ISFB Insight
When Machines Take on a Voice
June 3, 2026
Artificial intelligence is becoming part of the workplace lexicon. In the banking sector, it will likely shift tasks rather than eliminate entire job roles. It will make the fundamentals more apparent, forcing organizations to provide extensive training for their teams and requiring each employee to further develop their technical skills.
We tend to view artificial intelligence as part of the long line of automation that has transformed the workplace, and there is something reassuring about that comparison. As early as the last century, people were already seeking to streamline physical tasks; Frank and Lilian Gilbreth’s work on the analysis of movements aimed to eliminate the unnecessary in order to increase efficiency. The machine took over the physical tasks, while the individual retained speech, reasoning, and decision-making.
Today, AI no longer merely performs tasks; it is becoming part of our language. It writes, rephrases, summarizes, compares, and prepares decisions. Yet language is not just another tool: it is the very medium through which we think. When a machine becomes part of our language, it simultaneously becomes part of the way an organization reasons, makes decisions, and tells its story. In short, it becomes part of its organizational culture.
The task rather than the profession
People often wonder which jobs might disappear, and how soon. I am wary of figures that claim to predict the future. Here, it is important to distinguish between the short term—where we can make projections with an acceptable margin of error—and the long term, which falls under the realm of forecasting—and sometimes even a form of futurology, whether acknowledged or not. Forecasting is useful, but it must be taken for what it is: a body of work consisting largely of economic data that often lags behind what it claims to describe, and of collective imaginations—yet it has the merit of encouraging organizations to invest time in strategic thinking.
Finance is not simply a list of jobs that can be eliminated or retained based on the power of the tools. AI is already being integrated into certain processes, such as compliance, portfolio selection, fraud detection, and cybersecurity. It assists, filters, accelerates, and can improve the quality of work. However, it does not resolve the issue of assessing a situation. In other words, the debate is not about man versus machine, but about the task supported by the tool. In a bank, opening an account, recommending an asset allocation, assessing a risk, or taking responsibility for a decision remains a human endeavor, because it involves accountability, rules, and a relationship that is both personal and institutional.
The Paradox of Fundamentals
AI should not become the one-size-fits-all solution for every current challenge. Not all aspects of banking fall under the purview of AI. The majority relate to financial literacy, organization, management, training, law, or customer relations.
Tomorrow, however, in knowledge-based professions, simply producing content will no longer be enough. Machines will help us produce faster, more cleanly, and more accurately. Value will shift toward understanding, putting things into perspective, and interpretation. To learn about a subject, I can read a brief article in a free daily newspaper or seek out the seminal paper, followed by a few meta-analyses. I won’t understand the same thing. It will all depend on my sources, of course, but also on my ability to connect what I read to other knowledge, to see its limitations, to spot biases, and not to confuse a clear answer with a solid one.
AI will amplify the capabilities of those who already have a strong connection to knowledge, and will tend to undermine those whose connection to knowledge is less pronounced, in an environment where the speed of information dissemination can very easily mask superficiality. AI will not create skill gaps, but will sometimes make them more pronounced. Training can help mitigate these differences, provided it is not aimed solely at the most curious.
Toward a Skills Transformation
The question that organizations are openly asking themselves remains: should we move quickly, or proceed cautiously? If we move too slowly, we risk falling behind; if we move too quickly, we’ll make a lot of rookie mistakes. What seems certain to me, however, is that banks must begin training their teams on a large scale without further delay. Not just to write better prompts, but to understand how AI could transform banking work: customer relations, the quality of advice, operational processes, compliance, data security, legal liability, and even professional judgment. Employees, too, have an interest in taking the initiative, because AI will change their jobs, whether they chose it or not.
That is precisely the purpose of the summer training program offered to banking professionals, and which can also be implemented internally at ISFB member institutions to integrate the internal cultural dimension.
Training today starts with choosing a direction. A bank must be able to define what it expects from these tools, what it rejects, what it is testing, and what it keeps under control. Otherwise, everyone risks working on their own, sometimes using the organization’s tools, sometimes using their own.
Best practices will likely emerge through a series of trials in controlled environments, where it is permissible to test the technology without putting the entire institution at risk. Management must provide clear guidance on where AI is appropriate, where it is not, and what areas should remain subject to human judgment.
The Price of Relief
One final point strikes me as important, because it touches on what gives a piece of work its value. AI doesn’t just produce content; it standardizes it. We’ve all come to recognize these polished texts that all have the same flavor, the same words, the same syntactic structures. It provides access to a respectable average quality, but at the cost of flattening styles and reasoning. Yet what no longer has depth or distinction eventually loses its value.
AI will not replace humans. It will simply become part of nearly every tool used in intellectual work. And, like any tool, it says nothing on its own about the quality of the work produced. A hammer can be used to build straight lines or to damage a wall. AI raises the same question: used without perspective, it will make us faster and likely more superficial; used with discernment, it will help us better compare, verify, formulate, and decide. This is also what makes banking training even more necessary than before: the easier access to information becomes, the more we need to know how to understand it, contextualize it, and assess its value.
This may be the least spectacular task ahead of us once we finally stop talking about AI and refocus on the fundamentals of our professions. It will be the most demanding but also the most rewarding: using our tools without ceasing to think, knowing when to slow down, staying attentive to our relationships, and not falling into the trap of taking the easy way out.
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