Your Team Adopted AI. So Why Are They More Exhausted Than Ever?

When AI tools started rolling out across organisations, the promise was seductive: less admin, more thinking time. Fewer repetitive tasks, more space for the work that actually matters. Leaders signed off on the investments, communicated the vision, and waited for the productivity gains to show up.

For most teams, they didn't.

A Microsoft Work Trend Index found that 77% of employees say AI has actually added to their workload rather than reduced it. If you've been paying attention to your teams over the past year, this probably doesn't surprise you. The tools are genuinely useful — but something isn't translating. And the instinct is to blame adoption, or change fatigue, or employees who "aren't ready."

That instinct is wrong. The problem isn't the people. It's the system they're working in.

What Happens When You Add Speed to a Broken Process

AI tools don't redesign work. They accelerate the existing shape of it.

When you give a team faster ways to produce outputs — drafts, analyses, reports, summaries — without changing the workflows, approval structures, or output expectations around those outputs, you don't lighten the load. You raise the bar. More iterations. Faster turnarounds. Higher volume. The same person, running harder on a treadmill that's been turned up.

I've seen this play out repeatedly. A communications team starts using AI to generate first drafts, and within three months they're producing twice the content — but still going through the same four rounds of approval. A finance team uses AI to build models faster, and leadership simply asks for more scenarios. An HR team automates parts of their reporting, and the time saved is immediately absorbed by a new set of requests that "wouldn't have been feasible before."

The efficiency gains get captured by the system, not the people. And the people feel it.

The Design Problem Nobody Is Solving

Here's the question most organisations are not asking: if AI is doing more, what are we explicitly stopping?

Not "what could we theoretically stop" — but what has actually been removed from the plate, with clarity and intention, so that people can feel the difference?

This is a work design problem. And most leaders are not trained to think about work design — they're trained to add, delegate, and optimise. The discipline of subtraction is genuinely harder, and in most organisations, there is no one explicitly accountable for it.

The result is a workforce that is simultaneously more capable and more stretched. Teams that have technically "adopted AI" but haven't experienced any of the promised relief. And a growing cynicism about transformation initiatives that — if leaders aren't careful — will make the next change harder to land than the last one.

The Conversation That Changes Things

I worked with a leadership team last year who came to me frustrated. AI adoption was high — their teams were actively using the tools — but engagement scores had dropped and turnover among their strongest performers had ticked up.

When we dug into it, the story was consistent across every team: people were doing more, not less. The tools had expanded what was possible, and leaders had unconsciously expanded their expectations to match — without any conversation about what that meant for the humans doing the work.

The fix wasn't complicated. But it required something most senior leaders find uncomfortable: slowing down to ask their teams a set of very direct questions.

What are you spending time on that AI could handle? What should we stop asking you to do? What would genuinely free up your thinking?

The answers were specific, actionable, and in most cases, immediately addressable. Within two quarters, the same teams that had been running on empty were reporting meaningful improvements in how they were experiencing the work — not because the tools changed, but because the design around the tools finally caught up.

What Leaders Actually Need to Do

The conversation about AI in most organisations is still almost entirely about capability — which tools to use, how to train people, how to measure adoption. These things matter. But they are upstream of the real issue.

The leaders who are getting this right are asking a different set of questions:

What does our team's work actually look like now, versus six months ago? Not in theory — in practice. What's been added? What's been removed? What's the net effect on the people doing the work?

What do we need to stop, not just start? Every AI initiative should come with an explicit conversation about what it replaces — not just what it enables. If it doesn't, the gains will be absorbed invisibly and the costs will be felt very visibly.

Where is the approval process slowing down the technology? Fast tools inside slow systems create frustration, not productivity. The bottleneck is almost never the people — it's the infrastructure around them.

Are we confusing activity with value? More output is not automatically better output. If AI is helping teams produce more, the question leaders should be asking is whether all of that "more" is actually serving the organisation's goals — or just filling the space that the technology created.

The Real Ask

AI adoption is not a technology project. It's a work redesign project that happens to involve technology.

The organisations that will see genuine, sustainable productivity gains from AI are not the ones that deployed the most tools the fastest. They're the ones where someone in a leadership role had the discipline to ask: what needs to change about how we work, not just what we use?

That question requires courage — because the honest answers often implicate decisions that leaders made, priorities that were set, and structures that were built. It's easier to point to the technology than to examine the system.

But the 77% are waiting for someone to do the harder work. And in most organisations, that someone is you.

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Is your team running harder since AI rolled out — without feeling the benefit? If you'd like to think through what work redesign looks like in your context, I'd love to have a conversation. Book a complimentary strategy call here.

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Adeline Tiah is an ICF PCC Certified Executive Coach based in Asia, with 28 years of corporate leadership experience across global MNCs. She specialises in leadership transformation, high-performing teams, and culture change — and is the author of Reinvent 4.0, a guide to leading with purpose in an age of disruption.