Beyond the Hype: What CFOs Should Know About AI Agents
When chief financial officers (CFOs) consider implementing agentic artificial intelligence (AI), they should treat it like other technologies their companies have adopted in the past, with some adjustments to mitigate specific risks that come with the new system.
There’s a good reason for this approach: Agentic systems have been around for a long time, according to George Westerman, senior lecturer at the MIT Sloan School of Management, in an interview with PYMNTS.
What is agentic AI? Westerman said there’s not yet one agreed upon definition, but at its simplest, it is software code that will process information and make a decision or take an action.
“The concept is not new,” Westerman said. For example, many processes launch and relaunch in Microsoft Windows automatically on a regular basis. Also, automated trading on Wall Street has been around for decades.
Read more: Inside Goldman Sachs’ Big Bet on AI at Scale
Not Like Traditional Computing
What’s different is that instead of rules-based bots, where actions are pre-determined, AI agents built on top of generative AI models can dynamically generate responses, understand, adapt and learn while having autonomy and decision-making abilities to complete a task given by the user.
“It can do things that traditional computing could not do: It can hold a conversation with a client. It can process unstructured data and documents,” Westerman said. However, “we still want to use the same processes to evaluate how to do it.”
That means CFOs should approach agentic AI like past forms of automation they’ve incorporated — evaluating what processes can benefit, identifying costs that can be removed, find potential benefits from accelerating work, and assessing risks to finances and reputation, according to Westerman.
CFOs also should use their existing governance policies and risk frameworks to evaluate the new technology — and revise as necessary.
“You should already have very strong governance and policy approaches to automation, and you’d want to apply those same policy approaches to agentic AI but also see where those policies may need to change,” he said.
See also: Nvidia CEO: Why the Next Stage of AI Needs A Lot More Computing Power
Assessing ROI
The same approach goes for evaluating the ROI of agentic AI, Westerman said.
Niall Byrne, CFO at Qatar Investment Authority (QIA), told the World Economic Forum on Tuesday (March 25) that “we are exploring pilot projects with clear metrics to help quantify the return on investment on AI investments, including looking at adoption rates, data processing speed, value creation and employee productivity.”
Westerman said CFOs must be clear-eyed about costs, since implementing AI is “expensive,” like other technology integrations. It was the same case with cloud computing, which is pay-as-you-go, but costs could climb with higher usage in contrast to using your own servers.
For AI, the costs include compute charges, cleaning of data, for licenses and changing processes, which is often the larger expense, he said.
Westerman sees the biggest agentic AI opportunities for finance in the following areas:
- Making sense of unstructured data such as videos, emails and PDFs
- Automating routine parts of planning, control and reporting
- Compliance
- Underwriting
- Customer interactions
What CFOs should do:
1. Align agentic AI initiatives with business goals
Clearly define the financial outcomes you aim to achieve with AI agents, such as cost savings, improved forecasting, or enhanced risk management. Investments should be aligned with business objectives and demonstrate clear ROI, according to the World Economic Forum.
2. Manage risks proactively
Assess risks related to data security, privacy, regulatory compliance and financial accuracy, Westerman said. Develop contingency plans for AI errors or system failures and maintain clear accountability structures.
“Every leader, including CFOs, must champion AI and understand the systemic risks of generative AI in finance,” said Kalin Anev Janse, CFO and member of the management board of the European Stability Mechanism, in a World Economic Forum blog post.
3. Invest in the right skills and address job fears
If there will be job cuts, tell the staff. “As with any organizational change, you want to be very transparent with your people,” Westerman said. Train employees on how to use AI for their jobs and encourage open collaboration among the staff.
To find AI engineers, companies don’t need to hire the best graduates from the top schools because there’s a lot of good talent around, Westerman said. But they should at least have a core group of people who understand AI well, and the rest of the workforce trained on how to use it.
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