AI & Automation in Community Banking

ATX believes the organizations that win the AI & Automation race won’t be the fastest movers, but the most deliberate builders focused on driving real ROI. Bold, yet deliberate builders will build risk and security management into their projects, this will enable and drive innovation that will lead to multiple layers of success.

Gartner® predicts that 40% of agentic AI projects will fail by 2028 due to high costs and unclear value. Success today depends on having a clear strategy, well-defined data, strong governance, and disciplined risk management.

Many banks are struggling to balance AI enthusiasm with the necessary ethics and controls. Right now, excitement is pushing teams to move quickly, often assuming their current data and security structures can handle the demands. In most cases, they can’t. Governance isn’t optional, it’s foundational.

At ATX, we approach AI as a strategic initiative that balances sound planning and governance alongside experimentation and discovery. We take this approach both internally and with our clients. The pace of change is relentless. A recommendation made three months ago can quickly become obsolete as functionality continues to improve with tools like Copilot, ChatGPT, or entirely new platforms emerge.

If your organization isn’t comfortable operating with an “it’s okay to fail and learn” mindset, you may be considering waiting while others to blaze ahead. We’ve seen this before. When e-banking first emerged, some banks moved early, changed vendors multiple times, and adapted along the way. Others waited, stalled and thought e-banking would just be a phase. The early adopters ultimately found new ways to deliver services that weren’t previously possible. Those who waited, received the same benefits but sometimes years later which resulted in opportunity lost while they were waiting.

For organizations that are ready to move forward rather than wait, a few foundational priorities can significantly improve the likelihood of success and make innovation manageable:

1. Establish a Clear AI Strategy Aligned to Growth
AI should not be treated as a standalone initiative or a short-term efficiency solution. It should be integrated into a broader growth strategy. While cost reduction and margin pressure are real, the greater opportunity often lies in rethinking how value is created. Building a cross-functional AI strategy team—combining internal leaders with external expertise—can help ensure both practical execution and informed perspective.

2. Prioritize Functional Application of AI
The real value of AI comes from how it is applied. Organizations should focus on identifying meaningful use cases where AI can enhance operations, decision-making, and customer experience. This starts with data. Establish clear objectives for how data will be used, and invest in improving data quality, accessibility, and analysis. When done well, these efforts unlock new capabilities that extend far beyond incremental improvements.

3. Strengthen Data and Technology Infrastructure
A modern data infrastructure is essential to support AI at scale. Advances in technology, including agentic AI architectures, are expanding what is possible, but they also place greater demands on underlying systems. Evaluating your current environment and identifying gaps can often be done quickly with the right partner. The goal is to build a flexible foundation that can evolve alongside rapidly changing tools and platforms.

4. Reinforce Governance, Risk, and Controls
While financial institutions have long-standing strengths in risk management, AI introduces new and unfamiliar challenges. Data sourcing, model behavior, security, and privacy require heightened attention. Establishing—or enhancing—a governance structure dedicated to AI can help ensure that innovation is balanced with control. Clear oversight, defined policies, and ongoing monitoring are critical in building trust and maintaining compliance in an AI-driven environment.

Taken together, these steps provide a practical starting point for organizations looking to adopt AI with intention, discipline, and long-term impact.