Why AI Changes How We Understand Human Performance at Work

For more than a decade, my work has focused on wellbeing and performance in the corporate world. I have trained, coached, and advised teams and leaders in small organisations as well as large global companies, across different industries and cultures.

And if there is one thing I have observed consistently over the years, it is this: despite having more data than ever, work has not become healthier, nor has it become more sustainable from a performance perspective.

In many organisations, the opposite seems to be happening. Pressure is increasing, wellbeing is deteriorating, and performance is becoming more fragile. This is not just a personal impression. Large international studies, such as the Gallup engagement surveys, show that employee engagement is at some of the lowest levels ever recorded worldwide.

This creates a striking paradox.

We measure more than ever, yet very little seems to improve.

The limits of data-rich work environments

Most organisations today describe themselves as data-driven. They track working hours, sick leave, absenteeism, turnover, engagement scores, productivity indicators, and performance metrics.

In practice, however, this data rarely helps organisations understand why people struggle or what would genuinely improve both wellbeing and performance.

From what I have seen in my work, there are a few structural reasons for this.

Most of the data organisations rely on is quantitative. It is largely retrospective. And it captures outcomes rather than the processes that lead to those outcomes.

We see that someone takes more sick days.
We see engagement scores drop.
We see productivity decline.

But these signals usually appear after problems have already taken root.

What remains largely invisible is how work is actually experienced on a daily basis. How pressure builds over time. How communication patterns evolve. How cognitive load accumulates. How leadership behaviour shapes the system long before any KPI moves.

As a result, many organisations are measuring extensively, yet remain surprisingly incapable of making things meaningfully better.

Why AI will mark a genuine turning point

This is where AI will change the picture.

Not because it will simply generate more data, but because it will make different kinds of data observable in ways that are not yet widely available today.

AI-enabled work environments will, for the first time, make it possible to examine how work unfolds as it happens, rather than only after problems have already materialised.

What these future AI-enabled environments will allow us to observe are qualitative aspects of work that have so far remained largely invisible at scale. This includes patterns of interaction and communication, the language and tone used in everyday exchanges, the clarity or ambiguity of instructions, escalation dynamics, fragmentation versus coherence of work rhythms, and early signals of cognitive overload or sustained pressure.

These are not abstract variables. They are the conditions that shape how people think, feel, collaborate, decide, and sustain effort over time.

The promise of AI in the workplace is therefore not simply automation or efficiency. It is the possibility of moving beyond counting outcomes and towards understanding the conditions under which performance and wellbeing are constructed day by day.

Why this matters even more as work becomes automated

As AI increasingly takes over repetitive, routine, and low-value tasks, the human role at work is changing fundamentally.

What remains for humans are high-value contributions such as creative problem solving, complex decision-making, judgment under uncertainty, ethical reasoning, sense-making, and leadership.

Decades of research in psychology and neuroscience are very clear on one point. These capacities do not function well under chronic stress, constant interruption, or excessive cognitive load. Creativity, learning, and complex thinking only emerge under specific cognitive and emotional conditions.

If AI-enabled work environments are layered onto systems that already overload and exhaust people, automation will not deliver the gains organisations expect. Instead, it risks amplifying pressure, accelerating burnout, and constraining the very human capacities that organisations increasingly depend on.

Why I invested in Kaamfu

This is precisely why I decided to invest in and collaborate with Kaamfu and why I serve as an advisor to the board.

I share Marc Ragdale’s (the founder) conviction that wellbeing and performance are not competing goals. They are intrinsically linked. And this link becomes even more critical in AI-enabled workplaces.

Kaamfu is among the very first initiatives attempting to explore how AI-enabled work environments could be designed differently from the outset. For me, this creates a rare opportunity to bridge theory and practice.

After more than a decade of observing the same patterns across organisations worldwide, Kaamfu offers the possibility to research and refine these observations more systematically, and to explore how human performance actually unfolds in real work contexts at scale.

Introducing Human Performance Intelligence™

This is the context in which I am developing the Human Performance Intelligence™framework.

Human Performance Intelligence™ is the applied science that integrates wellbeing, performance psychology, behavioural dynamics, and real-time insights to understand, predict, and enhance how people function in modern work environments.

Its purpose is not to oppose automation or technology. It is to ensure that AI-enabled systems are designed around how humans actually function cognitively, emotionally, and socially.

Because if we simply place AI on top of already dysfunctional systems, nothing will improve.

But if we use AI to better understand the conditions under which humans operate at their best, when creativity, judgment, and critical thinking can emerge, then we have a real opportunity to design work environments that are both healthier and more effective.

Looking ahead

AI will give us unprecedented visibility into how work happens. Visibility alone, however, will not be enough.

What will matter is how we interpret what we see, and how we use that understanding to design AI environments where humans can operate as their best, most intelligent selves.

This is the research direction I am now pursuing: to help shape AI-enabled work environments that do not merely automate tasks, but genuinely support human performance and wellbeing where it matters most.