Speaking at the Gartner Finance Symposium, Twisha Sharma, senior principal for Gartner’s finance and technology research, said that due to the complex nature of AI tools, the differing tasks they are designed to achieve and the need by many businesses to utilise multiple AI tools, they need to be thought of as a wider portfolio.
“AI does not follow one cost curve, and it does not produce one uniform type of value,” she said.
“CFOs need to stop looking for a single ROI formula and instead build a balanced portfolio that includes productivity use cases, targeted process improvements, and selective transformational bets.”
Sharma used the metaphor of AI projects being different types of travel, all of which have different purposes and economic identities. Think flight, ocean travel, and driven travel.
“An AI portfolio should contain projects with routine use cases that automate repetitive tasks, those with more advanced use cases that improve analysis and decision making, and larger transformational use cases aimed at innovation or competitive disruption,” said Gartner in a release.
Sharma said businesses that do not treat AI applications as a portfolio may run into unexpected costs and budget shocks later down the line.
“The economics of AI differ sharply from one use case to another, making it difficult for a standard value approach to capture the full picture, especially as the cost difference between various types can be significant,” she said.
“Each use case will have different timelines, different ambitions, different risk profiles, and different ongoing costs. If finance teams don’t dissect cost models with precision, they will face budget surprises later.”
She also said that CFOs who tunnel focus on immediate financial returns, such as cost reduction, improvement of cash flow, or growing revenue, may undervalue AI tools and misuse them, particularly as many AI tools first create non-financial value, such as business agility, innovation capacity, shifting roles, and more.
“The value of AI is not always captured first in traditional financial metrics. In many cases, it appears earlier in better decisions, faster adaptation and stronger organisational capability. CFOs need to account for that if they want a complete picture of what AI is really delivering,” she said.
CFOs should consider productivity gains and other non-financial benefits and, as previously said, treat AI tools as a portfolio rather than hyperfocusing on getting a dollar value.
