" prediction accuracy tends to falter beyond a certain range of input values " or " some customer groups were underrepresented in the training data. " Operationally, a good way to proceed is to build and deploy a series of increasingly complex AI applications, rather than being wedded to an ambitious design at the get-go. Iteratively adding functionality and gradually incorporating more data fields can make measuring performance easier and avoid costly mistakes. Bilac: Bankers should understand that AI is not a do-it-all, perfect solution for every problem. It is most effective when applied to narrow and practical problems where it is easy to deploy and measure the benefits of using the technology. Because of this, vendors who make wide-ranging promises about their AI systems should be considered with a due level of scrutiny and diligence. Another potential pitfall I have seen some banks run into is jumping in too early and trying to develop their own systems from scratch. Open sourcing and the publication of algorithms has made the basic ingredients for AI tools readily available, but it still takes a significant amount of expertise to take these foundational elements to a state ready for implementation, evaluation, deployment and maintenance. This approach can be quite resource-intensive and in most cases turns out to be much more complicated and expensive than initially imagined. Potts: Banks need to be circumspect and thoughtful about potential data bias in the AI models themselves and always check their work. Banks also need to be mindful of the transparency of the models they use; this is where the regulatory bodies are keenly interested. You can't just have these black box processes in place that you can't explain to examiners and auditors. The models that get used have to have some real transparent " explainability " to them. The third issue is overreliance, especially for community banks because the relationship banking aspect of community banking continues to work for a reason. " AI is quickly becoming a standard in how we assess and manage fraudulent activity as well as helping bankers more efficiently market their services to their customers because they can better understand their specific needs. " -Wayne Miller, ICBA Solutions Group 48 // ICBA Independent Banker // November 2023 Illustration by Korkeng/Adobe