Businesses often talk about the benefits of AI, particularly in terms of productivity and revenue, as if they were the logical outcome of successfully adopting the technology. We imagine that fast tasks, simpler steps, or content produced in a matter of moments are enough to take the business to the next level, which will be reflected in its financial statementsbecause, let’s not kid ourselves, that is the ultimate goal.
This vision has accompanied every technological wave and is logically repeating itself today with AI. However, when we look at how these gains appear and how they are or are not captured by the organization, we understand that they are only valuable in terms of how we decide to use them, but to do that, we first need to have decided something.
In short:
- AI-related gains only generate value if they are part of a deliberate and focused strategy: without a clear intention, they remain potential or are scattered without any tangible effect.
- Organizations are repeating the same reflexes with AI as they did during previous technological waves, assuming that benefits will automatically appear, when in fact they require active management.
- The time freed up by AI can be used in various ways (training, innovation, quality, workload reduction, productivity), but explicit choices must be made to avoid counterproductive uses.
- The lack of clear governance on the allocation of productivity gains can lead to conflicts of interest between employees, managers, HR, and the business, to the detriment of overall efficiency.
- It is not the technological tool that creates the impact, but the way in which the business chooses to use the leeway it generates, in particular by managing the use of the time freed up.
Focus on gains rather than losses
In the collective unconscious, technology evokes productivity gains, lighter workloads, fast processes, and the assumption that all of this will ultimately consolidate to produce tangible gains. And when I say tangible gains, I mean things that ultimately materialize in the books.
This is a reassuring belief because it gives meaning to the investment and allows us to imagine collective progress resulting from many individual advances. However, when we examine what is happening in teams, we see a multitude of scattered situations, proven and relative successes that we can identify but are unable to capture the fruits of. Employees move forward individually, teams much less so, and the organization sometimes not at all. This is not a new issue.
But capturing the gains made possible by technology, in this case AI, but this applies to anything that promises time and productivity gains, does not happen by chance and requires decisions and, above all, intentions. Without this, and without going so far as to say that they evaporate, they follow a random path that may not necessarily lead them where the business would like them to go. The history of technology, whether collaborative, office-based, or other, has already shown this to be almost systematic.
AI confirms this principle, not because it has a particular nature, but because businesses reproduce the same reflexes with it as they did with previous waves.
An unallocated gain does not always benefit the right people
A gain is therefore only valuable if it meets a choice. An employee can complete a task more quickly, a team can be more efficient in a sequence, content can be produced in a few minutes rather than several hours. We save time, but until that time saving is matched by a decision, individuals and groups cannot be sure of benefiting from it. Technology helps us to create potential value, but without a decision on what to do with that potential, it will often remain just that—potential—or will not be transformed into what we expected.
It is therefore necessary to anticipate what we want to do with this potential value, which is somewhat similar to the situation described by Parkinson’s Law: if you don’t decide what to do with the time you’ve freed up, others will do it for you (Are you familiar with Parkinson’s law on how your employees manage their own time and productivity?). This is exactly where AI comes in: there will be a “battle” over the use of the time saved between employees, managers, and the business, and if there are no rules, with no intention of what we want to do with the productivity gains, they may not be allocated in the best way, depending on whose point of view you take.
Once again, I insist on this subject, which I believe should even be a real issue in terms of AI governance, because once we are faced with a fait accompli, once we realize that we have succeeded in appropriating the technology in a productive way (AI adoption does not replace productive appropriation), it is often already too late.
Gains can take many forms, but they must be clearly defined
The way in which gains from AI can be transformed into tangible benefits, sometimes into assets, can lead in different directions, which is why it is important to plan ahead.
We can decide to devote this time to learning or training in one area or another. The time freed up from administrative tasks can help us to train in our core business or further improve our use of AI. In the same vein, this time can be used for innovation.
Another approach is to use this time to improve the quality of the work produced by reinvesting it into the work itself. Writing with greater care, refining an analysis, improving a response, anticipating a need, all these actions require a little more time and attention. We don’t produce more, we produce better.
A third approach is to lighten the overall workload, take this time to breathe, avoid cognitive overload, a bit like in a QWL approach. Some even suggest that if the promises of AI are kept, we could move to a 4-day week.
When the business lends itself to it and there is demand, these gains can be monetized by reinvesting in production capacity. It’s not about producing more for the sake of producing more, because without solvent demand, and therefore the ability of marketing and sales to sell this excess capacity, it serves no purpose and can, on the contrary, exhaust staff and even lose money Technologies sell productivity, but businesses want revenue. If we are not talking about productive functions but support functions, this will, on the contrary, increase the quality of service, as they are generally completely understaffed.
Finally, in the worst-case scenario, which is not uncommon, this time can be captured by a manager panicked at the idea of seeing their teams idle and be transformed into reporting, meetings, useless tasks, and end up in bureaucratic inflation.
The Harvard Business Review recently echoed this issue by showing that time saved is not an advantage until the team or company has decided how it will be used (How Is Your Team Spending the Time Saved by Gen AI).
Of course, there is no perfect solution. It can vary depending on the team, its business, and even vary over time depending on the context or the person. There is no perfect solution a priori, but the absence of intentional distribution can only be problematic, a source of confusion and even tension.
Unallocated gains backfire on the organization
As we have just seen, the use of time saved without deciding what to do with it can backfire on the organizationbecause if it does not decide for itself what it wants to do with it or put in place a governance system that allows managers to decide how all or part of it is allocated, there is a risk of ending up in situations where one person decides in their own interest and, more often than not, to the detriment of others.
If employees use it to slow down or take breaks, businesses and managers may not get what they want out of it.
If managers use it to artificially “occupy” their teams to the detriment of training and workload management, HR and the business are likely to take a dim view of this.
If HR decides to use this time for training and quality of life at work while customers are waiting to be served, the business and managers will be penalized.
The list of such examples is long and tells us only one thing: the worst situation is one where the situation is unclearand where there will be competition over the use of this time, where everyone can see how it is being used and where, in the end, the business risks not reaping any benefits or not those it would have liked to prioritize at a given moment.
As I said, this is a governance issue that requires a cross-functional approach, as the number of stakeholders involved can be significant.
Manage the use of time rather than the tool
Ultimately, managing gains means accepting that technology does not create impact, but only margins that can be used to create impact.
In fact, impact arises when a business or team intentionally decides what it wants to do with these margins, and when a leader takes responsibility for that choice. An organization that knows what to do with a gain progresses; conversely, it remains at the starting line.
The issues that AI confronts us with, or will confront us with, remind us that without guidance, progress is very relative and that an organization does not take advantage of its transformation because its employees work faster, but because it knows what to do with the time they free up. A leader who manages these gains well does not control technology, but rather the use of time.
Bottom line
The gains from AI mean nothing until they are matched with intent. They only become a lever when the organization decides what it wants to do with every minute saved. The time saved is a kind of fuel, but it is up to the business and its managers to decide which engine they want to run it with and in which direction they want to go.
To answer your questions…
The productivity gains brought about by AI do not automatically translate into visible results. Speeding up tasks or simplifying certain processes only has a real impact if the business decides how to reuse this time or these resources. Without clear guidance, the benefits are lost in day-to-day operations. To make them measurable, it is necessary to define in advance where they should be reinvested, whether to improve quality, accelerate projects, or support growth.
The promises of AI are often based on the idea that increased efficiency will automatically generate value. In practice, without strategic decision-making, the gains remain diffuse. They can be absorbed by routines or diluted within the organization, preventing them from being converted into savings or revenue. Benefits only appear when their use is guided by a clear intention. It is therefore essential to direct these gains to prevent them from remaining theoretical.
Past technological waves show that adopting a tool is never enough to produce a lasting impact. As with digital technology and automation, AI only generates results if the business organizes the exploitation of the gains. History reminds us that effects are not automatic: they depend on explicit choices about how to use the technology. This perspective confirms that value comes less from the technology itself than from how it is integrated and managed.
A business that allows AI gains to spread without guidance misses out on the opportunity to derive real value from them. The benefits may remain invisible, be scattered across teams, or reinforce existing practices without improving overall performance. The lack of decision-making often leads to a dilution of effects, making it difficult to measure impact. By reacting rather than directing, the organization deprives itself of an accessible strategic lever.
To guide AI gains, the organization must define a clear objective: cost reduction, quality improvement, faster turnaround times, or development of a new activity. This decision helps avoid the natural dispersion of benefits and ensures their conversion into measurable results. The next step is to allocate the resources saved to these priorities and monitor their impact. This intentionality transforms potential gains into real operational leverage.
Image credit: Image generated by artificial intelligence via ChatGPT (OpenAI)
Related articles:
Who is handling your artificial intelligence projects? Probably not the right people.
How does digital transformation look like #1 : the visible part
Wrong assumptions in digital transformation : my Social Business Forum Presentation
Talents have gone digital. HR didn’t.
Are HR Ready For New Horizons ?
“E-learning is about knowledge acquisition, not about using it at work”. William Peres
