AI intensifies work instead of reducing it - consequences for HR
The promise I personally believe in is tempting — artificial intelligence will take over routine tasks and execute them autonomously, tirelessly. This is the vision driving AI adoption across virtually every industry, the vision fueling investors who keep pouring billions into language model development.
New research published in Harvard Business Review, however, puts this vision under scrutiny. Their eight-month study at an American tech company (roughly 200 employees) revealed that AI doesn’t actually reduce workload. It consistently intensifies it.
There’s something to this. Even though I deploy AI everywhere I can, my workload hasn’t shrunk one bit.
Work intensification
The report identifies three mechanisms through which AI tools increase — rather than decrease — the scope and pace of work.
Task expansion
When AI fills knowledge gaps, employees start taking on responsibilities that previously belonged to others. Product managers and designers began writing code. Researchers took over engineering tasks. People in various roles started doing things they would have previously outsourced or simply postponed.
According to the researchers, AI makes new tasks feel accessible. A sense of agency kicks in — “I’ll just try it with AI.” These small experiments add up to a real expansion of responsibilities. The side effect? Engineers spend more and more time reviewing and fixing code generated by colleagues who got into “vibe coding.”
Mapping this to my own experience, I can confirm. AI gave me back time, but also new capabilities — and I don’t hesitate to use them. Vibe coding our ATS system has become part of my daily routine, and my role as a trainer and AI implementation consultant is thriving. The result? Just as I never had enough time before, I still don’t. Maybe even less so now.
Blurring the line between work and rest
The study’s authors note that AI drastically lowers the barrier to starting a task. No more blank page, no more startup friction. The effect? Employees began “firing off a quick prompt” during lunch, in meetings, right before leaving the office — so AI could work while they were on break.
These micro-actions don’t feel like work. Writing a prompt feels more like a conversation than a formal task. But over time, the workday loses its natural pauses, and the boundary between work and rest becomes easier and easier to cross. Many employees admitted in hindsight that their breaks had stopped serving any restorative function.
More multitasking
AI introduces a new rhythm. Employees juggle multiple threads simultaneously — writing code by hand while AI generates an alternative version, running several agents in parallel, returning to long-shelved tasks because “AI can handle them in the background.” This is definitely my case. I regularly work alongside multiple agents. Multitasking has always been my natural work mode, with all its positive and negative consequences.
The researchers note that having a “partner” creates a feeling of momentum, but the reality is constant attention-switching, checking AI outputs, and a growing list of open tasks. Cognitive load rises even when the work feels productive.
A self-reinforcing cycle
The report’s authors describe a mechanism that’s hard to stop. AI speeds up tasks → expectations around pace increase → greater dependence on AI → an even wider scope of attempts → even more work. As one of the engineers in the study put it: you thought AI would save you time and let you work less? In reality, you work just as much or even more.
There’s a real risk that what looks like a productivity explosion in the short term could, over a longer horizon, lead to burnout, judgment errors, and difficulty distinguishing genuine gains from unsustainable intensity.
What can organizations do? The "AI practice" concept
The report suggests that companies shouldn’t react passively but should deliberately shape norms around AI use. These norms should rest on three pillars:
Intentional pauses — planned moments to stop, verify assumptions, and assess direction before work continues. They don’t slow things down; they prevent quiet overload from building up.
Sequencing — instead of reacting to every AI output in real time, organizations should batch notifications, protect focus windows, and let work progress in coherent phases. Less fragmentation, less costly context-switching.
Human anchoring — protecting time for human-to-human contact. Short check-ins, shared reflection, dialogue. AI offers one synthesized perspective, but real creativity requires exposure to diverse human viewpoints.
What does this mean for HR and entire organizations?
HR departments will find themselves in a dual role when facing these phenomena. On one hand, they’ll be subject to work intensification themselves: recruiters and HR professionals using AI will start taking on more processes, writing prompts between meetings, juggling multiple candidate pipelines at once. The feeling that “AI can handle” one more recruitment, one more report, one more compensation analysis will keep growing. With that feeling may come a quiet expansion of duties, blurring of workday boundaries, and rising cognitive load. I don’t think most HR professionals are immune to these mechanisms.
On the other hand, HR departments will be the first to deal with the effects of AI intensification across the entire organization. If employees in various departments start working faster, more, and without natural breaks, the consequences will land on HR’s desk: rising burnout indicators, declining engagement in pulse surveys, more sick leave, higher rates of irritability and team conflicts, and so on. HR will be the ones collecting these signals, diagnosing them, and trying to respond. And if they’re already exhausted from the intensification of their own AI-augmented work, their ability to respond effectively will be severely limited.
What becomes even more important is that tools supporting HR work don’t just speed up processes but, above all, structure and lighten them. An example from my own domain — a well-designed ATS system shouldn’t be yet another source of notifications, prompts, and tasks to manage. It should function as a framework that organizes workflow, automates what’s truly repetitive, and gives recruiters space for what humans are still irreplaceable at.
The key question
The Berkeley researchers end their article with a question every leader should ask themselves — will you actively shape how AI changes work in your organization, or will you let that change quietly shape you?
For HR departments, this question carries particular weight. Because if they don’t answer it deliberately, they’ll become both victims and firefighters of the same blaze.
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Maciej Michalewski
CEO @ Element. Recruitment Automation Software
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