The new CFO: How AI has changed the game for chief financial officers

BrandPost By Narasimha Kini
Dec 07, 20234 mins
Artificial IntelligenceIT Leadership

Unraveling the impact of artificial intelligence on finance leadership and enterprise success.

Electronics Development Engineer Working on Computer
Credit: gorodenkoff

Artificial intelligence has already unlocked opportunities that most organizations never thought possible. Now, it’s time to pay for it, and that’s putting a spotlight squarely on the chief financial officer (CFO), who has increasingly become the gatekeeper deciding which projects get funded and how significantly AI will play a role in enterprise strategy.

For the CFOs at the center of that transformation, the stakes are higher than ever. Nearly half of the companies (47%) recently surveyed by CNBC say that AI is their top priority for tech spending over the next year, and AI budgets are more than double the second-biggest spending area in tech, cloud computing, at 21%. That’s a big item on the corporate balance sheet, and it places the onus on CFOs to make sure their organizations are harnessing AI the right way.

It’s a huge shift from the norm. Traditionally, the work of the CFO and the finance team was focused on protecting the company’s assets and reputation and guarding against risk. While these roles will not change, the foundational work of the finance organization, the structure, the import, and the focus of these dimensions will change. AI will impact how the work gets done. It will strengthen and improve the veracity of financial data, and, most importantly, it will help CFOs take a more active role in value creation.

For example, by tapping into real-time data with AI-enabled analytics, CFOs will be able to develop multiple scenarios for capital allocation, offering more forward-looking projections and more accurate forecasts. This can include steps like replacing the traditional net present value/discounted cash flow calculator with multi-scenario models to stress-test multiple different forecasts under countless different scenarios. Going even further, some of the most progressive finance teams are incorporating sensor-based IoT data from plants, factories, and even trucking fleets to prioritize capital expenditures. They can even optimize capital allocation decisions, such as dividend distribution versus share buy-back, by rapidly modeling multiple scenarios and market conditions.

This type of data-driven predictive modeling simultaneously helps CFOs take a more active role in defining enterprise strategy while also helping them determine which AI projects should receive the most funding based on their anticipated impact on the bottom line.

Meanwhile, the CFO will also need to factor in the emergence of new AI-related regulations on data and privacy protection as well as ethical use guidelines for AI and other technologies as these new technologies are implemented. CFOs will need to take an active role in defining company policies to comply with these requirements, working even more closely than usual with their IT, risk, and compliance departments to ensure they are implementing AI responsibly.

This is a challenge that CFOs may not have asked for, but – ready or not – it’s their burden to bear. For those who get the formula right, it will also be a huge opportunity to catapult the finance organization into the future. CFOs have an opportunity to be front and center in helping organizations identify, define, and monetize new sources of value. But they will be doing so while navigating relatively uncharted waters, establishing best practices, and learning important lessons along the way. The key at every step in that process is to never lose sight of the core responsibilities of the finance department—to be the steward of the company, to manage financial operations and required reporting, and to be a strategic partner.

Learn more about how EXL can put generative AI to work for your business here.

About the Author:
Narasimha Kini is executive vice president and global head of the emerging business unit at EXL, a multinational data analytics and digital operations and solutions company