Vendor-sponsored IT buyer surveys are free, appear regularly and usually include input from at least several hundred respondents. That makes them a useful sales intelligence tool for IT consultancies, which can use the polling to keep tabs on buyer priorities. Last month, Cisco and NTT Data commissioned a poll that shed light on the trends driving AI consulting deals. Today, Avalara published a survey of its own that looks at enterprise AI projects from a different angle. The software vendor collected data on what AI use cases CFOs are prioritizing, how they measure ROI and the challenges such projects face. That’s useful reading for the growing number of IT consultancies that compete for enterprise AI budgets. 

CFOs are a particularly important buyer cohort because they sign off on the AI projects of not only the accounting team but other departments’ as well. Avalara, which makes tax compliance software, polled 500 CFOs in the US and UK for its new survey.

The company first looked at the organizational factors that influence AI projects. It found, unsurprisingly, that stakeholder buy-in and talent availability are two of the most important considerations. Among the 71% of CFOs that told Avavara they are “very confident in their team’s ability to successfully adopt AI,” the most cited reasons for optimism were strong executive support and the availability of technical skills and training. The 29% of CFOs who stated they are not confident pointed to the same factors. In particular, many of those executives attributed their team’s AI challenges to fear of change at the organizational level and AI talent shortages.

Avalara also asked the respondents what AI use cases their teams are prioritizing. According to the company, 35% of CFOs who are already “diving into AI adoption” named real-time reporting as a top use case. It was tied for first place with expense management, which was likewise listed by 35% of the participants. Much of the work involved in expense management involves copying information from physical receipts to an accounting application. That task can largely be automated using a type of AI algorithm known as an OCR, or optical character recognition, model. Many popular accounting tools include OCR features, which means the technology is fairly easy for enterprise finance teams to adopt. That was likely one of the reasons so many of the survey respondents listed OCR. 

Avalara’s next set of questions focused on CFOs’ AI investment roadmaps. The company says 16% of the respondents named regulatory intelligence, or the task of tracking changes in financial regulations, as a top investment priority. Another 15% said they’re focused on building AI agents. 

Avalara also collected data on what AI investments CFOs aren’t making. Survey respondents told the company that e-invoicing and cross-border compliance are the use cases “most likely to keep them up at night,” yet those use cases are not a major focus of AI initiatives. One reason might be there aren’t too many AI tools on the market today that can automate those tasks. 

Avalara wrapped up the poll by asking CFOs how they plan to measure the success of their teams’ AI projects. The business goal most commonly associated with enterprise automation initiatives is cost cutting. In the case of finance departments, however, that’s apparently not always the main goal. The most commonly cited measure of success among the survey respondents wasn’t cost cutting but rather compliance improvement. Just over a third of the respondents, 36%, listed it as their primary success metric. Cost cutting was tied for second place with error reduction, improved decision making and revenue improvement at 31%.

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