As the myriad of new AI technology applications and their burgeoning potential becomes more and more a part of the conversation in business and banking, there is one common truth: No one will get to sit this one out.
While it is essential to adopt an "eyes wide open" approach that takes into account the potential pitfalls of AI, and ensures use of these capabilities is ethical and responsible, it will be impossible for financial institutions to avoid AI altogether, and those that try risk losing ground in a competitive market.
When talking about integrating AI, a great deal of attention is focused on the technology piece, such as evaluating various applications or how to select AI vendors. But there has not been commensurate attention on the critical role of leadership. None of the AI technology matters unless banking executives demonstrate clear leadership around it.
What does that mean? Broadly, senior executives are charged with shaping organizational culture and encouraging a comprehensive range of business operations in the financial services sector. The most effective leaders understand that you don't lead with technology to drive change. Rather, technology is an enabler to overcome business challenges and realize a future different than today.
Before integrating transformative technology like AI and generative AI, a financial institution's leadership must first be aligned on the business problems they're attempting to solve. Banking leaders, and their staff, need to have a clear north star.
Do you want to be known for customer service, being the lowest-cost provider or for being innovative? AI can help across all of these dimensions. It can be leveraged to enhance and personalize customer interactions, to increase back-office efficiency or to position an institution at the forefront of the market with new product offerings. All of this requires leadership direction. Otherwise, a financial institution can end up in a nebulous space, not really having a clear road map for what changes are necessary.
Continued leadership along the progressive continuum of adoption is critical. Even when an organization is able to define and articulate a north star, leaders may be challenged in convincing employees to embrace AI. And that resistance will slow transformation.
The technology is adept at working with partial account numbers and other shreds of data to alert banks of ongoing and potential crime, the network contends.
Consider a bank that is implementing AI to address customer service needs and is transitioning to AI-enabled self-service. The bank's traditional service staff may be understandably concerned about being replaced by the technology. Account holders, as well, may initially resist using self-service products. From a change perspective, leadership means proactively educating employees on how the new efficiency will allow them to spend time on more high-value account holder needs instead of mundane everyday tasks that can be ably handled by the AI. And, crucially, the initiative must be taken to ensure the added value is articulated to account holders and other key stakeholders. This is a positive evolution that will make their financial lives easier.
A different type of leadership will be required as financial institutions wade into generative AI, given its ability to create content and predict outcomes. While many banking executives have grown comfortable with conversational AI and are now trying to optimize it, there's more hesitancy around generative AI. It is a curiosity for many with questions around the art of the possible. How can it help with lead generation or fraud models? How will predictive capabilities create new standards for expectations and experiences? No one wants to be left behind, but there are plenty of inherent regulatory and compliance risks with predictive AI to create leadership paralysis.
A reasonable way to proceed is to start small and then scale rapidly. Rather than trying to do it all at once, implement one use case and then begin to ramp up — all while keeping the identified business strategy or north star in mind. With AI, the logical path for a financial institution to evolve its technology is to become as much of an expert as possible around conversational AI and implement chat-based support. Other early use cases for financial institutions may be leveraging AI to develop code, to help with lead generation or to create back-office efficiencies.
As a financial institution works to achieve success with early initiatives, it should continue to build up the AI culture and the AI tool kit before moving to generative AI. Develop strategic partnerships with fintechs well-versed in AI capabilities and potentially academia to strengthen confidence with AI skill sets internally. Create centers of excellence in these skills. Engaging in partnerships with academia can streamline the path to building AI knowledge. Banking staff appreciate the opportunity to learn from trusted sources, especially those that are skilled in breaking down complex technology into progressive levels of learning.
As the financial services industry continues to navigate the emergence of AI capabilities, banking executives can feel as though they are walking on a frozen lake, not knowing where the thin ice lies. This new technology only holds value when it's driven by leadership that's bold and visionary, while still measured. Though there are risks when it comes to AI adoption, the technology is here to stay. There is significant potential for adopters of AI to see success, in an area where no one wants to be left out in the cold.
