Companies are spending heavily on artificial intelligence, but buying the technology is proving much easier than getting employees to use it. This is particularly clear in finance, where AI adoption in finance continues to lag behind other major business functions.
According to the State of AI in Finance 2026 report from CFO Connect, 56% of finance leaders say their teams now use AI, roughly twice the level reported in 2023. Yet only 17% say AI is integrated into their core workflows, while 45% remain stuck in limited pilot programs.
The problem, therefore, may not be the technology itself. It may be the people expected to use it.
Why AI Adoption in Finance Is Falling Behind
Finance departments have access to increasingly sophisticated AI tools, but many employees are still experimenting rather than transforming how they work.
That distinction matters. Asking an employee to use an AI chatbot for a small task is very different from redesigning an entire forecasting, reporting or planning process around AI.
The research suggests that many organizations have successfully purchased technology without creating the conditions necessary for widespread adoption.
For CFOs, that creates an uncomfortable situation: the investment has been made, but the expected return remains out of reach.
The Human Problem Behind Technology
Deloitte research cited by Forbes found that organizations taking a technology-first approach to AI adoption were 1.6 times more likely to fail to achieve their expected return compared with organizations that put people at the center of transformation.
Employees may resist new technology because they do not understand how it works, lack the necessary skills or worry about its impact on their jobs.
Trust is another major factor. If finance professionals cannot understand where an AI-generated result comes from, they may hesitate to rely on it for important financial decisions.
This means that successful transformation requires more than training sessions and software licenses.
Two Ways Companies Are Closing the Adoption Gap
Some organizations are approaching the problem by involving finance employees directly in the development process.
At payments company Adyen, controllers and FP&A analysts work alongside technical teams to help design AI use cases. This gives finance professionals a role in shaping the technology rather than simply receiving a finished product from IT.
Another approach is being used by Zapier, where AI adoption has been made effectively mandatory across the finance function. According to the research cited by Forbes, about 98% of Zapier employees regularly use AI tools.
The two strategies are very different, but they share an important principle: adoption cannot be assumed.
What Is Holding Finance Teams Back?
Several obstacles continue to slow AI adoption in finance.
One major issue is uncertainty about where to begin. CFO Connect research found that 68% of CFOs say they have been slow to adopt AI because they do not know which processes to target first.
There is also a skills gap. Finance leaders increasingly want to develop their existing employees rather than rely entirely on hiring new AI specialists, but building those skills takes time.
Trust, security concerns and fragmented workflows create additional barriers. Many employees are using general-purpose AI tools for individual tasks while still manually moving information between systems.
That is experimentation—not transformation.
