Automation in accounts payable (AP) has made real progress. AI adoption is up, investment intent is strong, and most finance leaders believe their organizations are moving in the right direction.

But there’s a quiet disconnect hiding beneath the surface.

According to the Vic.ai AI Momentum Report, which surveyed nearly 800 finance and AP professionals, only 18% of respondents track advanced automation metrics such as no-touch or straight-through processing rates. In other words, while many teams are automating, very few are measuring how autonomous those processes truly are.

That gap matters — because without the right KPIs, it’s easy to overestimate maturity, underestimate risk, and miss the real return on AI investments.

Automation Is advancing faster than measurement

The AI Momentum Report also paints a clear picture of momentum:

• 72% of organizations now use some form of AI in finance
• 82% plan new AI investments in the next 12 months
• Over 80% say leadership is supportive of AI adoption

Yet when it comes to measurement, most AP teams are still relying on legacy KPIs designed for manual or rules-based environments. Commonly tracked metrics include:

• Invoice volume processed
• Cost per invoice
• Cycle time
• Invoices per FTE

These metrics are useful, but incomplete. They tell you how busy your team is, not how independent your automation has become.

Why traditional KPIs fall short

Traditional AP metrics measure effort and throughput, not intelligence or trust. An AP team can process more invoices per FTE while still relying heavily on manual review, rekeying, and exception handling.

This helps explain why other survey findings persist:

• 37% still cite manual data entry as their top AP pain point
• 44% of organizations still use some form of manual entry
• Many staff report double-checking AI outputs due to accuracy or trust concerns

In short, automation may exist — but autonomy often does not. And if autonomy isn’t being measured, it’s unlikely to be systematically improved.

Why “no-touch” processing changes the conversation

Advanced metrics like no-touch rate or straight-through processing (STP) shift the focus from how much work gets done to how much work no longer requires human involvement.

No-touch processing measures the percentage of invoices that move end-to-end — from ingestion through posting and approval — without manual intervention.

This matters because:

• Autonomy scales; manual review does not
• Fewer touchpoints reduce errors, delays, and burnout
• Trustworthy automation frees humans for judgment-based work

Yet the report shows that only 18% of AP teams actively track these autonomy indicators — suggesting many organizations don’t yet have visibility into how much work their AP automation solution is actually doing on its own.

Why advanced metrics lag adoption

So why are advanced automation KPIs still rare? The AI Momentum Report points to several contributing factors:

• Limitations from partial ERP integrations (despite 91% reporting some level of ERP sync)
• Continued human oversight needed due to accuracy or compliance concerns
• Cultural hesitation to stop checking AI outputs
• Lack of shared definitions for what “success” means

This connects directly to earlier findings in the report:

• Executives report higher AI usage (74%) than staff (50%)
• Staff often cite uncertainty, training gaps, and trust issues
• Adoption exists, but confidence lags

Teams are reluctant to measure autonomy when they don’t fully believe in it yet.

New benchmarks for AI maturity in AP

As automation becomes more intelligent, KPIs must evolve accordingly. Forward-looking AP teams are beginning to layer in metrics such as:

• No-touch / straight-through processing rate
• Exception rate (and exception quality, not just volume)
• Accuracy trends over time (learning curves vs. snapshots)
• Human intervention hours per 1,000 invoices
• Time-to-value metrics: how quickly automation reduces manual effort

These metrics don’t replace traditional KPIs — they complement them by revealing how much trust and autonomy the system has earned.

What leaders should do now

For CFOs and AP leaders, the takeaway isn’t that teams are failing — it’s that measurement hasn’t caught up with capability. Practical next steps include:

• Start tracking no-touch rates for a subset of invoices
• Align leadership and staff on what “working” actually means
• Use metrics to build trust, not just dashboards
• Tie autonomy metrics directly to ROI, morale, and scalability

As the report shows, 79% of organizations using AI already see measurable benefits — including faster processing, faster approvals, and improved employee satisfaction. Advanced KPIs are how those benefits become repeatable and defensible.

You can’t improve what you don’t measure

Only 18% of AP teams tracking advanced automation metrics isn’t a failure — it’s a signal of where the next wave of maturity will come from. The finance teams that lead next won’t just automate more — they’ll know, with confidence, how autonomous their processes truly are.

To access complete survey insights and results, download the AI Momentum Report.