Fewer Than 10% Will See Headcount Reductions as a Result
Gartner experts examined how finance functions are successfully implementing AI technologies during the Gartner CFO & Finance Executive Conference, taking place today in London.
While CFOs are already making changes to fully harness AI in finance, a sense of uncertainty, inflated expectations and employee disengagement often quells success rates in AI’s usage. CFOs who combine the strengths of people and machines increase their chances of AI success through a satisfied and engaged workforce.
“Despite AI’s ability to emulate human performance, algorithms cannot match the unique capabilities of people in areas that require creativity and complex problem solving,” said Ash Mehta, Senior Director Analyst in the Gartner Finance practice. “By recognizing the respective strengths of people and machines, finance leaders can build processes that boost the abilities of people and machines, while mitigating their weaknesses. This requires a new kind of collaboration between people and machines that will improve business performance and employee satisfaction.”
Ash Mehta, Senior Director Analyst at Gartner, discussing AI use cases with finance leaders in an “Ask the Expert” session today at the Gartner CFO & Finance Executive Conference in London.
“To supercharge the abilities of both AI and people, they must learn to collaborate in a way that harnesses each other’s strengths,” said Mehta.
Gartner experts call this collaboration the human – machine learning loop, which promotes continuous process improvements that encourage finance staff and AI-driven machines to collaborate on processes while dividing labor according to the respective strengths of each. While relying on each other for improvements, both parties can iteratively add greater value (see Figure 1).
Figure 1: The Human-Machine Learning Loop
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Source: Gartner (September 2024)
The labor performed by machines in this way then frees humans to take information, advice and recommendations from algorithms, using their creative and strategic strengths to solve complex problems by designing process improvements. Once new processes are in place, people trigger the next iteration of the loop by building new machines that execute the new processes and analyze the respective data.
