AI Fluency is Becoming a Career Dividing Line

By Gleb Tsipursky

The new office divide is no longer remote worker versus in-person worker 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 unusual bluntness: many employers now say workers who resist AI risk stalled advancement or worse. Out of 2,400 employees and C-suite leaders, 60% of companies say they plan to lay off employees who will not adopt AI, 77% of executives say AI resisters will be passed over for promotions, and 92% say they are actively cultivating an “AI elite” class of workers.

Even more telling, 87% of executives say those employees are at least 5 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% of core job skills are expected to change by 2030, with technological change as the biggest driver.

At the same time, McKinsey’s workplace AI research found that almost all companies are investing in AI, while only 1% describe themselves as mature in their use of 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 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% 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 a promise they have not yet earned.

AI Fluency Means Precision, Not Just Usage

That is how an “AI elite” narrative turns corrosive. Workers get the message that they must use AI, but not 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 rather than spraying tools across the company and hoping the culture catches up.

That is the better model. Train people. Pick workflows that matter. Measure outcomes that executives actually care about. 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. But 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.

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Editor’s Note: This is part of an ongoing series examining generative AI and its continuing impact on the business world.

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The information and opinions presented are the author’s own and not those of Vistage Worldwide, Inc.

This story was first published on the Vistage Research Centre.