Intuit is betting that within five years, the manual work consuming half a finance team's week - reconciliation, exports, error-fixing and report stitching - will be "largely invisible," handled by AI agents running continuously in the background. Ashley Still, executive vice president and general manager of Intuit's mid-market business, laid out that vision in response to questions from CFO Dive, detailing how the company's new AI capabilities aim to shift finance teams from monthly report production to real-time strategic work.
Still said the company's rollout includes two new capabilities for mid-market CFOs: Intuit Intelligence Chat, a conversational interface across Intuit Enterprise Suite, and more than 40 new AI skills that automate complex financial processes. The chat tool lets users query numbers and understand why they moved - like why margin dropped or spending spiked - with answers grounded in their own books and traceable to specific customers, vendors, products or accounts. The AI skills span payroll, multi-entity intercompany transactions and custom objects.
How AI changes daily finance work
Still described a concrete shift: instead of waiting for month-end close or a manually assembled dashboard, a CFO can ask how projects are tracking against budget and receive an answer in seconds across multiple entities. The system recommends next steps but only acts after the user confirms, preserving control and auditability.
"Rather than asking their teams or digging through reports, business and finance leaders can now ask Intuit Intelligence plain-language questions and get answers grounded in their own books, and find out what's behind an anomaly or a trend," Still said.
Accuracy, controls and pricing
On the question of accuracy and controls, Still said Intuit combines AI reasoning with deterministic accounting logics. "The numbers Intuit Intelligence cites come from deterministic calculations based on how an experienced accountant would do, not LLMs guessing the math," she said. Nothing is posted, transferred or finalized without direct approval, and an audit trail is maintained.
On pricing, Intuit has embedded AI value into its existing platform model while introducing a consumption model for Intuit Intelligence queries. Still said the industry is in the "early innings" on AI software pricing and predicted a hybrid approach will win.
"We do not believe that unconstrained token-based pricing will win, and we have already seen pushback from both businesses and accountants on companies that are relying on this model," she said.
Measuring ROI and avoiding common mistakes
For CFOs evaluating AI investments, Still pointed to concrete metrics: how much of the finance week is spent on reconciliation versus strategic work, how current the data is behind major decisions, and whether speed translates into a healthier bottom line. She cited Rhodes Companies as an example, which achieved a 15% EBITDA margin - its first year of profitability - after enabling rigorous revenue recognition and accrual-based accounting.
The biggest mistake CFOs make, Still said, is layering AI on top of fragmented data. "If your data is scattered across systems and spreadsheets, AI will just help you get to the wrong answer faster," she said. Many mid-market companies run seven to 25 different apps, and that sprawl limits their ability to gain real insight.
Before implementation, Still advised CFOs to consider three things in order: whether data is actually consolidated, what governance model exists with human judgment in the loop, and how fast they can get to value without lengthy, expensive migrations.
Why this matters for AI for CFOs
For finance leaders evaluating their AI strategy, Still's comments offer a practical checklist. The core takeaway: consolidate your data foundation before adopting AI tools, and measure success by whether manual work is shrinking and strategic work is expanding. As Still put it, the AI-powered CFO's advantage won't remain a differentiator for long - "it's just table stakes for running a finance function credibly." Finance teams that delay consolidation or treat AI as a bolt-on tool risk falling behind peers who've built their operating model around it. For those ready to move, resources like AI for CFOs can help structure the transition, while broader guidance on AI for Finance covers the wider applications across accounting and risk management.
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