At this point, few companies will not have experimented with AI. Some, even, have been using it effectively for years.
Nor is it strange to see how some have incorporated the use of AI into their internal governance and compliance frameworks, showing a clear concern for ensuring a legal, responsible, and diligent use. “One must use it, but one must use it well,” they say.
And, in this scenario, voices are beginning to be heard that maintain that artificial intelligence does not necessarily reduce work: in many cases it is reorganizing, accelerating and -even- intensifying it.
Especially in these recent times, in which the adoption of AI is celebrated as an automatic productivity lever, it seems appropriate to open the debate on the future of business productivity in the AI era and its impact on the workload for employees.
The reverse of the promise
The business argument used to foster the internal use of AI has not varied: if processes are automated with AI and technical tasks are accelerated, workers will have more time for higher-value activities. The logic seems impeccable.
But qualitative data collected in recently published research questions these approaches and points to a more complex reality: when a technology increases the capacity to do, it can also broaden expectations about the volume of tasks that can be performed with such resources and, in particular, the speed to complete them.
The organizational effect
The investigations point to three clear mechanisms of workload intensification.
First, tasks are expanded: which is summarized in that there are people who before having Artificial Intelligence tools at their disposal did not assume certain functions, but with it they start to do so because AI lowers the entry barrier. The case of programming or drafting legal documents, for example.
Second, the line between work and rest blurs: what before were breaks now turn into micro-times utilized to continue producing (the anxiety for a last prompt).
Third, achieve a state of permanent multitasking: employees most intensive in the use of AI usually keep several streams open at once, perform more checks and suffer greater attentional fragmentation.
The debate is not limited to a mere question about whether we are more efficient, but whether we are facing a genuine change in the architecture and management of work.
And if that happens without explicit rules, there is a clear risk that organizations confuse enthusiasm in AI adoption with sustainability in its use.
The illusion of profit
In this reflection, a paradox emerges: the easier it is to do something, the more likely it is to be done. And the more it is done with AI, the more a new standard of speed is normalized.
A standard that does not require to be imposed by direct employer mandate; it is enough that it becomes habitual.
In the case of companies, both public and private, if it is promoted that each employee self-regulates in their use of AI, instead of designing a "common good practice in the use of AI", it is most probable that a tendency towards an intensive and disordered use of the technology will emerge.
The effect achieved is the opposite of what is sought: the initial time saving is consumed in the performance of new tasks and microtasks, accompanied by a feeling of anxiety for not meeting the new expectations of speed in their execution.
The need of rules
In this case, it does not seem that the solution involves stopping the adoption of AI, but rather it is necessary to provide it with criteria. And integrate its use into a human structure where limits, priorities, and times are established.
Without that, technology will tend to push employees towards continuous availability which will cause the opposite effect: erode the quality of employees' judgment and increase the wear and tear of the teams.
A question of substance
It has already been demonstrated that with AI we can do more things and more quickly. The underlying question that arises when questioning its current use is what organizational and human cost that “more” has.
If uncontrolled use causes more pressure and more fatigue, the productivity improvement will not be such; or it will be unsustainable.
In light of all the above, perhaps we should consider whether the debate about AI in the company should shift from immediate performance to corporate design. Because it could happen that the true -and longed-for- competitive advantage does not come only from the fact of using AI, but from knowing how to regulate it internally to achieve the promised multiplier effect.
And it is at this point that many organizations still have not begun to think with sufficient seriousness.
ABOUT THE FIRM:
Francisco Pérez Bes is deputy of the Spanish Data Protection Agency. In addition, he was a partner in the Digital Law area of Ecix Group and is former Secretary General of the National Cybersecurity Institute (INCIBE)