A restaurant can succeed or fail based largely on the reputation and creativity of the head chef it employs. In reality, any single chef is just a small part of the equation of a professional kitchen. The average small restaurant not only employs one to two chefs but as many as three to five additional cooks to help fill customer orders. The number of kitchen staff needed to run a restaurant increases based on size and menu complexity, as well.While it takes multiple kitchen staff to operate a restaurant, getting the number right is critical. As the adage goes, too many cooks in the kitchen can be unproductive — a fact that is driving many businesses to assign responsibility for their organization’s artificial intelligence (AI) efforts to a single individual. However, there are mixed thoughts on whether that is a good thing while AI’s role in the banking industry is still developing. AI in the Banking IndustryThe role of chief artificial intelligence officers (CAIOs) was recently pushed to the forefront by the White House’s Office of Management and Budget, which announced that all federal agencies must appoint a CAIO to ensure that the government stays on top of changes with AI. The position is catching on within other industries: 21% of large and midsized companies have indicated plans to create CAIO positions as well. Overall adoption of AI is on the rise, from consumer use to businesses, and that includes the banking industry. AI’s primary use in the banking world has typically been data analysis, but it’s expanding into operational uses with the rise of generative AI capabilities. A 2023 McKinsey report estimates that generative AI could reduce banking operating expenses by $200B-$300B, and increase productivity by 3%-5%. Companies are also finding ways to apply AI to fraud prevention, risk management, and customizable client experiences. Barclays, for instance, utilizes generative AI to detect unusual behavioral patterns that would prompt a fraud alert if such a pattern was flagged on certain account activity.The ProsWith the rise of AI’s presence in various facets of a financial institution’s operations and offerings, as well as the rapid developments within the nascent technology, appointing a CAIO is a natural next step in the technology’s progression, as the banking industry also expands its use cases.The goal of creating a dedicated role for AI oversight stems from the need for accountability and the knowledge that someone is dedicated to tracking AI’s evolution. A dedicated CAIO can help manage the following areas:
- AI strategy development. CAIOs work with leadership to determine a company’s AI needs and goals and then develop an AI strategy that’s the most beneficial for their organization. This can involve identifying where AI’s application is the most beneficial, collaborating with different departments, and resource management.
- AI compliance management. As AI usage grows and expands across different industries, new regulations and compliance standards will be developed. A CAIO can manage your company’s AI compliance as standards and regulations are created.
- AI training and testing. A dedicated CAIO can oversee the deployment, testing, and training of AI within your organization. This can also include quantifying the results of any AI implementation and how its usage has benefited your organization.
- AI risk management. AI usage carries its own risks regarding data privacy and security that can be more closely monitored by a CAIO.
The Cons While greater transparency and accountability are the major expectations of adding CAIO roles, skepticism abounds regarding how beneficial such positions will ultimately prove to be. Though 52% of financial institutions have plans to hire generative AI employees in 2024, so far, few are seeking to bring on CAIOs. Here are some of the reasons companies aren’t bringing on CAIOs along with barriers for those who want to pull the trigger but haven’t done so yet.
- Focusing on filling other tech roles. Some institutions aren’t ready to consider a CAIO yet, because they have different staffing priorities for their technology plans. Instead, the technology roles most financial institutions are currently focused on filling include general AI experts, data engineers, data scientists, and prompt engineers.
- The challenge of finding the right talent. In cases where there is a desire to bring on CAIOs, finding qualified candidates is a challenge. Ideally, CAIOs should have expertise both in business strategy and advanced science. While the industry’s largest financial institutions can offer the perks and benefits needed to attract such candidates, community financial institutions interested in the benefits of a CAIO but not the costs of a permanent position may be better served by outsourcing such responsibilities or bringing in outside consultants or advisors on a temporary basis.
- Determining hierarchy with a CAIO. Reporting structure and organizational challenges are something to consider, as well — many businesses are not yet sure where the role should fit within their hierarchies. Absent best practices for this new role, some organizations are housing CAIOs within the IT portion of their organizations, while others believe the role should be overseen by chief operations officers.
- Company sentiment toward AI. There are often major discrepancies in the openness to AI among employees within financial institutions and also their experience levels using AI-based tools. Younger employees tend to be more familiar and open to AI usage, while more seasoned employees may be hesitant to break with established processes.
Businesses that want to remain competitive do not have the option of ignoring AI, and that includes community financial institutions. Though it makes sense to keep a close watch on how the CAIO role develops and emerges within the business world, and how major financial institutions decide to approach it, for now, smaller institutions are probably best served remaining on the sideline and seeking any additional guidance or expertise needed for their AI initiatives from consultants or third-party experts.
