As a CPO, I believe you have to understand the real value of each action, its cost and its security impact. Today, AI has become an almost mandatory lever in any product roadmap. That well-applied AI is a productivity accelerator is clear, and that it provides very powerful solutions we can implement very nimbly, too. But in some cases I’ve seen that, just to slap on the “AI” label, solutions are implemented with a high maintenance cost that really add little or nothing to the end customer.
That’s why, sometimes, reality is uncomfortable: not every application of AI adds value, and not every one deserves to be implemented. The CPO’s role is no longer just to prioritise features, but to discern rigorously where AI generates real, sustainable impact.
Tangible value for the product and the user
The first critical variable is tangible value. It’s not about adding AI because “it’s trendy”, but about answering concrete questions: does it improve conversion? does it reduce friction? does it increase retention? or does it simply add complexity without measurable impact?
The cost–return equation
The second layer is the cost–return equation. Integrating AI isn’t neutral: it involves costs of infrastructure, data, training, maintenance and model evolution. A CPO must assess whether the expected return justifies not only the initial investment, but also the operational debt it generates over time.
The product’s digital security
But there’s a third axis that’s usually underestimated: the product’s digital security. Adding AI widens the attack surface, introduces new data dependencies and can create risks of exposure or misuse of sensitive information. In critical products, especially in corporate environments, security isn’t optional: it’s structural.
We must therefore balance three simultaneous forces: business value, economic efficiency and security resilience. The right decision isn’t always the most innovative one, but the most sustainable.
In this context, AI stops being a technological layer and becomes a strategic product decision, where the key question isn’t “what can we do with AI”, but “what should we do with AI without compromising the product or its security”.
Because, in the end, the real differentiator isn’t using AI: knowing where not to use it also defines the quality of a CPO.
Are you implementing AI in your projects? Have the impact, the cost, the adoption and the security been assessed… or was it just “shoehorned in because it was the thing to do”?