Financial institutions and tech providers are homing in on myriad use cases for agentic AI in B2B transactions, which could see higher adoption than in the consumer space.  

AI agents are poised to succeed in the B2B payments sector due to its structure, addressable size and grounded principles, Andrew Jamison, chief executive of spend management company Extend, told FinAi News. 

Total agentic commerce transaction value in 2026 is expected to be $8 billion and may reach $3.5 trillion in 2031, think tank Juniper Research estimated in an April report. 

In B2B payments, there are specific invoices — known payment rails, receivables and payables — which have little grey area, reducing errors and maximizing agentic deployment, Jamison said.  

“I think on the consumer side, it goes in 50 directions, and I think that makes it a little bit harder,” he said. 

Grounded in truth  

B2B is becoming a better proving ground than consumer because it is more grounded in truth, Jim McCarthy, CEO of B2B payments processing and issuance platform Thredd, told FinAi News.  

“There’s a purchase order, an invoice, a contracted rate, all of which offers a documented expectation the agent’s action can be checked against,” he said. “That makes the work verifiable, and verifiable work is the only kind you can safely delegate to an agent at scale.” 

Conversely, with consumer payments, many variables can create complexity in agentic adoption, Andrew O’Connor, agentic AI lead at PSE Consulting, told FinAi News. 

The agent must have predefined spending instructions, avoid fraud and find a product that the consumer will approve, O’Connor said. 

“From a retail perspective, if somebody wants X amount or certain types of trainers [shoes] — the brand, the sizing, what the retailer is, adds complexity,” O’Connor said. “There’s less choice and less variability in the B2B space, which reduces the complexity and the potential for something to go wrong.” 

Ample use cases 

There are numerous opportunities to deploy agentic AI in B2B transactions before and after the payment, Thredd’s McCarthy said.  

Before a payment, AI agents can handle tasks such as supplier verification, onboarding and policy enforcement, he said. 

“An example would be an agent provisioning a virtual card scoped to a specific supplier, amount and window, so the control is structural rather than a rule someone has to police afterward,” he said. 

After a payment, McCarthy said agents can reduce an “enormous amount of skilled finance time” by handling tasks including:  

• Invoice-to-transaction matching; 

• Exception handling; 

• Dispute initiation; and 

• Reconciliations.  

Although agentic payments are ripe for the B2B space, the industry must collectively decide where liability lies for adoption to take off, PSE’s O’Connor said. 

Register here for the FinAi Lending Summit, set for Oct. 7-8 in Las Vegas. This inaugural event will include speakers from Fifth Third and Capital One as well as a fireside chat with Piermont Bank founder and Chief Executive Wendy Cai-Lee.