What is Holding Back AI Adoption in Enterprise Finance?

AI is becoming a valuable tool across business sectors, transforming how companies operate and improving efficiency. 

In the finance sector, however, adoption has been slower as leaders determine how to use these tools and whether the return on investment is worthwhile.

A report from Spendesk titled ‘The State of AI in Finance’ highlights this cautious approach. 

As the technology develops, the report finds that some finance leaders are demonstrating that AI can solve real-world challenges and unlock new opportunities. 

While the adoption of AI tools in finance has progressed in the last year, the report shows that 61% of teams have not yet implemented AI into their workflows.

Despite this, there is considerable optimism about its potential, with 85% of Chief Finance Officers (CFOs) positive about the efficiency gains AI could bring to their teams. 

Common objections holding back implementation include the unclear benefits of using AI, the limited skills or training in existing teams and the time it would take to overhaul current processes.

Axel Demazy, CEO of Spendesk, says: “Gen AI has accelerated access to AI; and when you look at how steep that acceleration is, you can tell the inflection point is far from being reached. 

“We have only scratched the surface of how AI can augment human operations at scale in all our workflows, and we will see continued investment by businesses as a result.” 

The report is based on discussions with hundreds of CFOs from the CFO Connect community, a private network for finance leaders.

Unclear ROI and skills gaps

According to a late 2024 CFO Connect survey, most CFOs acknowledge the potential for efficiency gains but are uncertain about how and where to begin. 

The primary concerns identified were related to return on investment and team capabilities.

The main factors holding them back are:

• unclear benefits of AI (36%)
• limited skills or training (32%)
• time constraints (14%)
• data privacy or security concerns (12%)
• lack of leadership support (5%)

Spendesk’s research indicates that many finance leaders perceive AI as a tool for simple, everyday tasks such as drafting emails or for use by other departments like marketing and sales. 

While CFOs express concern that their teams may lack the skills to adapt, Finup360’s Founder Anne-Claire Chanvin says we’ve seen this transformation before: “This change is as big as when Excel was introduced in the 1980s. It completely transformed how they worked, and today AI is bringing the same kind of change.”

AI opportunities in finance operations

AI is proficient at handling tasks that are rule-based, repetitive and time-consuming, which could free up finance professionals to concentrate on higher-value activities that require human judgement. 

However, this focus on mundane work can have a negative impact on employee retention. 

“We keep seeing demotivated junior staff stuck doing basic work. No wonder there’s such high turnover in finance teams” says Bogdan Năforniţă, CEO and Co-Founder of Profluo and previous Chief Financial Officer at BMW.

Many of these repetitive tasks are ideal candidates for AI-driven automation. 

Sarah Fu, Founder and Managing Partner of Elsa Capital, says: “Finance teams all do these very repetitive things: creating the same slide deck, do a weekly, biweekly, monthly refresh, or rebuilding models. With LLMs, there’s the opportunity to do those repetitive things a lot better.”

Enhancing reporting and internal controls

Reporting is another area where AI could deliver substantial enhancements. 

Anne-Claire gives an example where a reporting task was dramatically streamlined, saying: “it was a task that previously took one day per accountant, per country. Using the script [referring to a ChatGPT script], it only took five minutes.”

Beyond reporting, AI can be used to review communications, presentations and reports to ensure consistency with industry standards. 

This capability extends to internal audit functions, providing a secondary check on accounting procedures.

Paul Jun, former Vice President of Corporate Finance and Strategy at DropBox, explains: “If you feed an AI tool the ASC 606 memo that your auditors use and a revenue contract, it can go through it and see if you’ve written your ASC 606 memo consistently with the handbook and consistently with your model customer contract.

“It’s almost like an internal audit function, to do a second check through some of the accounting procedures and memorandums you may have.” 

The Spendesk report highlights the waiting potential of AI in finance, with clear applications in simplifying reporting, data analysis, invoices, expenses and document reviews.