The arrival of general AI will force a total redesign of work: from current automation to future superintelligence, technology will challenge performance metrics, redefine professions, and require managing an excess of productive capacity.
The connection between artificial intelligence, time self-management, and reduced working-hours models is quite clear. And when general AI (AGI) arrives, this connection will remain.
Before the big leap toward AGI, we’ve seen all kinds of experiments with shorter schedules or four-day workweeks as ways to improve well-being, retention, or motivation without necessarily hurting productivity.
General AI—understood as AI with cognitive abilities comparable to humans—would allow a significant jump in productivity, innovation speed, and complex problem-solving. If human work in many professions is drastically reduced in volume thanks to AGI, the focus may shift from “how many hours” to “what kind of hours.”
With general AI working 24/7, without fatigue, without rest, sharing knowledge instantly, the productivity ceiling changes radically. This means that human working hours as a key measure of value may lose relevance compared to how the human–AI ecosystem is organized.
What We’re Doing Today
If we return for a moment to today’s artificial intelligence, we should remember that generative AI can already draft texts, reports, and emails; summarize content; provide preliminary analyses; run targeted searches; and automate part of administrative and coordination work. This is not general AI, but it already shows that productivity is no longer solely the result of human effort but co-created between humans and AI systems.
The Adecco Group’s Global Workforce of the Future report—covering 31 countries and 21 sectors—finds that workers in Spain believe they save an average of 171 minutes (2.85 hours) per day thanks to AI (versus 51 minutes a year ago), yet companies do not observe equivalent productivity increases.
The report suggests that AI can free “operational time” for higher-value tasks, but without conscious intervention (training, work redesign, impact metrics), those “freed times” may not translate into real improvements.
Worldwide, 76% of professionals surveyed believe AI is creating more job opportunities, and 70% say roles are evolving, while only 23% have seen or expect job displacement. In Spain, perception is even more positive: 82% think AI is generating more jobs, and 68% confirm role changes. Only 22% have experienced or expect displacement.
The OECD finds that generative AI brings 5% to 25% improvements in writing, summarizing, translation, and coding tasks. MIT Sloan reports that in a controlled test, AI (GPT-4) improved highly qualified workers’ performance by up to 40%.
A St. Louis Federal Reserve study estimates that generative-AI-using jobs saved 5.4% of weekly working hours (around 2.2 hours in a 40-hour week). The Dallas Fed notes that most studies find AI boosts productivity, though unevenly between more and less experienced workers.
Time and Effectiveness
All this shows that AI can save time and improve efficiency. But the gap between perceived time savings and organizational measurement remains. The Adecco report stresses that although employees feel they save a lot of time, organizations are not measuring or observing it.
Some of that freed time may be spent on:
- checking AI output quality
- correcting errors
- prompt engineering
- simply meeting rising expectations for more output
Harvard Business School calls this “AI-generated garbage work”—tasks of validation, editing, and supervision of AI output. Some call it workslop, reflecting a vague but real problem emerging at the intersection of AI, time management, and productivity: indiscriminate or unreflective AI use can create a false sense of efficiency while actually reducing the value of our work and increasing the load on others.
Another MIT study notes that although 80%+ of companies have integrated AI tools into workflows, 95% have seen no measurable return on that investment. The issue is not just technological but a mix of strategy, processes, culture, human skills, and management metrics.
If organizations cannot measure the impact of freed time, they cannot convert it into real benefits (like fewer hours).
The Real Intelligence Is Still Human
Mario Garcés, founder of The Mindkind, notes that today’s generative models are powerful but limited in “real intelligence” (causality, sensory experience). Many experts agree: AI can enable reduced working time by automating administrative and routine tasks but does not yet replace intellectual or critical work requiring judgment, experience, and common sense.
New Value of Work
The capacity freed by AI raises questions:
What is the value of human work?
What do we do with more free time?
How do we redefine professions?
This is where shorter workweeks or reduced hours appear as realistic options.
If we reach general AI with human-level or superior capabilities, it could handle not just repetitive tasks but also parts of solution design, experimentation, simulations, and hypothesis generation. We could have mental teams working 24/7, sharing knowledge instantly. As Garcés says: “What one AI learns, all AIs learn.”
Will we be more productive with AGI? Yes, but it may rewrite the classic productivity problem (“we produce too little”) into a new one: how to manage excess productive capacity.
When AI takes over routine or administrative tasks, humans gain hours. Instead of simply loading more work, one alternative is reducing the workday. Without redesigning time management around AI, the result won’t be more productivity but more burnout, with people supervising machines for many hours.
A New Work Model Will Be Inevitable
AGI leads to an uncomfortable idea: the current model of work cannot be maintained when the notion of scarce human time disappears.
If production no longer depends on our hours, keeping long workdays becomes economically inefficient, organizationally incoherent, and competitively harmful.
Reduced-hours models will become a logical consequence of any system that aims to truly leverage available intelligence—human and artificial.
General AI will not only increase productivity; it will require new responsibilities in time management.
