Artificial intelligence (AI) has arrived in financial services at full force, and unlike the slower adoption curve of cloud computing, banks and credit unions cannot afford to lag. Competitors are already embedding AI into their core operations, and cybercriminals are deploying it just as aggressively. The stakes are high: AI is transforming cybersecurity, fraud detection, and operational efficiency, yet adoption requires an equal commitment to governance and trust. For institutions that strike the right balance, AI will not just be a tool for efficiency but a foundation for long-term resilience.
The Security Upside: AI as a Force Multiplier
When it comes to security, AI is already delivering tangible value. Institutions across the country are using AI to reinforce their defenses and protect customer assets. At Diebold Nixdorf’s recent annual Intersect Conference, we heard from several leaders from both large financial institutions and smaller community banks and credit unions speak about how they are implementing AI across their organizations. Thomaston Savings Bank, for example, has deployed AI to monitor risk, manage cybersecurity (like flagging fraudulent emails before they spread through employees’ inboxes), and is leveraging AI-driven tools to support vendor management, using tools like Ncontracts to streamline contract review, ensuring both compliance and efficiency.
From my perspective at Diebold Nixdorf, AI is a natural extension of existing security infrastructure. It enables systems to identify anomalies faster, more consistently, and at a scale no human team can match. Whether flagging suspicious login attempts or monitoring ATM behavior, AI acts as a force multiplier for human teams, helping them detect and respond to threats before they cause real harm. These aren’t experiments on the fringe. They are live, proven deployments showing how AI is actively safeguarding financial interests today.
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The New Risks: Data, Agents, and Trust
With new tools come new risks. Agentic AI systems, where AI agents act autonomously or interact with one another, create new layers of uncertainty around where sensitive data flows. Without strong visibility, institutions risk customer information being ingested into unintended or ungoverned systems. Banks are right to emphasize cyber protections that ensure customer data never slips outside their control. Similarly, it’s essential to be mindful of potential UDAAP violations that can occur if AI systems inadvertently steer customers toward unsuitable products. These concerns reflect a broader truth: compliance and ethics cannot be an afterthought.
Beyond regulatory issues, AI poses new challenges to public trust. Deepfake voices and synthetic personas are no longer theoretical. A fraudster posing as a trusted banker on the phone could easily trick customers into handing over credentials. That kind of breach would not only harm individuals but also undermine the trust institutions have spent decades building. The lesson is clear: AI introduces risks that require new governance structures, new transparency into data usage, and a proactive stance on how to maintain, and even strengthen, customer trust.
Governance and the Path Forward: Balancing Speed with Guardrails
If AI is to fulfill its promise, governance must be the foundation. That doesn’t mean slowing down but creating conditions where innovation can move quickly without jeopardizing compliance or trust. At Diebold Nixdorf, we take a pragmatic approach. AI tools run freely inside our tenant or on-premises environment, where data remains under our control. When external data transfer is required, we use a cross-functional review process that involves IT, legal, and business leaders. These guardrails don’t stifle innovation; they enable us to move confidently and efficiently.
Across the industry, banks are achieving similar success by starting with lower-risk use cases, such as internal productivity tools, customer-service automation, or vendor integrations. By building AI “sandboxes,” organizations can create controlled environments to test, refine, and scale AI implementations without exposing sensitive data. Others in the industry are already exploring how AI agents could support customer interactions 24/7, improving service accessibility without increasing headcount. We are entering a new digital arms race, and it’s clear that speed matters. The institutions that win will be those that act boldly while maintaining the discipline to govern responsibly.
Adopt with Urgency, Govern with Discipline
It shouldn’t be controversial to say that AI is no longer optional or a “nice to have” in financial services. It is both a shield against today’s cyber threats and a driver of tomorrow’s customer experiences. However, success requires more than plugging in the latest tools. It demands an intentional strategy that balances speed, safeguards and experimentation with oversight.
Financial institutions that adopt AI with urgency and govern with discipline will not only protect their customers but also lead the industry in defining the future of trust in banking.
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