A new study from Harvard Business Review suggests that AI doesn't reduce work, but rather intensifies it, enabling more high-speed, individual tasks that require protective „human connection” time to avoid professional burnout.
One of the promises of AI is that it can reduce workload so employees can focus more on higher-value and more engaging tasks. But, according to a new study, AI tools don't reduce work, they steadily intensify it: In the study, employees worked at a faster pace, took on a wider range of tasks, and extended work across multiple hours of the day, often without being asked. This may seem like a victory, but it's not quite that simple. These changes can be unsustainable, leading to increased workloads, cognitive fatigue, burnout and weakened decision-making, reveals the new Harvard Business Review analysis. The productivity gains enjoyed in the early days can give way to lower-quality work, staff turnover and other problems. To correct this problem, companies need to adopt an „AI ethic,” or a set of rules and standards around the use of AI, which can include purposeful breaks, sequencing work, and adding a broader human approach.
În prezent, multe companii sunt îngrijorate de cum să convingă mai mulți angajați să utilizeze IA. La urma urmei, promisiunea reducerii poverii unor sarcini prin intermediul IA – redactarea documentelor de rutină, rezumarea informațiilor și decodarea – și acordarea de mai mult timp lucrătorilor pentru sarcini de mare valoare este tentantă.
But are they prepared for what might happen if they succeed? While leaders focus on the promised productivity gains, they may be blindsided by the complex reality and not see how much these gains are costing them until it's too late.
”In the present research, it was discovered that AI tools have not reduced work but have instead constantly intensified it. In an eight-month study of how generative AI has changed work habits at a US tech company with about 200 employees, it was found that employees worked at a faster pace, took on a wider range of tasks, and extended their working hours across more of the day, often without being asked to. It is important to note that the firm did not mandate the use of AI (though it did provide subscriptions to commercially available enterprise AI tools). Of their own volition, workers did more because AI made „doing more” seem possible, accessible, and, in many cases, intrinsically rewarding,” say the study's authors.
Although this may seem like a dream come true for leaders, the changes brought about by the enthusiastic adoption of artificial intelligence can be unsustainable, causing problems down the line. Once the initial excitement of experimentation fades, workers may find their workload has quietly increased and feel overwhelmed by juggling everything suddenly in front of them. This gradual increase in workload can, in turn, lead to cognitive fatigue, burnout, and weakened decision-making. The increased productivity initially enjoyed may give way to lower-quality work, staff turnover, and other issues.
Acest lucru îi pune pe lideri într-o situație dificilă. Ce ar trebui să facă? A cere angajaților să se autoreglementeze nu este o strategie câștigătoare. Mai degrabă, companiile trebuie să dezvolte un set de norme și standarde privind utilizarea IA – ceea ce numim o „etică IA”. Iată ce trebuie să știe liderii și ce pot face pentru a-și pregăti angajații pentru succes.
How generative AI intensifies work
From April to December of last year, we studied how generative AI tools altered work habits at a tech company, according to HBR specialists. We did this through personal observation two days a week, monitoring internal communication channels, and over 40 in-depth interviews across fields such as engineering, product, design, research, and operations.
I have identified three main forms of intensification:
- Expanding tasks
Because AI can fill knowledge gaps, workers have increasingly taken on responsibilities that previously belonged to others. Product managers and designers have started writing code; researchers have taken on engineering tasks; and people across the organization have tried their hand at work they would have outsourced, postponed, or avoided entirely in the past.
Generative AI has made these tasks feel accessible again. These tools have provided what many have experienced as an empowering cognitive boost: they reduced reliance on others and offered immediate feedback and corrections along the way. Workers have described this as „just trying things out” with AI, but these experiments have accumulated into a significant broadening of job scopes. In fact, workers have increasingly absorbed work that previously might have justified assistance or additional headcount.
Au existat efecte secundare ale extinderii atribuțiilor oamenilor. De exemplu, inginerii, la rândul lor, au petrecut mai mult timp revizuind, corectând și îndrumând lucrările generate de IA sau asistate de IA produse de colegi. Aceste cerințe s-au extins dincolo de revizuirea formală a codului. Inginerii s-au trezit din ce în ce mai mult îndrumând colegi care „codau prin vibrații” și finalizau cereri de extragere parțial complete. Această omisiune a apărut adesea informal – în thread-uri Slack sau în consultări rapide la birou – adăugând volumul de muncă al inginerilor.
- Blurred lines between work and non-work
Deoarece inteligența artificială a făcut ca începerea unei sarcini să fie atât de ușoară – a redus fricțiunea de a se confrunta cu o pagină goală sau un punct de plecare necunoscut – lucrătorii au strecurat cantități mici de lucru în momente care anterior fuseseră pauze. Mulți au solicitat informații de către inteligența artificială în timpul prânzului, în cadrul ședinței sau în timp ce așteptau încărcarea unui fișier. Unii au descris trimiterea unei „ultime solicitări rapide” chiar înainte de a părăsi biroul, astfel încât inteligența artificială să poată lucra în timp ce ei se îndepărtau.
These actions rarely felt like they were doing much work, but over time, they yielded a workday with fewer natural breaks and more continuous engagement with the work. The conversational style of prompting further dulled the experience; typing a line to an AI system felt closer to conversation than to completing a formal task, making it easier to extend work into the evening or early morning without deliberate intention.
Unii lucrători au descris că și-au dat seama, adesea în retrospectivă, că, pe măsură ce solicitarea în timpul pauzelor a devenit obișnuită, timpul de nefuncționare nu mai oferea același sentiment de recuperare. Prin urmare, munca părea mai puțin limitată și mai ambiantă – ceva ce putea fi întotdeauna avansat puțin mai mult. Granița dintre muncă și non-muncă nu a dispărut, dar a devenit mai ușor de depășit.
- More multitasking
AI introduced a new rhythm where workers managed multiple active threads simultaneously: manually writing code while AI generated an alternative version, running multiple agents in parallel, or reactivating long-dormant tasks because AI could „handle” them in the background. They did this, in part, because they felt they had a „partner” to help manage their workload.
Although this feeling of having a „partner” allowed them a sense of momentum, the reality was a constant shift in attention, frequent checking of AI outputs, and an ever-growing list of open tasks. This created a cognitive load and a feeling of constant juggling, even if the work felt productive.
De-a lungul timpului, acest ritm a crescut așteptările de viteză – nu neapărat prin cerințe explicite, ci prin ceea ce a devenit vizibil și normalizat în munca de zi cu zi. Mulți lucrători au remarcat că făceau mai multe deodată – și simțeau mai multă presiune – decât înainte de a utiliza IA, chiar dacă economiile de timp obținute prin automatizare erau aparent menite să reducă o astfel de presiune.
What does this mean for organizations – and how can „AI ethics” help”
All of this has produced a self-reinforcing cycle. AI has accelerated certain tasks, which has increased expectations for speed; increased speed has made workers more dependent on AI. Increased dependence has broadened the scope of what workers are trying to accomplish, and a broader scope has further expanded the amount and density of work. Several participants noted that while they felt more productive, they did not feel less busy, and in some cases felt busier than before. As one engineer summarized, „You thought maybe because you could be more productive with AI, then you'd save time, you could work less. But in fact, you don't work less. You just work the same amount or even more.”
Organizations might see this voluntary expansion of work as a clear win. After all, if workers are doing this of their own volition, what's the harm? Isn't this the productivity explosion we were promised?
However, our research reveals the risks of allowing work to expand and accelerate informally: what appears to be higher short-term productivity can mask a silent increase in workload and escalating cognitive strain as employees juggle multiple AI-driven workflows. Because the extra effort is voluntary and often framed as enjoyable experimentation, it's easy for leaders to overlook how much additional burden workers are shouldering. In time, overload can impair judgment, increase the likelihood of errors, and make it difficult for organizations to distinguish between genuine productivity gains and unsustainable intensity. For workers, the cumulative effect is fatigue, burnout, and a growing sense that it's harder to switch off from work, especially as organizational expectations for speed and responsiveness rise.
Instead of passively reacting to how AI tools are reshaping jobs, individuals and companies alike should embrace an „AI practice”: a set of intentional norms and routines that structure how AI is used, when it’s appropriate to pause, and how work should and should not expand in response to newly acquired capability. Without such practices, the natural tendency of AI-assisted work is not contraction, but intensification, with implications for burnout, decision quality, and long-term sustainability. As organizations work to develop their AI practice, they should consider adopting:
Intentional pauses
As tasks accelerate and boundaries blur, workers might benefit from short, structured moments that regulate pace: protected intervals to assess alignment, reconsider assumptions, or absorb information before moving forward.
Aceste pauze nu ar încetini munca în general; ele ar preveni pur și simplu acumularea liniștită a supraîncărcării care apare atunci când accelerarea nu este controlată. De exemplu, o pauză decizională ar putea necesita, înainte de finalizarea unei decizii majore, un contraargument și o legătură explicită cu obiectivele organizaționale – lărgind câmpul de atenție suficient de mult pentru a proteja împotriva derivei. Incorporarea unor astfel de pauze în fluxul de lucru zilnic este o modalitate prin care organizațiile pot susține decizii mai bune, limite mai sănătoase și forme mai sustenabile de productivitate în medii augmentate de IA.
Sequencers
As AI enables constant background activity, organizations can benefit from norms that deliberately shape when work advances, not just how fast. This includes batching non-urgent notifications, holding updates until natural breakpoints, and protecting focus windows where workers are shielded from interruptions.
În loc să reacționeze la fiecare rezultat generat de IA așa cum apare, secvențierea încurajează avansarea muncii în faze coerente. Atunci când coordonarea este ritmată în acest fel, lucrătorii se confruntă cu o fragmentare mai mică și cu mai puține schimbări de context costisitoare, în timp ce echipele mențin randamentul general. Prin reglarea ordinii și a calendarului muncii – în loc să solicite o reacție continuă – secvențierea poate ajuta organizațiile să păstreze atenția, să reducă supraîncărcarea cognitivă și să sprijine o luare a deciziilor mai atentă în locurile de muncă bazate pe IA.
Human communication
Pe măsură ce IA permite o muncă mai individuală și autonomă, organizațiile pot beneficia de protejarea timpului și spațiului pentru ascultare și conexiune umană. Oportunitățile scurte de a se conecta cu ceilalți – fie prin scurte verificări, momente de reflecție comună sau dialog structurat – întrerup implicarea individuală continuă cu instrumentele IA și ajută la restabilirea perspectivei.
Beyond perspective, social exchange fuels creativity. AI offers a synthesized, unique perspective, but creative perspective depends on exposure to multiple human viewpoints. By institutionalizing time and space for listening and dialogue, organizations re-anchor work in social context and help counteract the draining and individualizing effects of fast-paced, AI-mediated work, the study authors conclude.
