Every leader I speak to right now is somewhere on the same spectrum: either cautiously optimistic about AI, quietly overwhelmed by it, or both simultaneously. And that tension – that contradictory experience of feeling more capable and more exhausted at the same time – turns out to be exactly what the research is uncovering.
We’ve been told the story of AI as relief. Less admin. Faster decisions. More time for the strategic, human work that matters. It’s a compelling narrative. But a growing body of evidence suggests it’s an incomplete one – and for leaders in particular, the gap between the promise and the reality deserves serious attention.
The Productivity Surge That Doesn’t Feel Like Rest
A landmark study published in Harvard Business Review by Aruna Ranganathan and Xingqi Maggie Ye found something striking: when a 200-person tech company gave employees access to generative AI tools, they didn’t work less. They worked more – at a faster pace, across a broader range of tasks, and deeper into their evenings. Nobody asked them to. They just did, because AI made doing more feel possible.
“You had thought that maybe, because you could be more productive with AI, you save some time, you can work less. But then really, you don’t work less. You just work the same amount or even more.”
— Engineer, quoted in HBR study on AI and work intensification
The study identified three distinct patterns: task expansion (people absorbing work that would previously have gone to others), blurred work-life boundaries (AI made starting a task so frictionless that workers slipped prompts into lunch breaks and late evenings), and constant multitasking (managing multiple AI threads simultaneously, creating cognitive load even as it felt productive). The result was a self-reinforcing cycle: AI accelerated tasks, which raised expectations for speed, which created greater reliance on AI, which widened scope further.
The Decision Pressure Leaders Were Already Under
This lands on leaders who were already struggling. Research by Oracle cited in a second HBR study found that 85% of business leaders have experienced decision stress, with three-quarters reporting a tenfold increase in daily decisions over the previous three years. Poor decision-making is estimated to cost firms at least 3% of profits annually – and that’s before we factor in the reputational costs of a single poorly handled crisis.
There’s a deeper paradox at work here. AI gives leaders access to more data, more analysis, and more options than ever before. But more isn’t always better. In practice, the cognitive load of processing vast amounts of information – much of it beyond what you actually need to make a sound decision – is itself a significant source of pressure. Research consistently shows that decision quality degrades as the volume of information increases past a certain threshold.
AI can surface fifty data points where five would suffice, and the effort required to evaluate, filter, and contextualise all of it quietly drains the very capacity leaders need for clear-headed judgment. The result is what researchers call decision fatigue: the more choices and information you process, the poorer your subsequent decisions become. AI, paradoxically, can intensify exactly the problem it promises to solve.
DDI’s Global Leadership Forecast 2025 found that 71% of nearly 11,000 leaders reported rising stress levels since taking on their current role – up from 63% in 2022. Successfully leveraging AI was cited as a top stressor by 29% of respondents. In other words, the very tool meant to relieve pressure is now a source of it.
“AI doesn’t just give you more information – it gives you more than you can act on. And more data without better judgement doesn’t improve decisions; it just makes poor ones feel more justified. The leaders who get the most from AI aren’t the ones who use it most. They’re the ones who know what question they’re trying to answer before they ask it – and who bring the human judgement to know what the answer actually means.”
— James Brook, TalentPredix™
The Hidden Cost Hiding in Plain Sight
What makes this particularly tricky for leaders is that the overload is largely invisible – to themselves and to their organizations. Because employees are expanding their workloads voluntarily, and framing it as energising experimentation, it rarely registers as a problem until it becomes one. A 2026 ActivTrak analysis confirmed the pattern: after AI adoption, task volume and multitasking rose while focused work fell. Burnout isn’t just driven by hours worked – it’s driven by fragmentation, decision fatigue, and lack of recovery time.
Meanwhile, the DHR Global Workforce Trends Report 2026 found 83% of workers reporting at least some degree of burnout, with burnout’s influence on engagement growing sharply – 52% of workers now say burnout drags down engagement, up from 34% in 2025. At the same time, ManpowerGroup’s Global Talent Barometer 2026 found AI adoption jumped 13% while confidence in using AI fell 18%. The tools are spreading faster than the support structures around them.
What Good Leadership With AI Actually Looks Like
The HBR research on decision-making under pressure makes clear that AI genuinely can help – as a sounding board, a co-pilot for synthesising complex risk data, a tool for stress-testing decisions before you commit. The question is whether it’s being deployed intentionally, or just absorbed into the existing pressure. Here’s what the research, and hard-won experience, suggests good leadership looks like in practice.
Build In Intentional Pauses – And Protect Them
Not slow-downs, but structured moments to check alignment and absorb information before pressing forward. AI removes friction, which is mostly good, but friction sometimes served a purpose. A quick decision pause before a major commitment – one counterargument, one explicit link to your strategic goals – can prevent the kind of drift that only becomes visible in hindsight.
Set Boundaries For Yourself – And For Your Team
The blurring of work and non-work is one of the most consistent findings across the research. Because AI makes it so easy to start a task, people stop stopping. Leaders need to model clear boundaries – no prompting during lunch, no ‘quick last query’ at 10pm – and build team norms that make it safe to switch off. Deloitte’s 2025 Workforce Intelligence Report identified cognitive strain and decision friction as the leading indicators of burnout, ahead of workload volume for the first time. Boundaries aren’t soft; they’re structural and vital for effective performance.
Don’t Let AI Become The Boss
There’s a subtle but important shift that happens when AI moves from tool to authority – when its outputs stop being inputs to your thinking and start being the answer. Leaders need to actively resist this. AI works best when it serves the human agenda, not the other way around. That means using it to interrogate your assumptions, not validate them; to widen your options, not close them down. As one expert framed it in the HBR decision-making research: AI functions best as a teammate that challenges your thinking – not an oracle that ends it. The moment your team stops questioning AI outputs is the moment the risk quietly rises.
Keep It Human
AI gives you one synthesised perspective. It draws on patterns in data; it doesn’t draw on lived experience, organizational context, or the kind of judgment that comes from genuinely knowing your people. The 2025 Wiley Workplace Intelligence research found that the traits most predictive of high-performing teams were emotional intelligence, psychological safety, and trust – none of which AI can replicate or replace. The leaders who are getting this right are those who use AI to free up time for human connection, not replace it. Short check-ins, shared reflection, real dialogue – these aren’t soft extras. They’re what makes the rest of it work.
Know How Much Information Is Enough
Good leaders have always known when to stop gathering data and start deciding. AI makes that discipline harder to maintain, because the next analysis is always only a prompt away. Build the habit of asking: what information do I actually need to make this call? More often than not, you already have it. The rest is noise that costs you focus.
The Real Leadership Question AI Creates
The question facing leaders isn’t whether AI will change how you work. It already has. The question is whether you’re actively shaping that change – or letting it quietly shape you. The data suggests most of us are closer to the latter than we’d like to admit. That’s not a criticism; it’s an invitation.
Ready To Lead With More Clarity In The Age Of AI?
Feeling the pressure to make faster, better people decisions with less room for error?
The answer is not more data for the sake of it. It is better insight into what helps people perform, adapt, and thrive.
TalentPredix™ helps organizations understand the strengths, motivations, values, and human capabilities their people need to lead well through constant change.
If you want to build more human, future-ready leadership in the Age of AI, book a demo or get in touch with TalentPredix™.
Sources & Further Reading
AI Doesn’t Reduce Work – It Intensifies It – HBR, February 2026
How AI Can Help Leaders Make Better Decisions Under Pressure – HBR, October 2023
Why Leaders Need to Build Resilience to Avoid AI Burnout – IT Pro, March 2026
Is AI Helping Burnout or Quietly Making It Worse? – HRD Connect, March 2026
Workforce Trends 2026: Leaders Confront Burnout, Disengagement and AI-Driven Change – DHR Global / Hunt Scanlon, November 2025
Takeaways for 2026: About Stress, Change, People and Performance – Wiley Workplace Intelligence, 2025
Author: James Brook
James Brook is the Founder of TalentPredix™ and a leadership, transformation, and strengths-based development expert with over 30 years of global experience. A business psychologist and executive coach, he has helped thousands of leaders and organisations worldwide unlock potential, spark innovation, and build thriving, high-performing workplaces. Previously, James founded Strengthscope®, scaling it into a global strengths assessment brand before exiting in 2018. His earlier career includes senior HR and talent roles at Yahoo!, NatWest, and Novo Nordisk. He holds an MSc in Organisational Psychology, an MBA, and an Advanced Diploma in Executive Coaching.
