Why AI should be more than expensive lubricant for an old system.
In many boardrooms, AI is talked about in terms of optimization: faster processing, fewer errors, greater efficiency.
That is understandable and at the same time exactly where it goes wrong.
The real power of AI is not in fine-tuning the existing.
AI only becomes strategically interesting if you are willing to redraw the playing field itself: different services, different revenue logic, different way of organizing.
Without a vision for this, AI gets bogged down in “doing better what we’ve always done.”
Then it becomes expensive lubricant for a system that actually needs replacing.
And meanwhile, the risk of even more fragmentation grows: each team builds its own AI solution, without necessarily improving the whole.
This second article in the series builds on “AI in the boardroom: no improvement without vision” and raises the bar: from optimization to redesign.
This article is part of an inspiration campaign for directors, as part of the executive leadership program – Innovation & Transformation with Data and AI, developed in collaboration with the Erasmus Centre for Data Analytics, part of Erasmus University Rotterdam. The central message: AI is not a techno thingy, but a matter of vision, strategy, choices and leadership in the boardroom.
Optimization is comfortable – and a pitfall
Many of the AI initiatives start close to what already exists.
What we already do simply needs to be more efficient:
- a few minutes faster per file,
- a few percent fewer errors,
- a few fewer FTEs needed in the back office.
It certainly delivers. But strategically little changes.
The customer journey remains virtually the same. The role of the professional does not really change.
The business or service model is not fundamentally revised.
That’s precisely a trap:
you invest heavily in technology to make an old design run just a little smoother,
while competitors or new players use AI to change the game itself.
AI as an engine for different design
A keen AI vision goes beyond “how can we optimize our existing processes?”
She asks questions on a different level:
- If we were starting over today, how would we design our services with AI as a given?
- What parts of our current chain could we design completely differently, or even skip?
- What new forms of value can we deliver to customers, citizens or partners as AI now enables what was previously impossible?
Consider:
- proactive service rather than reactive handling;
- custom decisions that do scale;
- ecosystems in which data and AI make multiple parties smarter at the same time;
- completely new proposition forms (e.g., “as-a-service” models) that would be unaffordable or unmanageable without AI.
Without such questions, AI remains neatly on the margins: useful, but not strategic.
Fragmentation: each his own AI toy
Another reason why vision is indispensable; without a common compass, AI becomes an accelerator of fragmentation.
Departments, business units and staff clubs are getting down to business themselves:
- The HR department buys an AI tool for recruitment,
- customer service is experimenting with a chatbot,
- finance works with predictive models,
- operations is building its own planning tool with AI.
Each solution can be fine on its own.
But if they are not conceived from one design and one set of principles, an AI patchwork results:
- different data definitions,
- different standards of explainability and risk,
- various assumptions about the roles of humans and AI.
The result:
more complexity, more dependence, more vulnerability and no coherent benefit.
A true AI vision breaks through that.
It says not only what you do want, but also what you no longer accept:
island solutions with no contribution to the whole.
So what does a sharp AI vision include?
From this disruptive perspective, the building blocks of your vision shift.
- Horizon explicitly include
Not just, “How do we make current processes more efficient?“
But also, “What new services, roles or business models become possible with AI and which of these do we want to claim?” - Conscious choices about redesign
- What customer journeys will we fundamentally redesign over the next 3 years, using AI as a starting point?
- Which internal chains are so outdated that optimization is no longer enough?
- Architecture over point solutions
- What principles apply to al AI applications (data, ethics, human role, explainability)?
- How do we ensure that new initiatives strengthen rather than further fragment the whole?
- Role of leadership in the “new story”
- AI requires administrators not only to manage costs and risks, but also to be imaginative: sketching a story of what working, learning and value delivery will look like in their domain.
Crucial insight for leaders
I. From AI as optimization to AI as a design choice
The crucial tipping point. As long as AI is seen primarily as a tool to improve the existing, the impact remains limited. Only when you use AI as a design choice to reshape your services, operating model and role in the ecosystem does it become strategically relevant.
That takes courage in the boardroom:
- to recognize which parts of the current system are actually “out of development.”
- Not to let every AI budget evaporate into minor optimizations;
- to reserve space for experiments that are not about half a percent efficiency, but about a different kind of value.
II. AI as a touchstone for your ambition
AI painfully reveals how ambitious you really are as a board. Do you use it primarily to make the existing system perform a little better? Or do you dare use it to redesign that system itself, for the benefit of customers, employees and society?
With that, AI becomes a mirror: does it reflect an organization that merely optimizes its past,
or an organization that designs its future?
So the question for the boardroom is not just “what can we do with AI?”,
but mostly:
- If we use AI primarily to make the existing a little more efficient,
what opportunities for truly different thinking and organizing are we consciously missing now and dare we take that responsibility?
This article is an invitation to no longer see AI as something that “happens somewhere in the organization,” but as a touchstone for leadership in the boardroom. The inspiration campaign and leadership program we are developing with the Erasmus Centre for Data Analytics, part of Erasmus University Rotterdam, focuses precisely on this shift.
