Many finance chiefs are under pressure to meet growing demands with tight resources. Prophix CEO Alok Ajmera sees artificial intelligence as a way to close that gap, allowing finance teams to expand their capacity without increasing headcount.
Ajmera — whose firm provides software tools for CFOs — expects AI to lead more to slower hiring than widespread layoffs, as finance teams become more productive and take on additional work. Some jobs could be displaced as the skills finance organizations need change, he said.
“I think AI is going to be an enabling function for scale,” Ajmera said in an interview. “When you get more productive, you don't say, ‘Well, let's just do less. You say, ‘Let's do more.’”
Gartner research released earlier this year found that overall headcount growth expectations fell to 2% for 2026, down from 6% a year earlier.
More recently, Datarails found that 60% of CFOs and finance leaders surveyed are redeploying staff to higher-value work as AI takes on more finance tasks, while 3% said they are actively reducing headcount where AI has replaced work.
Ajmera said finance teams are still largely using AI for relatively low-risk, content-heavy tasks such as generating narratives, analyzing reports and producing variance explanations. Those tools can save users roughly four to eight hours a week, or the equivalent of a 10% to 20% productivity improvement, according to his estimate.
AI is already useful for interpreting and communicating financial information, he said. The next step is embedding AI more deeply across finance workflows, including tasks involved in closing the books.
Boston Consulting Group said in June that leading organizations could move toward AI-first finance functions within two to five years, with AI agents handling more finance activities and the number of staff needed for today’s workflows potentially falling by half.
However, the path to deeper AI adoption in finance remains difficult, with trust being one major obstacle.
CFOs are generally comfortable with AI reading financial data, generating narratives and producing reports, Ajmera said. They are much more cautious about allowing AI to touch financial data or take actions that affect budgets, forecasts and other financial results.
That hesitation is reflected in the latest Datarails survey. Seventy-five percent of respondents cited a lack of auditability as an obstacle to trusting AI for mission-critical finance tasks, followed by concerns about accuracy and hallucinations at 71%. Only 5% said they trust AI to produce board-ready financial reports without human review, while 4% trust it with month-end close.
Ajmera expects AI agents to take on more finance workflows as trust grows, initially with humans monitoring and approving their work. The shift, he said, will be from AI helping finance teams analyze information and create content to AI executing precise, repeatable processes.
“In finance and accounting, every number has to be 100% correct. You cannot have any variation,” Ajmera said.
