AI Agents Rewrite the Playbook for Community Banks and Credit Unions

We recently engaged in an AI-assisted exercise to research challenges and pain points across 14 operations that are common to community banks and credit unions across the United States. We wanted to match the amazing AI agents we’re creating at Soaring Titan to the real world challenges of people serving these critical institutions every day.

To accomplish this, we developed a framework for AI to follow that broke down operations like commercial lending, consumer deposits, treasury, and mortgage into their sub-functions and roles. AI automagically evaluated ideas against our competencies and then filtered them further using a proprietary rubric we’ve created to focus ideation on getting real and meaningful work done. Our research produced no less than 70 strong use cases — each testifying to the transformation we know all businesses will face in the coming months and years.

At Soaring Titan, we’re framing this technological and societal metamorphosis as the emerging “Cognitive Economy”. We planned — and still plan — to share the results of this research in upcoming posts, but it was the experience of the exercise itself that begged a different introduction… As I examined the ideas and their rationale, I was struck in an unexpected way. The shift towards the Cognitive Economy — one that I routinely describe and defend “intellectually” — affected me more “personally” than I anticipated. I was transported back to my time working directly within a community bank as a software engineer and solutions architect.

You see, AI did such an amazing job of detailing the people and processes often found within a community bank or credit union that my mind became filled with very “real” faces and conversations from long ago. I began to remember one-off software applications that I’d written to solve problems, build efficiencies, and meet regulatory requirements. It was like being back in 2007, and listening to the CIO describe his vision for a better topology of systems than those that were available to him on the market at the time. Reading on, I was reminded of interviews that I would conduct with bank personnel to learn more about their challenges and to consider where software might play a role in helping them. Colleagues from sister banks around the country would visit us to see the innovation being delivered at this $10B bank in Shelbyville, Kentucky. Later, I’d form Onovative with Michael Browning — a Software as a Service (SaaS) company for banks and credit unions. With Michael and I reunited at Soaring Titan, banking is one of a few key sectors that remain very close to our hearts.

Virtually every one of the 70 ideas our research suggested involved a problem that is (a) nothing new, and (b) being addressed to some degree of efficacy today, albeit by systems that are now becoming obsolete. Some of the very ideas our study highlighted were to address “old” problems that I sought to solve long ago with traditional software. Core system providers, software vendors, consultants, and internal IT will all seek to meet obvious challenges, but “how” these challenges will be met moving forward has changed forever thanks to AI. This is because AI is a different kind of software altogether. It no longer relies on traditional, if/then logic to make decisions. It no longer relies on a user to direct it. Now the software thinks. It reasons. It intuits. It talks like you and I do. It not only interacts with people, it can interact with other AI as well. It does not need to sleep. It does not need a break. It does not even need code. If it wants to create a traditional function or software application to help it solve a problem and to get a job done, then it can write, test, and deploy its own code! This has completely leveled the playing field once again for how problems - both new and old - should be solved and how work should be done.

All challenges — past and present — require a “reimagining” from the ground up as we shift from “Software as a Service” to “Service as a Software”.

Service as a Software

Service as a Software is the Future of Work and will drive the Cognitive Economy across all domains. With an AI agent, the software itself has become the worker — capable of understanding, executing, and improving upon traditionally human-delivered services. This is remarkably different from the kind of SaaS that Michael and I engineered just a few years ago. And, it is equally different from a custom, homegrown application or tool coded by someone like me at Citizens Union Bank those many years ago. In traditional software systems like those, people remain responsible for using them to achieve their desired outcome. They must act. With Service as a Software, AI agents are equipped with and use the same tools that a human would — allowing them to do work and to deliver complete outcomes beyond just delivering data or insights.

So will AI agents replace humans in the workplace? Let's just say that agents will increasingly reduce a drag on human potential where there exists a drive to explore it. In other words, autonomous AI can replace the repetitive tasks that bog us down, allowing us enterprising humans to do what we do best: imagine better outcomes, broader possibilities, and perhaps achieve a much-needed work/life balance.

Returning from my trip down memory lane in banking, I’m optimistic, and see a wide landscape of old challenges to be met in new and exciting ways. We’ll be sharing results from our research in subsequent posts and highlighting sector-specific applications for managed teams of AI agents on our website at https://soaringtitan.com. We look forward to digging into real problems, offering some “do it yourself” examples, and shaping the Future of Work with you using powerful AI agent teams, engineered and orchestrated by Promethia at Soaring Titan.