over the same period. Confidence also suffers because only 32 percent of executives believe their companies can effectively combine human labor with AI, leaving workers to absorb the uncertainty of a transition that leaders themselves admit they have not fully solved.

Q: Which workers are most at risk from AI automation?

A: The report points to entry-level and junior workers as facing the biggest hit, because the structured, repeatable tasks that often fill early-career roles are the easiest for AI to absorb. Risk is not limited to that tier, though. Any role dominated by predictable, rules-based work sits closer to the automation line than work that depends on judgment, relationships, or handling ambiguity. Understanding where your own role falls on that spectrum is one of the most useful steps you can take to protect your career.

Related Articles

• Why AI Does Not Have to Mean Layoffs for Your Job
• Fed Warns AI Job Costs May Hit Faster Than Benefits
• The Looming 2026 Crisis for Entry-Level Work and Job Seekers
• High-Achiever Habits That Lead to Burnout
• Why One Tech CEO Says AI Is a Scapegoat for 2026 Layoffs
• Why AI Will Create More Engineering Jobs, Not Fewer
• US Jobless Claims Tick Up as Layoffs Stay Near Historic Lows
• How a Confused AI Rollout Is Hurting Companies and Staff
• Why Nearly Half of CEOs Plan to Retrain Workers for AI
• Wells Fargo CEO Says AI Effect on Jobs Is Complicated

Future-proof your career by getting ahead of the shift instead of waiting for it to reach you. The Mercer data is a warning, but it is also a map: it shows exactly which skills, signals, and roles are gaining value as AI spreads, and which are losing it. Stay close to real labor-market data, build the parts of your work that are hardest to automate, and treat AI as a tool you direct rather than a force you fear. Create a free Metaintro account to track the trends shaping your industry and move first.