More than 90% of chief financial officers who deploy AI agents say the technology has delivered on its promised return on investment, according to the Salesforce CFO Priorities Report published this year. The research found that 74% of CFOs report their job responsibilities have grown over the past year, with roughly half now serving as lead decision-makers for their company's AI strategy. Financial leaders are increasingly relying on autonomous AI agents to manage complex revenue models, automate routine tasks, and improve operational health across their organizations.
The data reveals significant shifts in how finance teams operate and where they're investing. About 71% of finance leaders now sell through more channels than they did a year ago, spanning direct sales, web-based self-service, partner networks, social platforms, and mobile channels. Nearly two-thirds track transactions across multiple revenue models and hybrid arrangements. The biggest driver of revenue complexity is consumption-based pricing, which 87% of finance leaders plan to expand in the future. Current revenue models break down as follows: subscription or recurring products account for 46%, professional services 46%, consumption-based 43%, one-time sales 38%, and hybrid models 35%. Finance teams estimate that 6% to 15% of their transactions contain errors during the quote-to-cash process, while 67% report that a fifth of their work is now manual, eating up many hours each week.
AI agent adoption is accelerating across large enterprises. Companies with revenues of $1 billion or more show that 62% have either launched or are building AI agents, up from 53% last quarter. The average number of AI agents activated per organization has nearly tripled since 2025. More than 90% of finance leaders using AI agents say the technology is cutting costs, boosting productivity, speeding up decisions, strengthening compliance, improving communication, and sharpening forecast accuracy. Among those seeing results, 56% describe the ROI as significant. Yet concerns persist: 46% cite security worries, 42% flag governance issues, and many point to accuracy challenges.
The report explains that CFOs now oversee a wider technology stack, more revenue models, greater complexity, larger investments in sales strategies, and heightened governance demands as AI use cases multiply rapidly. The top five priorities for CFOs in 2026 and 2027 are improving forecast accuracy, improving operational efficiency, improving compliance, improving data accuracy, and scaling use of agentic AI. Finance leaders are hampered by isolated data and outdated technology systems that make tracking financial information across multiple revenue channels costly. Without tight integration across the broader tech stack, finance teams face data errors and workflow slowdowns. CFOs are now looking to AI agents to automate as much as 40% of finance teams' work. The research makes clear that becoming an agentic business operating at both human and machine scale will require trusted, accessible data, strong governance, and leadership that fosters urgency for business transformation led by AI-powered products, services, and processes. The mandate is clear: financial leaders must champion the adoption of digital labor or risk falling behind competitors who do. For organizations hesitant to embrace autonomous systems, the window for cautious experimentation may be narrowing faster than many boardrooms realize.