By ByteBot
Over 50,000 workers were told AI took their jobs in 2025. However, according to a January 2026 Forrester report, most companies don’t actually have mature AI systems ready to replace those workers. Moreover, the practice—dubbed “AI-washing”—exposes a troubling gap between corporate press releases and technical reality.
The Core Deception
Forrester Research found that “many companies announcing A.I.-related layoffs do not have mature, vetted A.I. applications ready to fill those roles.” In other words, companies are blaming AI for layoffs they can’t actually automate yet. Of the 244,851 global layoffs in 2025, nearly 70,000 (30%) cited AI as the reason. Nevertheless, the research tells a different story.
Molly Kinder, a senior research fellow at the Brookings Institute, cut through the noise: saying layoffs were caused by AI is “a very investor-friendly message,” especially when the alternative might mean admitting “the business is ailing.” That’s the game. Essentially, companies frame financial struggles and pandemic over-hiring corrections as AI transformation, and suddenly layoffs sound innovative instead of desperate.
Here’s the tell: if your AI systems were actually ready to replace workers, you’d deploy them first, prove the ROI, then announce workforce changes. Instead, companies announce layoffs and AI plans simultaneously—because the AI doesn’t exist yet. Furthermore, Forrester predicts half of these “AI-attributed layoffs” will be quietly reversed, with jobs returning offshore or at lower wages. When that happens, the lie becomes impossible to hide.
Expert Consensus on AI-Washing
Industry experts across banking, staffing, and research are calling out the AI-washing trend with remarkable unanimity.
Deutsche Bank analysts warned that companies attributing job cuts to AI should be taken “with a grain of salt”—”AI redundancy washing will be a significant feature of 2026.” Translation: expect more corporate dishonesty masquerading as innovation.
Sander van’t Noordende, CEO of Randstad (the world’s largest staffing firm), was even more direct: “Those 50,000 job losses are not driven by AI, but are just driven by the general uncertainty in the market. It’s too early to link those to AI.” When the global staffing leader says AI layoffs aren’t real, you should listen.
Meanwhile, Yale University’s Budget Lab analyzed U.S. labor market data from 2022-2025 and found AI hasn’t caused widespread job losses. The share of workers in different jobs hasn’t shifted significantly since ChatGPT’s debut. Additionally, Harvard Business Review titled their January 2026 analysis bluntly: “Companies Are Laying Off Workers Because of AI’s Potential—Not Its Performance.”
The verdict is in: companies are lying about AI to cover financial struggles.
How to Spot AI-Washing
AI-washing follows a predictable three-step pattern. Learn to recognize it.
First: Simultaneous announcement without prior AI deployment. Layoffs and “AI transformation” announced the same day. No track record of AI in affected departments. No timeline showing phased AI rollout followed by workforce optimization. Just press releases combining bad news with buzzwords.
Second: Vague claims lacking specifics. References to “AI efficiency” and “automation” with zero details. No explanation of which AI tools do what. No metrics on productivity gains. No deployment schedule. Just hand-waving about the future.
Third: Roles where AI can’t realistically work yet. Cutting jobs that require human judgment, creativity, or relationship management. Positions AI demos can’t even handle in controlled settings. Entry-level roles eliminated while claiming AI replaces senior expertise that doesn’t exist in any model.
Take Amazon. CEO Andy Jassy said 16,000 layoffs were “financially driven, not AI-related”—specifically about “culture” and reducing pandemic bloat. Yet Amazon has cut over 30,000 jobs since announcing AI-driven organizational changes. The contradiction isn’t subtle. It’s the pattern.
The Human Cost
Worker anxiety about AI job loss jumped from 28% in 2024 to 40% in 2026—a 43% increase in two years, according to Mercer’s Global Talent Trends survey of 12,000 people worldwide. Sixty percent of U.S. workers now believe AI will cut more jobs than it adds in 2026.
But here’s the problem: that anxiety is based on corporate lies, not technical reality. Developers are making career decisions based on press releases instead of deployment timelines. Consequently, Yale’s research shows no widespread AI job losses. The fear is real. The AI systems supposedly causing it are not.
What Developers Should Do
Don’t panic about AI taking your job. Question AI claims and demand proof.
When companies cite AI for layoffs, ask: “Show us the system.” Look for deployment evidence, not investor presentations. If AI was ready, why announce layoffs before demonstrating the technology works? The absence of proof is telling.
Understand AI’s current limitations. It automates routine tasks, not system design. Architecture decisions, cross-functional collaboration, business context, and code quality judgment still require humans. Therefore, entry-level roles writing boilerplate code face genuine pressure. Mid-career and senior developers building complex systems remain largely safe.
Focus on irreplaceable skills: system thinking, architectural trade-offs, domain expertise, and the ability to navigate ambiguity. These are the capabilities AI demos never show because they don’t exist in models yet.
Recognize the timeline. Real AI adoption is measured in years, not quarters. Current AI-washing will become obvious in 12-18 months when Forrester’s prediction comes true and those “AI-replaced” jobs quietly return. The companies lying today will face credibility crises tomorrow.
What’s Next
Deutsche Bank predicts “AI redundancy washing will be a significant feature of 2026.” Expect more companies to follow this playbook as it proves effective at protecting stock prices while cutting costs. However, credibility crises loom. As time passes without deployed AI systems, the lies become harder to maintain. Employees, journalists, and regulators will demand proof.
The gap between AI hype and implementation will eventually close—but the timeline is years, not months. Companies that lied about AI to justify layoffs will face questions when the systems never materialize. Or when those “replaced” jobs quietly return at lower wages, exposing the financial motivations that were there all along.
For now, skepticism is the right response. Don’t let corporate PR drive your career decisions. Demand evidence, not promises. And when companies blame AI for layoffs, remember: the world’s leading experts are telling you it’s not real.
