Finance AI Adoption Is Stuck Between Speed and Control. CFOs Want Judgment.
Mid-market finance leaders have moved past "Should we use AI?" The real question is why every option still forces a trade-off: speed you can't audit or control that won't scale. A new Wakefield Research study surveyed 100 CFOs at U.S. companies with $50M-$500M in revenue. Between 60% and 77% plan to adopt AI depending on the use case, yet a clear trust gap is blocking execution.
Read the full report: Finance AI Adoption Benchmarking Report.
The Trust Gap Is the Story
96% of CFOs say AI's biggest benefit is freeing time for strategic work. Only 14% completely trust AI to deliver accurate accounting data on its own. And 97% say human oversight is critical. That's not a contradiction - it's the spec. Finance wants automation that proves itself and knows when to ask for help.
Two Broken Models
- Copilots: Useful, but still force accountants to review transaction by transaction. You get single-digit productivity gains and a new layer of review work.
- Black-box agents: Promise full automation but offer no way to verify accuracy, weak audit trails, and poor business context.
CFOs want neither babysitting nor black boxes. They want intelligent escalation - AI that runs on its own for routine transactions, but escalates ambiguity with full context.
What CFOs Are Asking For
One CFO put it cleanly: "We need an autopilot - fast, accurate and with the sound judgment of our most reliable accountant." Dominic Rand, CFO of Kiva Brands, shared: "Most tools either wanted full control with zero transparency, or they created more work for my team. What we needed was what Maximor delivered: AI that could handle the routine with speed and precision and knew exactly when to bring a human into the loop. That's when automation becomes a partnership, not a risk."
The Bottleneck Isn't Intelligence - It's Judgment
As foundation models improve, raw capability is less of a differentiator. What matters now is policy awareness, business context, and escalation discipline. As Ramnandan Krishnamurthy, co-founder and CEO of Maximor, said: "CFOs aren't asking for smarter AI - they're asking for AI that knows its limits. They need systems that are verifiable, operate autonomously when appropriate, and demonstrate judgment about when to act and when to escalate."
What Intelligent Escalation Looks Like in Finance
- Operates autonomously on routine transactions (coding, matching, variance thresholds) with measurable accuracy.
- Detects ambiguity and escalates with full context: inputs, reasoning, confidence, and recommended next steps.
- Produces a complete audit trail and decision trace for every action.
- Understands company policies, vendor nuances, GL structures, and materiality.
- Shows its work - so auditors and controllers can verify, not guess.
Evaluation Checklist for CFOs and Controllers
- Auditability: Do you get evidence, rationale, and a decision trace for every action?
- Accuracy: Is accuracy defined, measured on your data, and reported by use case?
- Policy encoding: Can you encode your approval rules, GL policies, and exceptions without vendor tickets?
- Escalation logic: Are triggers clear (confidence, amount, vendor risk, new pattern), and fully configurable?
- Controls: Support for segregation of duties, maker-checker, and SOX-friendly logs?
- Context awareness: Can the system learn vendor-level behavior, period cutoffs, and recurring edge cases?
- ERP fit: Works with your current ERP without forced migration or data duplication?
- Security and governance: Clear data boundaries, model usage, and breach response; aligns with risk frameworks like the NIST AI RMF.
- Time to value: Can you pilot a narrow process in weeks, not quarters?
Practical Rollout Plan (Start Small, Prove It, Scale)
- 30 days: Choose one routine process with volume and clear rules (AP coding, cash application, expense classification). Define acceptance criteria and escalation thresholds.
- 60 days: Pilot in production with read-write access under tight limits. Track accuracy, cycle time, and escalation rate. Refine policies.
- 90 days: Expand to adjacent workflows. Lock in audit trail exports, access controls, and retraining triggers for new vendors and accounts.
What the Study Signals
Finance leaders are asking for speed, verifiable accuracy, full audit trails, and intelligent escalation - automation that earns autonomy by showing judgment about when to act and when to ask. The line is clear: AI that can't show its work and doesn't know when to escalate is unacceptable in finance.
About Maximor
Maximor is an AI-native finance automation platform that helps mid-market and enterprise companies run accounting and operational finance with speed and confidence, without replacing their ERP. Its proprietary Audit-Ready Agent architecture uses AI that knows when to act autonomously and when to escalate, producing fully verifiable outputs and decision traces for every action. Customers close faster, eliminate manual grunt work, and scale finance operations without adding headcount. Learn more at maximor.ai.
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