For years, we have been advised to pursue work-life balance. The metaphor itself may now be part of the problem because it assumes that work and life sit on two opposite sides of a weighing scale. If one side goes up, the other must come down. The implication is that work and life are separate domains competing for the same finite amount of time and energy.
But for many working professionals, that separation has already disappeared. Work travels with us through email, WhatsApp, Teams and smartphones. We think about unfinished work while having dinner, respond to messages from home, and often carry work-related concerns into weekends and holidays. Hybrid work has made the boundary even less visible. And now AI enters this already blurred system.
This is why I think the discussion around AI and work-life balance needs to go beyond the usual argument that AI will make us more productive. The more important question is whether AI can help us redesign the relationship between work and the rest of our life. And behind that lies an even more difficult question: if AI saves time and cognitive effort, who actually gets the benefit of that released capacity?
The blurring of work and life is not new. Mazmanian, Orlikowski and Yates (2013), in their study of mobile email use among knowledge professionals, described what they called the autonomy paradox. Mobile technologies gave people greater flexibility and freedom to work from anywhere, but that flexibility gradually created stronger expectations of availability. What appeared to increase individual autonomy could, collectively, create a culture in which people were expected to remain permanently connected.
We have experienced this transition over the last two decades. “You can work from anywhere” slowly became “you can be reached anywhere.” Technology therefore did not simply change the way a task was performed; it changed organisational expectations, communication norms and the meaning of professional availability.
AI may create a similar transition, but at a deeper level. Smartphones extended the workplace into our physical and social space. AI is now entering our cognitive space by taking over parts of drafting, searching, summarising, analysing, organising and decision support.
Generative AI can already assist with many routine cognitive activities: preparing first drafts, summarising reports, organising meeting notes, searching for information, comparing alternatives, developing presentations and performing initial analysis. Research such as Dell’Acqua et al. (2026) shows that AI can improve productivity and quality for certain kinds of knowledge work, provided the task lies within the capability of the technology.
But this evidence relates primarily to the quality and productivity of work. It does not automatically tell us anything about the quality of life of the worker. This distinction is important.
Suppose a professional previously needed four hours to prepare a report and can now complete it in three hours with AI assistance. We often describe this as one hour “saved.” But is that hour really saved? The organisation may simply add another task, increase the expected volume of output or reduce the turnaround time for future work.
In that case, AI does not create work-life balance. It creates higher work intensity.
This is the point at which the productivity argument becomes incomplete. AI may reduce the cognitive burden associated with individual tasks, but unless we consciously decide what happens to the released capacity, the system may simply absorb that capacity and demand more output.
This is why the recent study by Pinho, Fontes and Santos (2026) is particularly relevant. Using the Job Demands-Resources perspective, they examine how employee-AI collaboration relates to work engagement and work-life balance. Their findings suggest that AI can operate as a valuable work resource, while AI-related pressures and awareness of technological disruption can also become sources of strain.
This “double-edged” character of AI is important. Technology by itself does not determine whether the outcome will be positive or negative. The result depends on how it interacts with workload, management practices, organisational expectations, employee autonomy, communication norms and individual behaviour.
Consider two professionals using exactly the same AI system. In one organisation, AI reduces routine documentation and administrative work, allowing the employee to spend more time on deeper thinking, professional development and meaningful interaction with colleagues. The employee may also be able to finish work at a more reasonable hour.
In another organisation, exactly the same productivity improvement may lead to more assignments, faster deadlines and expectations of immediate responses. The employee becomes technically more efficient but personally more overloaded.
The technology is the same, but the human outcome is different. That is why I see the issue fundamentally as a socio-technical design problem.
At this stage, there is another danger. If we say that “work-life balance” is the wrong metaphor, we should not replace it with an idea of work-life integration in which work is allowed to enter every part of life. That would simply legitimise the always-on culture in a different language.
Clark’s (2000) Work/Family Border Theory is useful here. People continuously cross boundaries between work and family roles, but individuals differ in how much integration or separation they prefer. The objective, therefore, is not necessarily to eliminate boundaries. It is to design and manage them consciously.
For me, work-life integration means that work is understood as one important part of life, but not the whole of life. The issue is not how to keep work and life in two completely separate compartments; nor is it how to blend them completely. The issue is how to design their relationship in a way that is consistent with one’s values, responsibilities and aspirations.
Life Design offers a useful way of thinking about this problem. Traditional career thinking often starts with questions such as: What job should I take? How can I progress in my career? What skills should I develop next?
Life Design starts from a broader question: What kind of life am I trying to construct? Savickas et al. (2009) argue that careers in a changing world increasingly need to be understood as something people construct and reconstruct as circumstances change. AI is now becoming one of those changing circumstances.
So the AI question for a working professional should not be limited to: How can I use AI to do my present job faster? A more important question may be: If AI changes how I work, what role do I now want work to play in my life?
That leads to several practical questions. Which parts of my work should I delegate to AI? Which activities should remain distinctly human because they involve judgement, creativity, relationships or responsibility? Where should I maintain strong boundaries? And if AI releases some of my time and attention, what do I want to do with that capacity?
Imagine that AI eventually releases five hours of cognitive capacity for a professional every week. Those five hours may not necessarily mean leaving the office five hours earlier, but they represent human attention that was previously consumed by repetitive or low-value cognitive work.
The default organisational response may be to convert those five hours into more output. But that is only one possible use. Some of the released capacity could instead support learning, mentoring, reflection, creative thinking, family relationships, health, community involvement or simply time away from work.
This is not an argument against productivity. Better productivity is valuable, and meaningful work itself can be an important source of identity, achievement and purpose. The issue is what happens when productivity becomes the only measure of the benefit created by AI.
Perhaps, therefore, the more useful pathway is not simply:
AI → higher productivity → more output
but something closer to:
AI → reduced routine cognitive load → released human capacity → better work + richer life
The important phrase here is released human capacity. AI does not automatically create that outcome. Whether the capacity is genuinely released, and what happens to it afterwards, depends on individual choices, organisational policy and social norms.
This brings me back to the original problem with the balance metaphor. Work and life are no longer two completely separate worlds, and trying to balance them mechanically may not be the most useful way to think about contemporary professional life.
At the same time, integration should not become an excuse for permanent connectivity. What we perhaps need is purposeful work-life integration with consciously designed boundaries. Work should occupy an intentional place within the larger life we want to live.
AI gives us an unusual opportunity to revisit that design. It can reduce drudgery, support thinking and take over parts of routine cognitive work. But it can equally increase workload, accelerate expectations and make an already connected professional life even more intensive.
Technology creates the possibility. The surrounding human and organizational system determines the outcome.
So perhaps the important question in an AI-augmented world is no longer simply, “How do I achieve work-life balance?” It is: “If AI changes what I have to do, how I do it and how much of my attention work consumes, how do I want to redesign the relationship between my work and the rest of my life?”
And that, to me, is fundamentally a Life Design question.
Clark, S. C. (2000). Work/family border theory: A new theory of work/family balance. Human Relations, 53(6), 747–770.
Dell’Acqua, F., McFowland, E., III, Mollick, E., Lifshitz, H., Kellogg, K. C., Rajendran, S., Krayer, L., Candelon, F., & Lakhani, K. R. (2026). Navigating the jagged technological frontier: Field experimental evidence of the effects of artificial intelligence on knowledge worker productivity and quality. Organization Science, 37(2), 403–423.
Mazmanian, M., Orlikowski, W. J., & Yates, J. (2013). The autonomy paradox: The implications of mobile email devices for knowledge professionals. Organization Science, 24(5), 1337–1357.
Pinho, J. C., Fontes, A., & Santos, G. G. (2026). Balancing the double-edged sword of artificial intelligence: Job demands, resources, and work-life balance. Computers in Human Behavior Reports, 21, 100924.
Savickas, M. L., Nota, L., Rossier, J., Dauwalder, J.-P., Duarte, M. E., Guichard, J., Soresi, S., Van Esbroeck, R., & van Vianen, A. E. M. (2009). Life designing: A paradigm for career construction in the 21st century. Journal of Vocational Behavior, 75(3), 239–250.
