We show how AI shifts power and responsibility.
We ask who is truly at the wheel.
We argue that AI should support and that people remain the owners.
ABN AMRO has announced that thousands of jobs will disappear by 2028. A significant part of this is linked to automation and the deployment of artificial intelligence. Roles in customer contact, support, and file processing are particularly affected.
At the same time, research shows that only a small minority of artificial intelligence projects actually lead to noticeable revenue growth or cost savings. Often, an order of magnitude of around five percent is mentioned as truly breaking through; the vast majority remain stuck in experiments, pilots, and partial solutions.
On the one hand, a bank that firmly states: “technology is taking over, therefore jobs are disappearing.” On the other hand, figures showing that most artificial intelligence projects are far from delivering what they promise.
In that field of tension, you stand as a constructive leader. Not only with a financial issue, but above all with a relational issue: what does this do to the relationship between the board, the organization, and its people?
Surface level: a logical story
On the surface, the story is orderly and rational.
The bank wants to lower its cost-income ratio and increase profitability. Processes must become simpler, less manual, more standardized. Digital services and artificial intelligence form the core of that course.
Support work is relatively easy to standardize. So that is where the biggest impact falls. The organizational model follows the logic of the technology: if systems take over more work, fewer people can remain.
This is the classic efficiency story. Technology makes work redundant. The organizational chart becomes smaller. Executives present artificial intelligence as a lever to work faster, cheaper, and more accurately.
But that only describes the surface level: figures, charts, and presentations.
Undercurrent: uncertainty and the AI alibi
At the deeper level, something else is happening.
Artificial intelligence as an alibi
By linking layoffs to technology, a sense of inevitability arises. “It’s not our choice, it’s the spirit of the times.” That softens the visible responsibility of the board, but increases existential uncertainty among employees. If the cause lies outside everyone, where is influence still possible?
Symbolism of modernity
Artificial intelligence is not only a set of models and systems. It is also a symbol. A board that says “we are future-proof” shows that it dares to cut, dares to digitize, dares to innovate. In the market, that is read as decisiveness. Within the organization, it is also read as distance.
The gap with the reality of projects
In many organizations, only a small minority of artificial intelligence projects truly prove meaningful. The technology works on paper. The pilot runs. But real integration into daily work stalls. Yet in the narrative around reorganization, it is presented as if the technology has already amply proven that it can take over jobs on a large scale.
Scarcity and control
In sectors under pressure, you often see a retreating movement: more control, more risk avoidance, more emphasis on measurable outcomes. Artificial intelligence fits well within that. Everything becomes data, models, and dashboards. The softer questions—about meaningful work, loyalty, and trust—fade into the background.
In this way, artificial intelligence becomes both a technical promise and a psychological shield.
What does this ask of you as a constructive leader?
As a constructive leader, you have a different task than merely ensuring that a reorganization proceeds smoothly. You steer not only on figures, but also on underlying relationships and patterns.
Now – what you can do
Make an explicit distinction between cost reduction, strategic reorientation, and genuine technology-driven change. Do not name artificial intelligence too early as the reason for layoffs. That requires courage, because it makes the choice visible again at the level of the board.
Connect technology to the concrete work. Which tasks disappear? Which tasks shift? Which new forms of work emerge? How does the craftsmanship of your people change? How does their dignity in work change?
Use the deployment of artificial intelligence as a reason to start a conversation about culture. What kind of organization do you want to be when more work is done by systems? What role will judgment, dissent, and the ability to draw moral boundaries have?
Later – only once the foundation is in order
Rolling out artificial intelligence applications on a large scale only makes sense when processes are clear, data is in order, and the style of governance is sufficiently mature. Without that foundation, you mainly increase complexity and pressure, without sustainable value in return.
Not to do
Do not use artificial intelligence as a label for classic cost reductions. Do not continue experiments without a clear purpose, ownership, and evaluation. And avoid the idea that purchasing technology equals integration into daily work. The real change takes place in roles, relationships, and routines.
Risks and boundaries
Breach of trust
When employees experience that technology is used as an excuse for decisions that were already fixed, trust quickly erodes. That touches the core of the psychological relationship between organization and individual. You can limit this by clearly naming which decisions you take yourself and which are truly driven by technological possibilities.
Overestimation of promises
If the organization counts on savings that are not realized in practice, a gap emerges in the story. Then the promise of artificial intelligence becomes a source of disappointment. You can limit this by adopting modest assumptions, phasing implementation, and openly discussing scenarios in which results disappoint.
Erosion of professional identity
When support professionals mainly hear that their work will eventually be taken over by systems, engagement declines even before the technology truly works. You can reduce this by designing new forms of craftsmanship together with them and offering serious development paths.
Open ending
Artificial intelligence changes organizations, including banks. But the story that technology takes over jobs is only part of the story. At least as important is how you, as a constructive leader, deal with the relational consequences of your choices.
The question that lingers is this: when you speak in the coming months in board or executive meetings about artificial intelligence and costs, which sentences would you only be able to utter with difficulty? And what does that say about the next step you, together with your people, have to take?
Rene de Baaij