Gartner Inc., a research and consulting company, forecasts that by 2026, 90% of finance functions will adopt at least one (artificial intelligence) AI-enabled technology solution. Despite this, fewer than 10% of these functions are expected to reduce their workforce.
CFOs are already taking steps to integrate AI into finance, but challenges like employee disengagement and unrealistic expectations may hinder success.
“By combining human and machine capabilities, finance leaders can enhance business performance and employee satisfaction,” Mehta said.
While CFOs are already making changes to fully harness AI in finance, a sense of uncertainty, inflated expectations and employee disengagement often dampens success rates in AI’s usage. According to Gartner, CFOs who combine the strengths of people and machines increase their chances of AI success through a satisfied and engaged workforce.
AI-driven machines are proficient at automating simple decisions, such as analyzing large datasets. However, they may falter when faced with unique circumstances. Also, humans bring creativity and insight, particularly in solving unfamiliar problems.
Humans-machines collab
Gartner describes this collaboration between humans and machines as the “human-machine learning loop.” This process allows finance teams and AI-driven systems to work together, leveraging their respective strengths. Machines handle routine tasks like generating forecasts and approving expense reports, while humans focus on designing solutions to complex challenges.
This collaboration improves efficiency and drives continuous process enhancements. For example, a machine might suggest optimal invoice dates to boost cash collections, allowing finance professionals to develop new strategies based on these insights. As processes evolve, the loop iterates, with both machines and people contributing to further improvements.