When AI Becomes the First Conversation: Rethinking How Fintechs Buy and Sell

By Koen Vanderhoydonk, CEO at The Connector.

Something is changing in how fintechs sell, and how buyers buy

I have spent a lot of time speaking with fintechs, technology providers and people on the buying side of the market. What I am seeing is not simply another shift in digital marketing or another new sales tool. AI is starting to change the conversation itself.

The traditional journey was relatively straightforward. A buyer identified a problem, searched the market, visited websites, spoke to vendors, attended an event, issued an RFP and eventually made a decision. Today, much of that process can happen before a vendor ever knows the buyer exists. A buyer can ask an AI assistant which providers can solve a particular problem, how they differ, what the risks are, and which products integrate with a given environment. The answer can become the starting point for the shortlist.

That changes the rules: the buyer no longer starts with the vendor.

One of the most interesting observations I hear from companies in the market is that sales are already being influenced, and in some cases initiated, through chatbots and AI assistants. That matters because buyers no longer necessarily look for the company with the shiniest website or the most polished marketing message. The question becomes whose information actually answers the question.

This is a fundamental change

If an AI system is asked to explain how a particular fintech problem can be solved, the providers that surface are likely to be those whose available information is clear, detailed, and relevant enough for the system to understand. The buyer may arrive at a vendor because an AI conversation identified a specific capability, use case or answer, rather than because the vendor won a search-engine ranking.

Traditional SEO therefore feels less sufficient

Publishing another article titled "10 fintech trends you need to know" isn't enough. Vendors increasingly need to explain what they do, what problem they solve, how they solve it, where it works, where it doesn't, and what the real-world experience looks like. In other words, less marketing language, more substance. This also changes what good fintech content looks like.

I am seeing more value in formats that allow people, and increasingly AI systems, to understand a subject in depth. Long-form interviews, podcasts, detailed case studies, technical explainers and genuine conversations can provide something that a stream of generic, AI-generated blog posts cannot: context.

A good podcast, for example, can spend forty minutes discussing one problem from several angles. It can contain nuance, disagreement, practical examples, and the kind of language people actually use when they understand a subject.

That makes it useful not only to the listener, but potentially to the wider AI information ecosystem.

There is an important warning here, though. If vendors learn how AI systems work, they can also learn how to optimise what those systems see. That creates a new form of competition. It is no longer simply who has the best product, but who is best represented in the information layer through which buyers discover products.

The market's challenge, then, is not to replace SEO with "AI optimisation" and repeat the same game. It is to create information that deserves to be found.

The vendor side is changing too

For vendors, this means the sales process increasingly starts before the first sales conversation. A fintech may have a brilliant product, an experienced team and strong references. But if the information available about that company is thin, generic or overly promotional, an AI-assisted buyer may never get far enough to discover those strengths.

This puts pressure on vendors to become much more explicit about their expertise. What problem are you actually solving? For whom? What does implementation involve? What are the limitations? Which integrations matter? What evidence supports the claims? What happened in real implementations? The best vendor content may consequently become less polished and more useful. That is an interesting reversal for an industry that has spent years perfecting marketing language.

And then the buyer starts using AI to choose

The bigger question comes when AI moves beyond discovery. Imagine an RFP drafted by AI, based on an AI-assisted analysis of the buyer's requirements. It is sent to a group of vendors identified through AI research. Another AI system then summarises and compares their responses. It generates scores, highlights differences, and produces a shortlist. It is efficient. It is scalable. It can save enormous amounts of time. But a strange possibility hides inside this efficiency: buyer AI talking to vendor AI.

And if that happens, where does the human part of the decision fit in?

A procurement process can become extremely sophisticated while still missing something important: context. Why does one organisation work well with another? How does a team behave when something goes wrong? Can you trust the people who will actually deliver the solution?

What is not written in the RFP? These are difficult things to score.

The human conversation becomes different, not necessarily bigger

This does not mean the answer is simply to have more meetings. In fact, the opposite may be true.

Most people are already overloaded. Buyers don't have time to meet every fintech that appears on an AI-generated shortlist. Vendors cannot have meaningful conversations with every potential buyer either.

So perhaps the future is not about increasing the number of human interactions. It is about making the interactions that remain more valuable. This is where trusted intermediaries may have an increasingly interesting role. Someone who genuinely understands the market can help filter the noise, provide context around multiple vendors and connect the right people when there is a genuine reason to have a conversation. In a sense, the human part of the process can be compressed, not eliminated.

But that creates another question. Whom do we trust to provide that context, and how transparent are they about their relationships and potential biases? That question matters just as much as the technology itself.

AI is changing where trust begins

This may be the real shift we are witnessing. AI is not simply changing fintech products. It is changing discovery, positioning, marketing, procurement, and ultimately how trust is established between a buyer and a vendor. The first conversation may now happen with an AI assistant. AI may create the shortlist. AI may write the RFP. AI may analyse the answers.

But eventually, someone still has to decide whether they trust the people behind the product. That does not make AI less important. It makes the human layer more deliberate.

For fintechs, the challenge is to create genuinely useful information. Information that explains rather than advertises, demonstrates rather than claims, and gives both people and machines enough context to understand what the company really does.

For buyers, the challenge is different: to use AI without outsourcing judgment completely.

And for the market as a whole, the biggest question remains unanswered. How do we combine the extraordinary breadth and efficiency of AI with the context, trust and human understanding that have always been at the heart of doing business? I am watching that transition closely. Not because I have the answer, but because the way buyers and vendors find each other is changing before our eyes. The next chapter may not be AI replacing the conversation. It may be AI deciding which conversations are worth having.