How AI Is Rewiring Accounts Payable: From Automation to Autonomy

Four forces are reshaping finance operations faster than many predicted.

• AI moving from pilots to production
• Regulation shifting toward real-time compliance
• AP networks expanding reach and connectivity
• Composable ERPs redefining how finance stacks are assembled

Each force matters. But as they converge on accounts payable (AP), AI stands out as the primary catalyst – turning AP from a necessary cost center into a compounding source of financial and operational intelligence.

In my work with finance leaders implementing Invoice Lifecycle Management, I see AI in AP increasingly treated as a strategic execution layer, not just another automation project.

This does not diminish the importance of the other forces at play. Regulatory demands are accelerating toward real-time compliance. AP networks are extending global connectivity. Composable ERPs are increasing flexibility. Yet AI is delivering the most immediate, measurable impact.

According to Basware’s AI to ROI: Unlock Value with AI Agents report, 85% of finance leaders report achieving ROI from AI investments – underscoring AP’s strong potential for continued digitization and value creation.

The real differentiator is not AI in isolation. It is the quality, completeness, and continuity of data across the entire invoice lifecycle.

This approach (ILM) moves beyond task-level automation. It transforms processing speed, accuracy, efficiency, and analytics related to supplier health, purchasing patterns, cash flow, and operational performance.

The following customer examples demonstrate how AI is modernizing AP in practice – and how ILM extends far beyond traditional automation.

From 20 days to five: RadNet replaces OCR with intelligence

RadNet operates more than 400 imaging centers across the United States. Its OCR-based processes struggled with low-quality, handwritten documents, and only 40% of invoices were tied to POs. The remainder required manual handling. As the business grew, invoice volume increased – and so did staffing demands.

RadNet replaced OCR with SmartPDF, an AI solution trained on 2.3 billion invoices. SmartCoding was added for non-PO invoices, using machine learning to continuously improve accuracy and enable straight-through processing. AP teams remained in control, reviewing and refining coding suggestions where needed.

The results:

• 85% of PO invoices processed without manual intervention
• Invoice cycle times reduced from 20 days to under five

Jacob Simon, National Director of Purchasing, described the shift as “moving from a cost center to a profit center.”

AI did not remove AP from the loop. It removed busywork, allowing the team to focus on higher-value, strategic work – with every AI suggestion remaining reviewable, overridable, and fully auditable.

Instant learning, immediate impact: Billerud cuts costs by 66%

Billerud faced slow validation cycles, manual checks, and high error rates. Its PDF extraction process was adding cost rather than eliminating it.

The company implemented SmartPDF with AI Instant Learning. Unlike traditional OCR, which requires supplier-specific training, this AI adapts dynamically – learning in real time from invoice data as it flows through the system.

The impact was immediate:

• Invoice processing costs reduced by 25%
• PDF extraction costs reduced by 66%
• Rapid time-to-value as the AI improved from day one

AI trained on a global dataset supported AP teams with broader, pattern-based insights.

95% touch-free processing: Belden’s end-to-end view

Belden recognized that fixing AP in isolated stages would not deliver transformation. While individual steps were automated, the system could not learn across the full invoice lifecycle. Processes remained disconnected.

The solution was embedding AI end-to-end.

With SmartPDF handling intake, validation, and routing, learning occurred at every stage. As AI connected each invoice’s journey, performance improved with every transaction.

The result: 95% touch-free processing.

When AI operates across the full lifecycle – not just at a single checkpoint – it compounds intelligence over time.

Autonomous beginnings

Organizations implementing AI in accounts payable report an average ROI of 36% on million-dollar investments. These results help explain why AP is often the starting point for broader finance modernization.

AP combines:

• High transaction volumes
• Structured data
• Clear approval logic
• Repeatable processes

These conditions are well suited to AI.

That combination of rich operational data and embedded controls is what allows AI in AP to move beyond simple task automation toward policy-bound autonomy, where agents can propose or take actions within clearly defined guardrails.

This holds true even in complex enterprise environments involving thousands of suppliers, formats, tax requirements, currencies, and terms. While many tasks remain repeatable, edge cases are constant. Static automation struggles under this variability. Adaptive AI thrives on it.

This is where integrated platforms such as Invoice Lifecycle Management make a measurable difference. Traditional ERP-based automation often requires heavy customization to manage invoice variability, while ILM is designed to adapt as business rules evolve and regulatory requirements shift.

Beyond efficiency gains, the volume and richness of lifecycle data train AI to support increasingly complex tasks. AP automation becomes the governed foundation for more advanced agent-based capabilities – moving organizations closer to higher levels of trusted autonomy across invoicing processes.

AI-driven transformation in AP and finance is still evolving. But the direction is clear.

Accounts payable is becoming faster. More strategic. Increasingly autonomous.

Ready to turn AI into measurable ROI?

Discover how finance leaders are moving from experimentation to results.

Read the report: AI to ROI: Unlock Value with AI Agents and explore the data, benchmarks, and real-world outcomes shaping the future of AP.