Financial services CIOs – building GenAI at scale while managing risk

Shift the organization to “AI-first” thinking and imagine the possible

Financial institutions have historically embraced AI and machine learning in the middle and back office to speed transactions, mitigate investment risk and reduce cost. Now, GenAI provides new opportunities across the tech stack, including the front office, to not only create further efficiencies, but also to reimagine everything from opening a new bank account, to managing an investment portfolio, to processing an insurance claim. GenAI brings new capabilities and makes existing AI capabilities more accessible to employees and clients. In this way, some see GenAI as an opportunity to revisit the AI adoption in an organization, not only to re-examine internal operations, but also to reimagine business models. The CIO can provide leadership here not only by setting a vision and agenda, but also by educating their business counterparts on the appropriate use of AI/GenAI and by building the foundational tech stack to enable GenAI across the enterprise.

With this disruption also comes the responsibility and the need for transparency and governance at a board level, where the CIO must provide support and guidance. Boards of directors and senior leadership teams will have a responsibility to analyze both the acute risks and ethical considerations presented by GenAI. GenAI introduces new risks and legal concerns in how content is created, what data is used and how the algorithms are tuned, which demands both controls and transparency. Financial institutions making lending or credit decisions (e.g., leveraging GenAI) must be prepared to prove that data inputs do not contain bias and that there is transparency in how data is processed.

Be the catalyst for workforce transformation

The CIO has a bold opportunity to lead by example. The implementation of GenAI will disrupt virtually every job in the enterprise, eliminate some, create others and transform most. This requires a mobilization of the entire organization as the CIO partners with the business executives, COO, CHRO, CDO and others across the executive suite to build an enterprise-wide plan to upskill the workforce. Prompt engineering, for example, is a new skill, or perhaps even a new role, within the organization that is needed to maximize the benefit of GenAI. This level of disruption can sometimes be met with trepidation, particularly in areas of the firm where the fear of being replaced is highest; however, showing results in initial use cases, with a focus on augmenting human capabilities, will allay fears and inspire curiosity for how employees can leverage the technology to improve their own performance.

In this CIO “lead-by-example” approach, GenAI can accelerate the coalescing of software development, devops and the overall cyber agenda across the software engineering lifecycle. Flowing down to the day-to-day activities of the developers, team members can leverage code copilots to find opportunities to optimize, uncover limitations and mitigate risks. For the broader employee population, it’s low risk and nonthreatening to demonstrate how GenAI can enhance productivity and improve employee experience.

Optimize and modernize IT operations

Demonstrating GenAI value by transforming how IT operations function, particularly in software and solutions development, has direct implications from a design and cost standpoint, as well as serving as a showcase for the rest of the firm. Several areas rise to the top as key opportunities for the CIO:

• Operational efficiency – Technology operations is an area where GenAI can yield not only gains in productivity, but also cost savings. For the CIO, there’s an opportunity to be an even greater contributor to the financial goals of the firm and show impact to the bottom line, through both cost takeout and potential new revenue streams. Not only are there opportunities to shift costs of development from rote coding tasks to a more strategic impact, but GenAI-assisted development also delivers improved time to market and reduced risk for the firm.
• Risk takeout – Legacy systems in need of modernization represent a risk to the organization on several levels. Solution and code functionality is often poorly documented and not fully understood as the original developers leave the firm or former skills stagnate. Legacy solutions were not architected with current standards and best practices in mind, leading to evolving workarounds and increased tech debt. GenAI represents an opportunity to understand and audit this code efficiently, allowing the organization to stabilize legacy solutions and undertake modernization efforts. On a go-forward basis, GenAI can also be leveraged for ongoing code and application review, proactively mitigating risk as platforms evolve and age.
• Workforce optimization – While some think of GenAI as workforce replacement, extending human capabilities and optimizing time will be its main benefits in the short and medium terms. Firms hope to meaningfully reduce developer time spent in areas like code review and quality assurance, initial software development, security and compliance. This can elevate the entire development cycle toward a focus on design, architecture and performance vs. code development and testing. 
• Accelerated software engineering – In the software development cycle, GenAI can be a valuable accelerator. A variety of tools in the marketplace are focused on use cases, such as auto-generating project plans, drafting user stories, rapid proto-typing, code refactoring and optimization, and synthetic data generation for testing can reduce development time and impact time to market for new applications.