AI Washing Or Layoff Warning? How Employees Might Be Paying The Price For Corporate Cost Cutting

Last Updated:March 06, 2026, 08:10 IST

AI washing is when firms claim to use advanced AI but rely on basic automation, exaggerate results, or present tools as fully working when they are limited or not truly deployed.

According to global outplacement firm Challenger, Gray & Christmas, technology companies announced 49,795 job cuts through 2025, with artificial intelligence frequently cited as a driver of “workforce optimisation”. (Image: Canva)

When companies announce they are going AI-first, it rarely sounds like a warning. The official email is polished and forward-looking, framed as progress, competitiveness and inevitability in an era defined by rapid advances in artificial intelligence. Yet beneath the rhetoric, a quieter reality that is increasing becoming a corporate phenomenon- AI Washing.

In February 2026, Sam Altman, CEO of OpenAI, publicly acknowledged what many employees had begun to suspect, noting that some firms are “blaming AI for layoffs that they would otherwise do”. InCruiter CEO, Anil Agarwal agrees and does not mince words while telling News18, “In today’s environment, it’s often a defensive move to stay relevant to investors. True AI creates transformative workflows; AI washing just adds a digital facelift to basic automation or simple algorithms.”

Across 2025 and into 2026, that script has become familiar. According to global outplacement firm Challenger, Gray & Christmas, technology companies announced 49,795 job cuts through 2025, with artificial intelligence frequently cited as a driver of “workforce optimisation”. At the same time, PwC’s 2025 Global AI Jobs Barometer found that while AI adoption is accelerating, productivity gains are uneven and many firms remain in early deployment stages. What this really means is that the language of AI is racing ahead of the infrastructure needed to support it.

More recently, a Bengaluru-based home interiors platform, laid off around 1,000 employees, describing a shift towards becoming “AI-native”, even as it faced funding constraints and mounting losses. The move ignited debate within India’s start-up ecosystem, was this genuine reinvention, or a reframing of financial strain?

What Is AI Washing?

AI washing describes the practice of overstating or misrepresenting the use of artificial intelligence to appear more advanced than reality. In some cases, companies label routine automation or basic data processing as AI. In others, they exaggerate how effective their systems are compared with existing methods, or imply that AI tools are fully deployed and delivering results when they are still experimental, limited or not operational at scale.

“AI washing is essentially the ‘greenwashing’ of the tech world. It’s when companies sprinkle ‘AI-powered’ into their marketing or annual reports to inflate brand value without having any substantive machine learning under the hood. It’s misleading because it creates a gap between shareholder expectations and the actual technical capabilities of the workforce,” says Agarwal.

Growth Strategy Vs Cost-Control: What Does ‘Going AI’ Mean?

In a tighter capital environment, the distinction matters. Venture funding across Asia softened through 2025 compared with pandemic highs, and many late-stage firms are under pressure to show a credible path to profitability.

Agarwal observes, “In a lean market, AI is frequently being utilized as a ‘cost-control’ lever disguised as innovation. While profitable firms use AI to scale and find new revenue, struggling ones often use ‘AI integration’ as a narrative to justify headcount reductions and bridge budget gaps. We’re seeing a shift where ‘Going AI’ becomes a euphemism for streamlining operations. However, the smartest firms realize that using AI solely to cut costs is a short-term win; true growth comes from using it to augment human talent, not just replace it.”

Madhu Rajputra Peravalli, Co-founder and CEO of Troogue, is even more direct. “Lets call spade a spade. It’s not really a technology decision always. It’s a cost decision driven by survival economics. When margins are squeezed, the boardroom doesn’t say fire people, they say lets automate and improve productivity. Same result, different optics.”

He continues, “Real AI adoption needs investment in infrastructure, in people, in change. Financially strained companies don’t have the appetite for that. What they actually do is automate one visible process, issue a press release about ‘going AI-first,’ and quietly reduce headcount.”

From his vantage point, the pattern is visible. “I see this from the other side every day. Enterprises gutting internal teams and then urgently hiring AI-skilled contractors externally because they’ve announced a transformation they can’t actually execute. The decision to automate, in most stressed companies, isn’t about building capability. It’s about buying time with investors and the board. AI just happens to be the most credible-sounding cover story available right now.”

How Does the ‘AI as Replacement’ Narrative Affect Employees?

Gallup’s 2025 workplace data shows that employee engagement dips sharply during restructuring cycles, particularly where communication lacks clarity. Add automation anxiety to the mix, and the impact deepens.

Agarwal warns, “Automation anxiety creates a ‘survival mode’ culture that can stifle the very creativity companies need to recover. When employees view AI as a competitor rather than a collaborator, morale plummets and trust in leadership erodes. This uncertainty leads to burnout and a ‘knowledge hoarding’ mentality, where people fear sharing expertise. To fix this, leaders must be transparent. I believe the goal is ‘Human-plus-AI.’ If you don’t manage the psychological transition, you’ll end up with a high-tech office filled with disengaged, fearful people.”

Peravalli echoes that concern by adding, “The damage is detrimental not just for the employees but even for organisations. When leadership frames AI as a replacement, your best people start updating their LinkedIn profiles. Not the average performers. Because they have options. What’s left? A workforce that should have either been reskilled or a misfit to the current role.”

He adds a cautionary note, “Here’s the irony, the people most capable of making AI work inside an organisation are precisely the ones who leave when they feel threatened by the narrative. You end up with the technology and none of the human intelligence to run it. In India especially, a job isn’t just a paycheck. It’s the EMI, the family, the social identity. Smart companies are saying: AI amplifies you. Not replaces you. That’s not just better communication. It’s actually the truth if you’re willing to learn. Now companies say that and let go people, that circles back to point 1.”

Which Job Roles Are Most at Risk?

The World Economic Forum’s 2025 Future of Jobs update suggests that routine cognitive tasks face the highest displacement risk, even as demand grows for analytical and human-centred skills.

Peravalli is specific. “Every mundane, repetitive tasks like Report generation, rule-based decisions, Information relay, basic QA, template coding and tasks similar are at risk. Anything where the job is essentially ‘follow steps A to B to C’ is under pressure. Most middle management in large IT service organizations in India survived with excel and ppt skills, now that’s under pressure. In tech specifically and I deal with this daily. Junior manual testers, basic data analysts, entry-level developers doing repetitive work. These roles are already feeling the stress.”

But he stresses it is not confined to entry level. “But here’s what most people miss: it’s not just the bottom of the pyramid. Middle managers whose only job is to gather updates and present them upward? Equally exposed. AI does that faster and without the politics. What survives? Judgment under ambiguity, domain experience, he ability to read a room, navigate a client, build trust. Things you can’t prompt-engineer your way to.”

“The honest reality: our education system is still manufacturing people optimised for exactly the skills being automated. That’s the real crisis not AI itself, but the lag between what we’re training people for and what the market actually needs now.”

When Is ‘AI-Driven Restructuring’ In A Firm a Red Flag?

“Sad reality but yes. And the market is getting smarter at spotting it. Here’s a simple test, when a company announces AI-driven restructuring, lets dig into where’s the AI investment? Where’s the reskilling budget? Where’s the 12- 18 month capability roadmap? If there’s no answer, it’s not an AI strategy. It’s a balance sheet problem trying to get swept under the carpet,” Peravalli puts it bluntly.

He names the phenomenon directly, “Not of products but of people decisions. The layoff was always going to happen. The insane hiring, unplanned adding of fat post covid and the inflated valuations was always going to get under stress. AI just made it easier to announce while saving the value.”

The long-term consequences, he argues, are reputational, “These companies will struggle to hire real AI talent tomorrow because skilled people can read the pattern. They know the difference between an organisation genuinely building something and one that used ‘AI-first’ as a euphemism for ‘we’re in trouble.’ We’re already seeing candidates ask pointed questions about a company’s actual AI roadmap before they accept a job offer. The workforce isn’t naive, they have seen this movie before just with different technology as the villain.”

For employees and investors alike, the question is no longer whether a company is going AI first. It is whether the strategy is building capability or merely buying time. In 2026, the difference is becoming easier to spot.

Across 2025 and into 2026, that script has become familiar. According to global outplacement firm Challenger, Gray & Christmas, technology companies announced 49,795 job cuts through 2025, with artificial intelligence frequently cited as a driver of “workforce optimisation”. At the same time, PwC’s 2025 Global AI Jobs Barometer found that while AI adoption is accelerating, productivity gains are uneven and many firms remain in early deployment stages. What this really means is that the language of AI is racing ahead of the infrastructure needed to support it.

More recently, a Bengaluru-based home interiors platform, laid off around 1,000 employees, describing a shift towards becoming “AI-native”, even as it faced funding constraints and mounting losses. The move ignited debate within India’s start-up ecosystem, was this genuine reinvention, or a reframing of financial strain?

What Is AI Washing?

AI washing describes the practice of overstating or misrepresenting the use of artificial intelligence to appear more advanced than reality. In some cases, companies label routine automation or basic data processing as AI. In others, they exaggerate how effective their systems are compared with existing methods, or imply that AI tools are fully deployed and delivering results when they are still experimental, limited or not operational at scale.

“AI washing is essentially the ‘greenwashing’ of the tech world. It’s when companies sprinkle ‘AI-powered’ into their marketing or annual reports to inflate brand value without having any substantive machine learning under the hood. It’s misleading because it creates a gap between shareholder expectations and the actual technical capabilities of the workforce,” says Agarwal.

Growth Strategy Vs Cost-Control: What Does ‘Going AI’ Mean?

In a tighter capital environment, the distinction matters. Venture funding across Asia softened through 2025 compared with pandemic highs, and many late-stage firms are under pressure to show a credible path to profitability.

Agarwal observes, “In a lean market, AI is frequently being utilized as a ‘cost-control’ lever disguised as innovation. While profitable firms use AI to scale and find new revenue, struggling ones often use ‘AI integration’ as a narrative to justify headcount reductions and bridge budget gaps. We’re seeing a shift where ‘Going AI’ becomes a euphemism for streamlining operations. However, the smartest firms realize that using AI solely to cut costs is a short-term win; true growth comes from using it to augment human talent, not just replace it.”

Madhu Rajputra Peravalli, Co-founder and CEO of Troogue, is even more direct. “Lets call spade a spade. It’s not really a technology decision always. It’s a cost decision driven by survival economics. When margins are squeezed, the boardroom doesn’t say fire people, they say lets automate and improve productivity. Same result, different optics.”

He continues, “Real AI adoption needs investment in infrastructure, in people, in change. Financially strained companies don’t have the appetite for that. What they actually do is automate one visible process, issue a press release about ‘going AI-first,’ and quietly reduce headcount.”

From his vantage point, the pattern is visible. “I see this from the other side every day. Enterprises gutting internal teams and then urgently hiring AI-skilled contractors externally because they’ve announced a transformation they can’t actually execute. The decision to automate, in most stressed companies, isn’t about building capability. It’s about buying time with investors and the board. AI just happens to be the most credible-sounding cover story available right now.”

How Does the ‘AI as Replacement’ Narrative Affect Employees?

Gallup’s 2025 workplace data shows that employee engagement dips sharply during restructuring cycles, particularly where communication lacks clarity. Add automation anxiety to the mix, and the impact deepens.

Agarwal warns, “Automation anxiety creates a ‘survival mode’ culture that can stifle the very creativity companies need to recover. When employees view AI as a competitor rather than a collaborator, morale plummets and trust in leadership erodes. This uncertainty leads to burnout and a ‘knowledge hoarding’ mentality, where people fear sharing expertise. To fix this, leaders must be transparent. I believe the goal is ‘Human-plus-AI.’ If you don’t manage the psychological transition, you’ll end up with a high-tech office filled with disengaged, fearful people.”

Peravalli echoes that concern by adding, “The damage is detrimental not just for the employees but even for organisations. When leadership frames AI as a replacement, your best people start updating their LinkedIn profiles. Not the average performers. Because they have options. What’s left? A workforce that should have either been reskilled or a misfit to the current role.”

He adds a cautionary note, “Here’s the irony, the people most capable of making AI work inside an organisation are precisely the ones who leave when they feel threatened by the narrative. You end up with the technology and none of the human intelligence to run it. In India especially, a job isn’t just a paycheck. It’s the EMI, the family, the social identity. Smart companies are saying: AI amplifies you. Not replaces you. That’s not just better communication. It’s actually the truth if you’re willing to learn. Now companies say that and let go people, that circles back to point 1.”

Which Job Roles Are Most at Risk?

The World Economic Forum’s 2025 Future of Jobs update suggests that routine cognitive tasks face the highest displacement risk, even as demand grows for analytical and human-centred skills.

Peravalli is specific. “Every mundane, repetitive tasks like Report generation, rule-based decisions, Information relay, basic QA, template coding and tasks similar are at risk. Anything where the job is essentially ‘follow steps A to B to C’ is under pressure. Most middle management in large IT service organizations in India survived with excel and ppt skills, now that’s under pressure. In tech specifically and I deal with this daily. Junior manual testers, basic data analysts, entry-level developers doing repetitive work. These roles are already feeling the stress.”

But he stresses it is not confined to entry level. “But here’s what most people miss: it’s not just the bottom of the pyramid. Middle managers whose only job is to gather updates and present them upward? Equally exposed. AI does that faster and without the politics. What survives? Judgment under ambiguity, domain experience, he ability to read a room, navigate a client, build trust. Things you can’t prompt-engineer your way to.”

“The honest reality: our education system is still manufacturing people optimised for exactly the skills being automated. That’s the real crisis not AI itself, but the lag between what we’re training people for and what the market actually needs now.”

When Is ‘AI-Driven Restructuring’ In A Firm a Red Flag?

“Sad reality but yes. And the market is getting smarter at spotting it. Here’s a simple test, when a company announces AI-driven restructuring, lets dig into where’s the AI investment? Where’s the reskilling budget? Where’s the 12- 18 month capability roadmap? If there’s no answer, it’s not an AI strategy. It’s a balance sheet problem trying to get swept under the carpet,” Peravalli puts it bluntly.

He names the phenomenon directly, “Not of products but of people decisions. The layoff was always going to happen. The insane hiring, unplanned adding of fat post covid and the inflated valuations was always going to get under stress. AI just made it easier to announce while saving the value.”

The long-term consequences, he argues, are reputational, “These companies will struggle to hire real AI talent tomorrow because skilled people can read the pattern. They know the difference between an organisation genuinely building something and one that used ‘AI-first’ as a euphemism for ‘we’re in trouble.’ We’re already seeing candidates ask pointed questions about a company’s actual AI roadmap before they accept a job offer. The workforce isn’t naive, they have seen this movie before just with different technology as the villain.”

For employees and investors alike, the question is no longer whether a company is going AI first. It is whether the strategy is building capability or merely buying time. In 2026, the difference is becoming easier to spot.

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