AI and Business Development: panacea, placebo or poison pill?

The sales departments of banks, financial advisory networks and insurance advisory networks are investing increasingly in artificial intelligence. But the real competitive advantage will not depend on the tools adopted, but rather on the ability to turn technology, method and trust into value that clients cannot replicate on their own.

The underlying narrative is simple: AI will make advisers, bankers and insurance professionals more effective. That may be true. But the more interesting question is another one: what will happen when the same tools also become available to clients? BCG estimates (Global Wealth Report 2026) point to potential increases of up to 20% in revenues and 30% in operational capacity — but those who possess a tool do not win: those who develop a method for using it better and earlier than others do. Hence three possible developments: panacea, placebo or poison pill.

Panacea

AI becomes a true panacea when it stops being merely an application and becomes a system: when processes, skills, coaching and management models are rethought. Advisers arrive at meetings better prepared, with more time for the relationship. Training also changes in nature — continuous, on demand, capable of simulating complex clients and thorny objections. Professionals are not replaced: they are empowered, but only if AI is accompanied by cultural and organisational transformation. Otherwise, the second scenario emerges.

Placebo

Probably the most widespread and least discussed scenario: AI makes many activities faster — better emails in less time, faster presentations, documents summarised in a few minutes — all useful, but not necessarily transformative. If AI disappeared tomorrow, how much would qualified appointments, conversion and retention really change? If the answer is “not much”, the placebo risk is real: the organisation perceives innovation, but distinctive results struggle to materialise.

Poison Pill

The greatest risk is neither a technological error nor a system hallucination, but uniformity without judgement: if everyone uses the same tools without questioning why, average quality rises but differences diminish. There is a risk of producing less distinctive professionals — a paradox in a sector where trust is a competitive lever: trust rarely arises from homogeneity, but from the ability to develop and express professional judgement.

Method

And this is where the real test emerges: making the most of heart and mind, understood as method and trust. How solid is the method? How alive is trust in one’s own profession and clients? If these two variables are weak, AI does not replace them: it anaesthetises them.

AI’s contribution to method can be extraordinary, but it is not synonymous with using a tool: it is the ability to formulate the right questions before seeking answers. Two professionals using the same platform for the same activity obtain different results: the difference depends on the quality of the reasoning that guides it.

Trust

For years, trust was a consequence of technical expertise: those who possessed more information became a point of reference. Today, access to information has been democratised, and clients are increasingly well prepared. This does not reduce the value of advice, but changes its foundation: trust will be based less and less on privileged access to information and increasingly on the ability to give it meaning. Reliability, expertise, integrity and empathy are needed. The real challenge will not be to build AI-supported advisers, but professionals who use it to refine their professional judgement and, through that judgement, generate trust.

Conclusion

For this reason, the competitive advantage in the coming years will not belong to those who adopt AI first, but to those who know how to integrate it with what no technology can automate: professional judgement, responsibility for decisions and the ability to generate trust. In a market where clients, advisers and competitors will have access to the same tools, the difference will not be artificial intelligence: the difference will remain profoundly human.

And that is why, in the end, AI will have been neither a panacea, nor a placebo, nor a poison pill for anyone: it will have been exactly what each professional chose to make of it. Those who understand this first will not simply have adopted AI before others: they will have built, with it, something that, at least for now, no model will be able to replicate on their behalf.