The latest wave of artificial intelligence (AI) isn’t about better chatbots or faster content generation. It’s about delegation. The emergence of agentic AI is the story of an innovation moving beyond just automation. These secret AI agents are being built into autonomous software workers capable of making decisions, executing tasks and collaborating in ways that were once the exclusive domain of humans.
And in financial services, payments and B2B commerce, the utilization of agentic AI is already underway.
The depth of insights from recent conversations with payments industry leaders for the “What’s Next In Payments: Secret Agents” series reveals four defining themes foundational to how the marketplace is thinking about the impact of agentic AI applications across payments:
The AI agents are here. They don’t sleep. They don’t get tired. And, increasingly, they don’t need to be told what to do next when it comes to solving real-world business problems.
The only question left is whether companies are ready to hire them.
AI Agents Are Autonomous Operators, Not Just Tech Tools
Across sectors, AI is evolving from passive support (e.g., content generation, search) into autonomous agents that execute complex workflows, make decisions and interact with systems in real time.
These aren’t just advanced macros or rule-based systems. Today’s AI agents observe, learn, act and reason, often without direct supervision.
“We now actually think of agents as one of the boxes in our org chart,” i2c CEO and founder Amir Wain told PYMNTS, noting that it’s a philosophical shift.
“It’s not about being fancy. It’s about being effective,” Wain said.
These AI agents are showing the most potential across contact centers, developer workflows, payment orchestration, underwriting systems and fraud detection units.
“We’re quite bullish on agentic checkout and agentic commerce,” Nabil Manji, SVP head of FinTech growth and financial partnerships at Worldpay, told PYMNTS. “We’re actively using AI to improve our customer onboarding and underwriting journey — something the whole financial services sector has been trying to crack for years.”
“It’s not just about automation; it’s about delegation,” Coupa Product Strategy and Management SVP Rajiv Ramachandran said. “AI agents aren’t just processing invoices. They’re deciding whether to move money, how much, when and to whom.”
Governance, Trust and Responsible AI Are Non-Negotiables
With great autonomy comes great responsibility. As AI agents gain power, the accompanying risks grow, too. Unlike traditional AI systems with deterministic outputs, agentic AI is probabilistic, non-linear and unpredictable by nature. This can increase the governance burden.
“This isn’t a technical upgrade. It’s a governance revolution,” Kathryn McCall, chief legal and compliance officer at Trustly, told PYMNTS. “You’re messing with people’s money here.”
“You’ve got to treat these AI agents as non-human actors with unique identities in your system. You need audit logs, human-readable reasoning and forensic replay,” McCall added. “Can your agent initiate invoice creation but not approve disbursement without human review? What’s the scope? What are they allowed to do and what are they not allowed to do?”
Forward-looking companies are embedding trust into their tech DNA, building in guardrails like explainability, human oversight and ethical fail-safes to avoid costly missteps and ensure accountability.
“Payments is a zero-error industry,” Boost Payment Solutions Chief Operating Officer Illya Shell said. “Taking calculated risks is okay. But they’ve got to be very thoughtful and meticulous.”
After all, whether it’s autonomous B2B payments or AI-powered budget assistants, success hinges on ensuring end users (and internal teams) believe in the system.
“The bedrock of all of this is going to be trust with the member — and building that trust takes time,” Elizabeth Wadsworth, senior innovation strategist at Velera, said.
Infrastructure Rebuilds Can Scale Agent-First Operations
But the shift isn’t plug-and-play. Agentic AI is exposing serious infrastructure limitations, especially in payments and finance. AI agents demand real-time, scalable, secure infrastructure. Legacy systems can’t handle thousands of concurrent autonomous agents acting on APIs, analyzing data and triggering actions across systems.
“People underestimate what it takes to support this at scale,” Edwin Poot, chief technology officer at Thredd, said. “You’ll deploy agents per transaction — this will require changes to the infrastructure.”
Companies are rebuilding platforms for agent orchestration, simulation environments, serverless compute, federated data access and tokenization.
Stax Chief Technology Officer Mark Sundt told PYMNTS that if agentic AI is the engine, orchestration is the transmission. Without a central conductor, even the most capable agents act in isolation.
“You’ve got agents to agents … but who’s driving the process?” Sundt said. “Who’s doing the orchestration?”
Intelligent Commerce and Payments as the Proving Ground
Agentic AI is being battle-tested first in the payments and commerce ecosystem, especially for fraud detection, cross-border transactions, B2B automation, customer engagement and personalization.
“Cross-border payments aren’t optimized,” Boost’s Shell said. “But agentic AI can help us streamline the front end to ensure we know exactly who’s paying whom, and that the payments are geared in the right way to get out the door quickly.”
Agentic AI is also forcing a complete rethink of how online commerce happens. These agents don’t click on banner ads or fall for marketing copy. They optimize for price, shipping and past behavior.
“When AI agents shop on your behalf, they don’t see advertisements the way humans do,” said i2c’s Amir Wain. “They just look for real value.”
This space offers rich data, real-time needs, and high-stakes outcomes — making it the ideal launchpad for agentic AI’s full capabilities.
