The new office divide is no longer remote versus in person or manager versus individual contributor. It is between people who treat AI as part of the job and people who still think it is optional.

A recent WRITER and Workplace Intelligence survey captured the mood with blunt candor: Many employers now say that workers who resist AI risk stalled advancement or worse. Out of 2,400 employees and C-suite leaders, 60 percent of companies say they plan to lay off employees who will not adopt AI; 77 percent of executives say AI resisters will be passed over for promotions; and 92 percent say they are actively cultivating an “AI elite” class of workers. Even more telling, 87 percent of executives say those employees are at least five times more productive than their peers.

AI is being recast as the new minimum standard for relevance. That sounds harsh because it is, but it also reflects a deeper shift. AI is moving from novelty to baseline, and careers are being repriced around that reality.

This is not happening because every company has cracked the code. Far from it. The World Economic Forum’s Future of Jobs Report 2025 says 39 percent of core job skills are expected to change by 2030, with technological change being the biggest driver. At the same time, McKinsey’s workplace AI research found that almost all companies are investing in AI, even though only 1 percent describe themselves as mature in how they use it.

That gap matters. Employers are demanding AI fluency before they have built stable systems, clear norms, or convincing workflows. So “use AI” becomes a vague command that often means “be faster, cheaper, and more adaptable.” Yet genuine AI fluency is not prompt theater. It is about knowing when to automate, when to verify, when to keep humans in the loop and when sensitive data should never touch a model in the first place.

The Anthropic Economic Index points to the real pattern: AI is spreading through work as a mix of augmentation and automation, not as a clean handoff from person to machine.

There is a reason executives sound impatient. In a widely cited National Bureau of Economic Research paper on generative AI in customer support, access to an AI assistant raised productivity by 14 percent on average and delivered even larger gains for less experienced workers. Those numbers are catnip for leadership teams under pressure to grow without hiring.

But that same evidence should make companies more careful, not more reckless.

AI produces gains where tasks are structured, feedback is quick, and performance is measurable. It does not magically fix bad management, muddled processes, or poor judgment. A recent Harvard Business Review analysis of AI-linked layoffs argues that many firms are cutting staff based on anticipated value rather than proven results. In other words, some companies are reorganizing around unproven promises.

That is how an “AI elite” narrative turns corrosive. Workers get the message that they must use AI, but they do not get the training, guardrails or incentives to use it well. The result is speed without discipline: sloppy outputs, hidden errors and shadow adoption that quietly expands risk.

The more serious organizations are choosing a harder path.

Accenture’s LearnVantage push put a billion-dollar bet on large-scale AI upskilling. KPMG has offered cash rewards for employee AI innovation, signaling that experimentation should create enterprise value, not just personal efficiency. And Marriott’s technology leadership has emphasized a limited set of high-value AI use cases instead of spraying tools across the company and hoping culture catches up.

That is the better model: Train people, pick workflows that matter, measure outcomes that executives actually care about an build governance before a security incident builds it for you. Most of all, stop pretending that adoption is the same thing as transformation. It is not.

The employee most at risk now is not necessarily the one who has never touched an AI tool. It is the one who believes the old definition of competence will survive unchanged.

Leaders should be careful too. Companies will not win by turning AI into a fear-test. They will win by creating workplaces where human judgment gets more valuable as machine output gets cheaper. That is the real career insurance in the AI era, and the real competitive advantage.

Gleb Tsipursky, Ph.D., serves as the CEO of the future-of-work work consultancy Disaster Avoidance Experts and wrote “The Psychology of Generative AI Adoption” and “Returning to the Office and Leading Hybrid and Remote Teams.”

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