CFOs Look to Address the Finance Talent Gap With AI and ML

With the potential to supercharge enterprise functions in ways yet to be imagined, artificial intelligence (AI) and machine learning (ML) have understandably drawn plenty of attention from those looking to prepare for a future that’s quickly approaching. 

In the meantime, there’s plenty of opportunity for organizations to use AI and ML as they embark on their digital transformation journeys—particularly within their finance functions.

“Finance is in danger of becoming real laggards in the area of AI, automation, and even traditional analytics,” Tom Davenport, author of All in on AI: How Smart Companies Win Big With Artificial Intelligence; a president’s distinguished professor at Babson College; fellow at MIT Initiative for the Digital Economy; and visiting professor at Saïd Business School, University of Oxford

In a recent webcast hosted by Fortune and sponsored by Workday, Davenport, along with Vanessa Kanu, CFO at TELUS International; Katie Rooney, CFO at Alight Solutions; and Philippa Lawrence, vice president and chief accounting officer at Workday, discussed how organizations were implementing advanced technologies to address the talent gap in finance. 

Davenport said a survey he conducted a few years ago suggested human resources (HR) departments were “well ahead of finance in terms of using predictive analytics and machine learning.” 

However, for all the ways AI and ML could help transform the enterprise, Davenport emphasized that existing technologies can free up people to perform higher-level functions. Technology, as he sees it, won’t simply replace headcount.

“AI is typically a task-oriented tool. It doesn’t replace entire jobs and certainly not entire business processes,” he said. “In order to have much of an impact, you have to do a variety of small use cases and sort of pile them on top of each other.” 

Finance organizations have also started to look at AI and ML use cases to evaluate how such areas as customer service and employee-learning activities drive financial performance and quantify the value they provide to the business, Davenport noted.

Davenport added that audit organizations are already using automation to read through contracts to determine liabilities and measure performance, adding that CFOs and auditors will still need to review the end product and sign off on final results. “We’re never going to ask an AI system to do that—because we can’t,” he added. 

Davenport noted that AI and ML remain probabilistic functions. “All machine learning is based on statistics and statistical predictions,” he said. “If there’s an area where you absolutely have to have the right answer, that’s still going to be one that a human will have to do.”

While ChatGPT has garnered a wealth of news headlines in recent months, the biggest technology-enabled gains for business in the near future will likely come from automating repetitive tasks. “There are lots of opportunities from robotic process automation (RPA) for relatively structured predictable finance jobs—jobs involving pulling information from one system and putting it into another,” Davenport said. “It’s really quite useful for those settings.” 

Establishing a Solid, AI-Ready Data Foundation  

“AI is only as good, and the insights are only as good, as the underlying data,” Rooney said, adding that maintaining a solid data foundation is a priority for Alight Solutions, an Illinois-based human capital technology and services provider to 70% of the Fortune 100 companies. “Our first focus has really been on streamlining the data infrastructure,” she said. “We have all of our systems—finance, HR, every country—actually on Workday, which has helped level-set the teams.”

That data foundation, however, is critical to enable clear, data-driven decision-making. “Our strategy is really around making sure we have that one unified data source—and it’s even broader than finance,” Rooney said. “It has to get as much as we can across our organization, as well.”

How AI and ML Can Support People

Kanu said automation was about supporting employees at TELUS International, a Canadian technology company that provides IT services and next-generation digital solutions, “by making them more efficient and enabling them to focus on more engaging, meaningful work.” For instance, TELUS International uses an HR bot that handles more than half of all employee inquiries, which frees up employees to focus on higher-level functions. 

“Hiring highly qualified, talented team members globally and at scale to support our own customer demands is our job,” Kanu said, and technology has helped the company speed up recruitment, broaden its access to global talent pools, and increase candidate engagement. At a time when accountants are in short supply, she added, AI and ML can improve recruitment and retainment efforts. 

“We hire college grads. We hire really smart people, and then we somewhat dumb them down by turning them into Excel jockeys,” Kanu said. “Nothing wrong with Excel. I love it, but you know that’s not the greatest value we can get from our team members within finance and accounting, specifically.”

Kanu said there’s an opportunity to develop accounting and finance talent by improving employee experience, trading repetitive tasks for strategic work, and becoming better partners to other functions across the enterprise. Managing cells in a spreadsheet, she added, doesn’t engage employees’ higher intellectual capacities—and automation via AI and ML can help change that.

“For me, this is a personal mission because automation is key to unlocking the value from our team members,” she said. “People want to make a difference.”

The Effects of Automation on Work Roles

Automation will likely prompt finance leaders to think differently about talent, Rooney said, citing the potential effects of AI and ML technology on offshore talent. But, she emphasized, it’s not a simple matter of automation displacing workers on a geographical basis. “It’s more role- and process-specific in terms of where we can drive the most standardization to get the most leverage out of what we need to do every day.”

Yet humans will remain in demand for evaluating the customer and cultural implications of data-driven decisions, Rooney said. “Whatever the model tells you today, I guarantee tomorrow could be different,” she added. “Having that human element around how you interpret it, and how you action it, is really critical.”

Kanu also said she didn’t think AI would eliminate the need for human intelligence. “The kind of work that we all do will just evolve over time,” she added. “Anything that requires that higher level of complex thinking, anything that requires relationship building, spending time with investors and key stakeholders, how you manage your board—all of those kinds of skills are not going to go away anytime soon because of automation.”

Leading Through Technological Change

“We’ve adopted this human-centric approach to AI and ML, positioning machines as co-workers but not replacements,” Lawrence said, providing a glimpse of Workday’s vision for AI. 

Lawrence also asked how finance leaders have worked with their teams to adopt AI and ML.

“It should be a tool, in essence, that helps us work differently, provide insights differently, and free up capacity to partner with our business teams differently,” Rooney said. “Change is hard, especially in finance, but once you help people see the value of how they can do their work differently, it resonates. For me, it’s helped by just honestly getting started and showing what it can be.”

Kanu noted the pace of change can be overwhelming, especially with all the talk of generative AI and such uses as ChatGPT, and added that the best approach might be to start small.

“Focus on the most relevant use cases for your business and your industry, and then build your knowledge gradually over time,” she said. “We’re not trying to turn our finance organization into digital experts. They’re not going to be working for IT or building their own apps anytime soon, though maybe eventually. So when you cut it down into bite-size chunks, that certainly makes it a lot easier for the team to digest.”

Kanu added that her finance organization was in the process of building a team to help smooth the transformation process and increase its use of existing automation tools. “What I’ve found is while there’s resistance to change, generally everybody wants the outcome that will eventually make all their jobs easier,” she said. “The biggest impediment tends to be time.”

Watch the entire Fortune Emerging CFO webcast, titled “Addressing the Talent Gap With Advanced Technologies.”