TL;DR
Generative Engine Optimization was about getting your financial institution recommended inside AI answers. The next shift is already forming. AI agents are about to move from recommenders to transactors, opening accounts, moving funds, and completing applications on behalf of the people who used to be your customers. When the buyer stops being a human clicking on a form and starts being an agent acting on a human’s behalf, trust becomes the new battleground. This post is about what comes after GEO, why agentic trust is the layer that will decide winners and losers, and what financial services leaders should be thinking about in the next twelve months.
I’ve spent a lot of time this year on stages, in meeting rooms, and in this blog talking about GEO. The premise has been consistent. Search is being replaced by answers. SEO is being replaced by Generative Engine Optimization. And the institutions that figure out how to be named, cited, and recommended by ChatGPT, Perplexity, Google’s AI Overviews, and Bing Copilot are the ones that will win the next decade of discovery.
That is still true. But it is also already incomplete.
The discoverability era is ending sooner than anyone planned
When I walked through a large financial institution’s AI discoverability snapshot with their team earlier this year, the finding that hit hardest was simple. When a prospective member asked an AI assistant, “What are the best credit unions in X market?”, They did not show up. Not because they have a bad product. Not because they lack scale. They are the eighth largest credit union in Florida. They did not show up because the AI had not yet decided they belonged in the answer.
That moment, a real person asking a real question and getting a recommendation that excludes you, is the moment GEO was built for.
Here is what is interesting. That moment is already evolving. The next prospective member will not just ask for a recommendation. They will ask the AI to open the account. Book the appointment. Start the refi. Move the money. And somewhere between the question and the answer, a decision is going to get made about which institution gets the business.
GEO gets you on the shortlist. Agentic trust decides who gets chosen once the agent is the one acting.
What agentic trust actually means
Agentic trust is the set of signals, integrations, and reputational indicators that an AI agent uses to decide which financial institution it will transact with on a human’s behalf.
It includes some things you already care about.
Your API posture and whether an agent can actually open an account through a standardized interface without hitting six dead ends. Your identity proofing and whether the agent can verify the human it represents in a way your systems accept. Your rate sheet transparency and whether the agent can find current pricing without scraping a PDF from 2023. Your auditability and whether an agent action can be traced back to a consenting human with a clean paper trail.
It also includes some things you probably don’t care about yet but will.
Your llms.txt file and what it actually says about which agents are allowed to transact with you. Your machine-readable policies, including fees, minimums, and restrictions. Your agent-to-agent dispute resolution, meaning how your institution handles a disagreement between your systems and a customer’s agent. Your explicit agent compatibility and whether OpenAI, Anthropic, Google, and the emerging financial agent platforms list you as a verified counterparty.
None of these are optional in an agentic world. They are the new vault door.
Why the banks and credit unions who figured out digital first will win this one too
There is a comforting pattern in financial services. The institutions that took digital banking seriously in 2010 are the ones that took mobile seriously in 2014, that took API banking seriously in 2018, and that took AI seriously in 2024. The technology moves. The muscle of moving with it stays roughly the same.
Agentic trust is the next rep in that same workout. The institutions that already have clean APIs, structured policies, and a real identity layer have a massive head start. The ones that are still manually keying wire instructions into a screen that was last updated during the Obama administration have a problem that is going to get obvious fast.
This is not a technology problem at its core. It is an operating discipline problem. And the financial services leaders who have been preaching operational excellence for years are about to get a very visible report card.
What this means for marketing and strategy leaders
If you lead marketing, growth, or strategy at a bank or credit union, three things are worth doing in the next ninety days.
First, audit your agentic readiness, not just your AI visibility. Your GEO score tells you whether an AI will recommend you. Your agentic readiness tells you whether an AI will transact with you. Those are different scores. Measure both.
Second, get honest about your API surface. If your account opening flow cannot be completed through a programmatic interface by a trusted partner agent, that is a go-to-market problem, not a tech problem. The same applies to loan applications, funds transfers, and appointment booking. The path from agent to outcome should have fewer than five human handoffs. Today, for most institutions, it has fifteen or more.
Third, start publishing machine-readable facts. Your rates. Your eligibility criteria. Your fee schedules. Your product comparisons. The agents that will be choosing between you and your competitors will not be browsing your website like a human. They will be ingesting structured data and deciding. Make sure you are giving them something to ingest.
What comes next
Inside the next twelve to eighteen months, I expect three things to happen in a visible way.
The first is a public agent registry for financial services. Think of it as the modern equivalent of the NCUA or FDIC directory, but curated by the AI platforms and focused on which institutions can be transacted with programmatically. If you are not on it, you will be invisible to agents in a way that makes today’s GEO gap look mild.
The second is a new category of agentic CAC. Cost per acquisition via consumer AI agents will become a real line item on marketing dashboards. Early numbers will be wildly variable, which means early movers will get to set the benchmarks that everyone else will be measured against for a decade.
The third is the first high-profile agentic trust failure. Some institution, probably one you have heard of, is going to let an agent complete a transaction it should have blocked, or block one it should have allowed. The fallout will push agentic trust onto every board agenda in North America overnight.
You can prepare for all three now. Or you can wait until the first headline lands and scramble like everyone else.
The bottom line
Being recommended by AI was round one. Being trusted to transact by AI is round two. The institutions that treat this as a continuation of the GEO work they have already started will adapt in stride. The ones that treat recommendation as the finish line are going to discover, probably painfully, that the race just got longer.
I am going to be writing more on this over the next several weeks, including a look at what agentic readiness actually scores against, a walk-through of the first three agentic pilots every credit union should run this year, and a closer look at what happens when the “member” in your member experience is sometimes a bot acting on a human’s behalf.
If you lead a financial institution, the work you did on GEO was not wasted. It was the prerequisite. Now the real race is starting.
Kevin Farley writes about AI visibility, AI readiness for financial services, and the future of marketing in regulated industries. Read more on the blog.