Artificial intelligence is transforming how we work and the opportunity is real.
The ability to move faster, think bigger, and tackle problems that were previously out of reach is not hypothetical. We are living it.
But new data suggests that the way most organisations are deploying AI is not only leaving significant value on the table, it’s also creating unintended pressure in the process.
Research from YuLife, based on a YouGov survey of more than 1,100 UK employees, shows that among those already using AI tools, 26% say it has increased pressure at work and 23% report a higher workload. In London, where adoption is highest, 40% of users report increased performance pressure and nearly half worry about job security.
This isn’t an argument against AI. It’s an argument for deploying it more thoughtfully: thinking as much about the people using the AI as we are about the technology itself.
The efficiency trap
Time saved doesn’t automatically stay saved.
Tasks that used to take hours now take minutes, but that efficiency rarely results in less work. Instead, it resets expectations. Faster output becomes the baseline, and what once stood out as strong performance quietly becomes the minimum required.
Harvard Business Review recently identified a related dynamic “brain fry,” cognitive fatigue that emerges not simply from workload, but from the way AI changes the nature of work. When AI handles more of the thinking, humans are left managing, verifying, and course-correcting at pace. The cognitive load shifts rather than shrinks.
The result is that AI’s gains are real, but they’re often being absorbed by organisations rather than shared with the people doing the work. Around a third of professionals in our survey don’t believe productivity gains from AI will be reinvested into their wellbeing or development. That’s a leadership and culture challenge, not a technology one.
The wider context matters too. Last year, more than 850,000 additional sick notes were issued in the UK linked to mental health. We may be at a moment comparable to when people moved from fields to factories, a structural shift in how work is done that requires entirely new thinking about risk, resilience, and what support actually means.
What getting it right looks like
The organisations pulling ahead aren’t necessarily the fastest adopters. They’re the most intentional.
At a recent senior insurance industry roundtable I hosted, a clear consensus emerged: AI handles the preparation; humans handle the relationship, the judgment, the accountability. Clients are arriving better-informed than ever, which raises the bar, and raises the value of genuinely good human expertise.
The same logic applies internally. AI is most powerful not when it replaces thinking, but when it amplifies it, freeing teams to tackle bigger problems, move faster on what matters, and do work that simply wasn’t possible before.
The future isn’t human or machine. It’s human and machine.
What Getting it Right Looks Like
I’m not writing about this from a distance. We’re navigating it ourselves and it’s genuinely exciting.
We’re building a company-wide AI infrastructure for our people, with our Chief Product Officer and his team leading a significant investment in upskilling the whole organisation. The goal isn’t to hand people a tool and walk away, or simply to develop a small cohort of super-users. It’s to build real collective capability and context, so that individual increases in productivity can translate into better customer and company outcomes. That flywheel is already starting to turn.
We’ve also had to be deliberate about one thing: separating efficiency from expectation.
When something that used to take half a day can be done in an hour, the instinct is to fill the remaining time. Over time, that changes what people believe is expected of them. We’ve been explicit about where we won’t let expectations drift, and intentional about returning time saved to our people, rather than automatically reinvesting it into more output. But beyond managing expectations, this moment demands something deeper: a genuine investment in resilience, adaptability, and continuous learning. The organisations that thrive won’t just be the ones that adopted AI earliest. They’ll be the ones that built the human capability to grow alongside it.
The opportunity is in the intention
Expectation inflation is a choice.
It shows up in how leaders set targets, how performance is measured, and whether time saved is treated as an opportunity to improve how work is experienced, or simply as a way to extract more of it.
The companies that get AI right won’t just be more productive. They’ll be more resilient, more differentiated, and better places to work. That’s a real competitive advantage and it’s available to any organisation willing to be deliberate about how it leads this change.
AI is a genuine superpower.
The question is whether we use it to build something better, or simply to go faster.
We should be aiming for both.
Tal Gilbert is the CEO of AI-forward insurtech YuLife
