AI Turns Accounts Payable Into a Strategic Control Point

The corporate back office is undergoing a renovation, and accounts payable is at its center.

For decades, AP has lived in the shadows of corporate finance. Its success was necessary, unglamorous and relentlessly operational, measured in invoices processed, checks mailed, and exceptions resolved with minimal disruption.

When innovation arrived, it often meant incremental automation layered onto manual workflows. That era is ending.

Artificial intelligence is pushing AP out of the back office and into a more strategic role. As manual processes give way to intelligent decisioning, proactive fraud defense and data-driven payment optimization, AP is emerging as a source of liquidity, resilience and revenue.

“Folks are just starting to understand that AI isn’t just automation with kind of sexier marketing,” Finexio CEO and founder Ernest Rolfson told PYMNTS. “Embracing it as infrastructure lets you use your data as a strategic asset.”

That distinction matters. Automation speeds up existing processes. Infrastructure reshapes what is possible. When AI is embedded into AP workflows at an architectural level, it does more than reduce cycle times or headcount. It continuously learns from transaction data, supplier behavior and payment outcomes.

Read also: AI-Driven Accounts Payable: Elevating AP From Cost Center to Strategic Asset

AI as Infrastructure, Not Automation

Historically, AP scale has been constrained by labor economics. More suppliers, more invoices and more payment methods meant more staff. Or mounting risk. AI changes that equation.

“In the past, we’ve had folks with big call centers doing manual outreach,” Rolfson said. “You’re kind of hoping for a conversion rate.”

That model was never sustainable. Companies were “fighting a math problem with labor,” he said.

AI “really fixes that math,” Rolfson said. It enables high levels of personalization, precisely timed supplier outreach and scalable engagement without adding headcount, an especially critical advantage as companies face tighter labor markets and economic uncertainty heading into 2026.

The result is a compounding advantage. Unlike static rules engines, AI systems improve with every transaction, creating what Rolfson called a “competitive moat” for organizations willing to invest early.

Why Virtual Cards Still Haven’t Taken Off

Few areas illustrate the limits of legacy AP thinking better than virtual cards. Despite being available for years and offering benefits in speed, security and rebates, adoption remains low. Rolfson pegged countrywide adoption at roughly 7%.

The problem isn’t the product, he said. It’s the model.

“Companies are using static rules,” he said. “This supplier takes card, and this one doesn’t. It’s a bit of lazy thinking.”

AI introduces what Rolfson described as “dynamic decisioning,” optimizing payment methods at the transaction level based on fees, terms, supplier behavior and cash back tiers.

“It’s really not about necessarily getting the highest card acceptance, and more about optimizing the payment mix,” he said.

That level of complexity is beyond human scale.

“The team on the staff on the ground with a $50,000 or $60,000 base salary is not able to figure out this kind of level of complexity,” Rolfson said, and banks are rarely equipped to help.

Without AI-driven platforms, AP teams are left to manage supplier enrollment, retries, refunds and exceptions manually.

“Unless you’re doing anything over like 100 suppliers, forget about it,” he said. “You’re only going to get the tip of the iceberg.”

Turning AP Into a Revenue Engine

The key differentiator of modern AP solutions is architectural. Legacy providers “bolted payments onto existing AP workflows,” Rolfson said, often creating disconnected, manual processes. AI-native platforms treat payments as the platform itself.

“When every transaction can capture some earning, generate some float and reduce fraud losses, it’s shifting the mindset from AP as a cost center to a profit center,” he said.

However, technology alone isn’t enough, he said. The most successful AP teams share a distinct cultural mindset.

“They don’t want to be sending checks,” he said, citing higher fraud risk, higher costs and lower supplier satisfaction.

Instead, they actively promote electronic payments, especially cards, across contracts, websites and supplier communications. Payment strategy becomes part of supplier negotiations, with faster or more predictable payments used as leverage.

“Now we have supercomputers that can figure it out for you,” Rolfson said.

If payments optimization is one side of the AI-driven AP story, fraud prevention is the other.

“Now you’ve got AI that can generate invoices that look pixel-perfect,” Rolfson said. “You’ve got deepfake voices that can authorize wire transfers. They’re imperceptible.”

Phishing emails can pass every internal test. What was once “amateur hour” fraud has become “nation-state quality,” he said.

The only viable response is proactive defense built on AI, he said. That means validating identities in real time, confirming payment instructions on every transaction, and continuously checking suppliers against risk signals and fraudster lists.

AP may never be glamorous. But in an AI-driven economy, it is rapidly becoming one of finance’s most powerful levers.

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