The financial services industry is no stranger to technological change. From online banking to mobile payments, institutions have repeatedly adapted to new tools, new channels, and new customer expectations. But artificial intelligence, particularly Generative AI (hereafter referred to as GenAI), is not simply another phase in that evolution. It represents a structural break in how work gets done, how decisions are made, and increasingly, how transactions are initiated. An author of a recent American Banker article highlights a growing concern: banks are adopting AI faster than they are preparing their workforce to use it effectively. In fact, a majority of institutions are relying on informal, on-the-job learning to bridge the gap. While that approach might have worked for prior technologies, it will not work for GenAI. For community banks, the stakes are even higher. Unlike large institutions with deep specialization and dedicated innovation teams, community banks operate with leaner staff, broader roles, and tighter margins. That makes GenAI both more valuable and potentially more dangerous if not deployed with careful planning and intention. The path forward is not simply enterprise-wide adoption. It is implementing a comprehensive, structured, and institution-wide training program. Traditional technology training focuses on teaching employees how to use a system: where to click, how to complete a process, how to avoid errors. That model is unproductive for Generative AI due to the fact that GenAI is dynamic, not static, contextual, not procedural and continuously evolving. Even more importantly, GenAI is beginning to act not just as a tool but as a participant in financial ecosystems. With the rise of agentic commerce, institutions are preparing for a world where transactions may be initiated by AI agents acting on behalf of customers. Eventually, AI Agents may be taking initial calls and chats from customers. This introduces entirely new challenges such as: Fraud patterns that don’t resemble human behavior Authorization models based on permissions, not intent Dispute resolution requiring interpretation of machine-generated actions These are not incremental changes. They require a fundamental shift in workforce capability. Yet many institutions are still approaching AI training as if it were a software rollout. That gap, between adoption and understanding, is where risk, inefficiency, and missed opportunity are revealed. Relying on informal learning for AI creates three immediate problems: 1. Inconsistency Across the Organization – Some employees experiment and become highly effective. Others avoid GenAI entirely. The result is uneven performance, fragmented processes, and unpredictable outcomes. 2. Hidden Risk Exposure – Without guidance, employees may unknowingly input sensitive data into unsecured tools, generate outputs that violate policy or compliance standards or rely on inaccurate or unverified information. This reinforces the need for a human-in-the-loop approach, where all AI-generated outputs are reviewed for accuracy, relevance, and compliance before being used. 3. Missed Strategic Value – GenAI’s greatest impact is not in isolated productivity gains, it’s in transforming workflows. That only happens when adoption is broad, aligned, and intentional. For community banks, this is not just an efficiency issue. It is a competitive one. To understand why structured training is no longer optional, it’s important to look at the broader pressures facing community institutions today. 1. Margin Pressure Is Intensifying – Community banks are navigating a convergence of financial pressures: Rising compliance costs Increasing vendor expenses Aggressive competition for deposits Ongoing staffing challenges Incremental efficiency improvements are no longer sufficient. GenAI introduces the potential to reshape the cost structure itself. This can be achieved by a) automating low-value, repetitive tasks, b) reducing reliance on external vendors and c) increasing throughput without increasing headcount, but this only happens if employees know how to use the technology effectively. Without training, GenAI becomes just another underutilized tool, adding cost without delivering return. 2. The Talent Gap Is Widening – Community banks have long faced challenges attracting and retaining specialized talent such as credit analysts, compliance experts, marketing professionals and data/technology roles. That gap is not closing, it is expanding. GenAI offers a powerful counterbalance. It acts as a force multiplier, enabling existing employees to: Analyze more complex credit scenarios Draft and review compliance documentation Execute marketing strategies with greater sophistication Access data insights that were previously out of reach But this amplification effect is not automatic, it requires skill development, practical application and confidence in using AI tools. Without training, the talent gap remains. With training, the existing team becomes exponentially more capable. 3. Regulatory Complexity Continues to Grow – Regulatory expectations are not static, they are increasing in scope, depth, and scrutiny. GenAI can play a transformative role in this environment by monitoring policy adherence across workflows, assisting in drafting and reviewing documentation and identifying anomalies and potential issues before exams. This creates an opportunity to shift from reactive compliance to proactive risk management. However, regulators are also paying close attention to how AI is used. Institutions must demonstrate appropriate governance, data security controls and responsible usage practices. This balance, leveraging AI while maintaining compliance, requires trained employees who understand both capability and risk. 4. Knowledge Fragmentation Is a Hidden Drag – In many community banks, institutional knowledge is distributed across systems, embedded in documents or held in the experience of long-tenured employees. This fragmentation creates inefficiencies, such as: Time spent searching for information Inconsistent decision-making Dependency on specific individuals Enterprise GenAI introduces the concept of a unified intelligence layer that connects policies, procedures, and credit philosophy, providing consistent, real-time access to information. The result is better, faster decision-making, crucial for the long-term success of community banks. But this capability only delivers value if employees know how to access it, interpret it and apply it appropriately with adherence to AI policy and data security best practices. Proper training turns potential into performance. 5. Your Employees Are Already Using GenAI – This is the most immediate and often overlooked reality. Whether formally approved or not, your employees are already experimenting with GenAI. They are doing so on personal devices using public tools and without institutional guidance. This creates: Data security risks Compliance exposure Inconsistent outputs and decision-making Worse, without the proper training, your employees are likely making numerous mistakes in how they are using GenAI. This means that the value of GenAI is spotty, leading to inconsistent results that fail to move the gross margin needle. Ignoring this behavior does not eliminate it. It amplifies the risk. The only viable response is to make an enterprise version of GenAI tools available to all employees. Then further, enact an AI Policy that at a minimum restricts usage to approved tools, establishes clear policies on usage and data integrity and requires all users to complete a GenAI structured training program. In other words, replace uncontrolled experimentation with governed empowerment. Training Must Be Enterprise-Wide, Not Role-Specific One of the most common mistakes institutions make is limiting AI training to technical teams or innovation groups. That approach fails for a simple reason – every employee who touches a transaction, a customer, or a decision will be impacted by GenAI. This includes: Frontline staff Lenders and credit teams Operations and back-office functions Compliance and risk professionals Marketing and customer experience teams The C-Suite GenAI literacy is not a specialized skill. It must be a core competency. And like any core competency, it must be consistently taught, reinforced through application and aligned with institutional strategy. Recognizing both the urgency and the opportunity, FNBB, along with its partner nForce, has developed a comprehensive GenAI training program. Created as part of our own enterprise-wide AI rollout, this training is designed to maximize positive outcomes while reinforcing safe, policy-aligned usage. Today, that training program is available to FNBB client institutions. Called GenAI Fundamentals for Bankers, it is built specifically for financial services users and delivered through an interactive, web-based learning environment. It is designed not just to inform, but to enable, equipping employees with the knowledge and practical skills needed to integrate GenAI into their daily work. The program is offered in two flexible options: Basic – A robust, ready-to-deploy program using general banking content and examples Plus – A fully customized experience tailored to your institution’s policies, workflows, and use cases Both versions include a structured, progressive curriculum: Module 1: AI Fundamentals for Banking & Financial Services – A clear, practical foundation in how AI and GenAI function within the financial services landscape. Module 2: AI Policy, Security, and Risk Awareness – Guidance on safe, compliant usage —addressing one of the most critical concerns for institutions today. Module 3: GenAI Usage and Best Practices – How to effectively integrate AI into everyday workflows while maintaining quality and control. Module 4: Prompting Essentials – A hands-on approach to developing one of the most important new skills in the AI era. Module 5: Practical Applications in Banking Workflows – Real-world use cases that connect learning directly to measurable impact. The training program supports leading platforms such as ChatGPT and Microsoft Copilot with content tailored to how each tool operates, ensuring relevance regardless of your technology environment. GenAI is already reshaping how banks operate. GenAI powered customer-facing applications are not far behind. The question is no longer whether to adopt GenAI tools, it is how quickly and effectively your institution can build the capability to use it well. Institutions that delay comprehensive training risk falling behind in more than just efficiency, but also: Decision-making speed Customer experience Operational resilience Competitive relevance Training is not a cost center in this context. It is a strategic investment. Andrew Ng famously said, “GenAI is the new electricity.” That analogy is more than clever, it is instructive. Electricity did not create value simply by existing. It created value because organizations learned how to harness it, systematically, safely, and at scale. GenAI is no different. The institutions that invest in training today will not just adapt to this shift; they will define what comes next. Equip your team. Reduce your risk. Accelerate your future. To learn more about FNBB’s GenAI Fundamentals program, contact AI.Training@bankers-bank.com or reach out to your Relationship Manager to get started. Click here to view GenAI Fundamentals video. Resources https://www.americanbanker.com/payments/news/banks-struggle-with-ais-learning-curve?utm_campaign=NL_AB_Daily_Briefing_04082026&utm_source=newsletter&utm_medium=email&campaignname=NL_AB_Daily_Briefing_04082026&oly_enc_id=9007J3421978D5N ChatGPT was used in researching this article.