AI and the efficiency paradox

How AI can reduce burnout and engagement at the same time

The other day was quite stressful: looming deadlines, a difficult client on the one hand, and a well-intentioned but insistent one on the other. Being self-employed, I had no one to turn to, but I also had no one to blame!

However, being self-employed also gave me an option to deal with the stress - one that I never had in an office. I went for my afternoon snooze. In the treehouse, out of reach of WiFi, phone switched off, nestled in a hammock with only the swish of trees in the breeze and the rustle of birds and squirrels, I slept for about 40 minutes. I often do.

I am sure many of you reading this will be pretty envious - what a luxury to turn it off like that! But for me it's not a luxury. It’s a necessity. Time away from screens and deadlines makes me more productive and creative when I do return to work. I’ve learned this the hard way after years of running myself into the ground in pursuit of efficiency.

Efficiency is the idol of knowledge work. We're constantly urged, cajoled or shamed into streamlining, optimizing, and doing more with less.

We have a paradox to deal with here: AI can handle mundane tasks, but how can we fail to ask whether that’s enough to keep us engaged in our work?

AI to the rescue (but not so fast!)

So much of our work is somewhat repetitive and mechanical. But let's not exaggerate.

Adam Smith recognized what real monotony looked like in the 18th century. In Book V of The Wealth of Nations, he noted that when workers perform monotonous, repetitive tasks, such work can make individuals as stupid and ignorant as it is possible for a human creature to become. Smith proposed universal education as a remedy to maintain workers' faculties so they could participate fully in society.

Our monotony is not the tedium of a factory floor. But still, AI promises to take on some of the mundane tasks we all face.

Chatbots can already manage routine inquiries and schedule appointments. For those working with data, AI tools can dramatically improve the efficiency of data cleansing and even analytics. Process mining can analyze how teams, or even individuals, work, identifying inefficiencies and unnecessary steps in processes.

This is undoubtedly welcome because one of the leading causes of burnout is an unmanageable workload.

Exhaustion isn’t the only enemy

Burnout isn’t just about physical or mental fatigue. It’s about feeling disconnected from life, losing that bright hopefulness that makes work meaningful. I’ve learned that one secret of good work is not just reducing exhaustion but finding ways to engage our hearts and minds or risk falling into cynicism. One of the best frameworks for understanding workplace stress is the Utrecht Work Engagement Scale - a psychological tool designed to measure an individual's level of work engagement developed by Wilmar Schaufeli and Arnold Bakker in 2004. They point out that while exhaustion is often the more obvious consequence of an unmanageable workload, cynicism is a more profound, insidious effect that emerges when work loses meaning or becomes dissatisfying. And that can’t be resolved simply by reducing the workload.

Cynicism is tied to emotional and psychological disconnection from work. When employees no longer find their work meaningful or engaging, they become detached, negatively viewing their tasks and even their colleagues or clients. So, addressing cynicism involves much more than just reducing physical exhaustion — which AI can do - it requires creating interesting, meaningful, and engaging work.

Creative friction

So, here's the paradox of AI, automation and efficiency. While AI can reduce exhaustion by optimizing workflows, automating routine tasks, and improving work-life balance, it doesn’t necessarily make work more meaningful. If overused, AI may lead to scenarios where employees feel disconnected from essential aspects of their jobs, especially if AI takes over tasks that once provided a sense of accomplishment or challenge. AI may trap employees in a comfort zone, where workloads are optimized but lack intellectual stimulation or growth opportunities.

So, how do we avoid falling into this trap? How do we make space for the human element—creativity, reflection, and meaningful engagement- even though we still want AI's conveniences? We can’t let ourselves get disconnected from life by constantly multitasking. The answer most likely lies in finding a balance and embracing what we might call positive friction: the intentional pauses that help us reconnect.

That doesn't mean we all have to sleep in the treehouse, although if you're in the neighborhood, I will make you welcome!

I have written about the value of walking meetings rather than office-bound or online meetings. But there are other techniques that we can use, even using the very same productivity tools that may otherwise dull our senses.

Cal Newport has written about deep work: the ability to sit with an uninterrupted focus on cognitively demanding tasks. It's the opposite of multitasking: it’s about giving your attention to just one important task.

So, you might create structured periods in the day when staff can work without distractions, free from meetings, emails, and notifications. Set specific times when deep work is prioritized across the organization, ensuring everyone can find their zone.

It’s not what we have planned or wanted when we pursue AI-driven efficiency. But I’ve found that sometimes the real value comes from those moments of creative friction: the places where our interior voice tells us we need to pause and reflect, giving our work the best of our attention.

Write it down to raise it up

Another approach I have seen work well is to encourage reflection on work. Journaling, particularly interstitial and bullet journaling, can serve as practical, intentional pauses and help generate new ideas or perspectives that might not emerge in the typical workflow.

Interstitial journaling, for example, is a technique developed by Tony Stubblebine, where we take brief notes between tasks or meetings, capturing thoughts, emotions, and observations in real-time. By jotting down thoughts after completing a task or shifting between projects, we can reflect on what went well, what challenges we encountered, and what we learned. During these transitions, we are better positioned to spot inefficiencies and recognize frustration, satisfaction, or disengagement moments. Often, our best ideas come during periods of reflection rather than in the heat of productivity. Journaling allows employees to capture fleeting thoughts or insights that may arise when they aren’t actively trying to solve a problem.

Journaling can also buffer against the cynicism that often accompanies burnout by helping employees understand the why behind their tasks, connecting them with the purpose of their work. One of the most effective ways to combat this is to celebrate small achievements. Journaling allows employees to build confidence in their progress and, therefore, to take greater ownership of their tasks and results, even with automation. This feeling of ownership can reduce cynicism, as employees feel more personally invested in their outcomes.

And, of course, AI can even support journaling by offering suggestions based on task data, recognizing patterns, and helping employees track their progress over time.

Efficiency can be inefficient

Personally, I find working with AI to be very engaging. However, I am painfully aware that the efficiencies that AI affords knowledge workers may actually be a drawback rather than a success in the long run. We can optimize tasks and processes, but we need more. How can we fail to ask whether that constant drive for efficiency leaves us disconnected from life? The paradox is that to thrive in an AI-driven world, we need to remain more human than ever.