Agentic AI seems poised to revolutionize financial services, although there are risks that could stymie its momentum.
The U.S. market for agentic AI in financial services is projected to reach $24.2 billion in 2034, up from $1 billion in 2025, according to research and consulting firm Market.us.
However, “runaway agents” could disrupt the market, Kareem Saleh, chief executive of FairPlay, an AI enablement company for FIs and insurance providers, said last week at Fintech Meetup in Las Vegas.
Runaway agents are AI agents that loop endlessly, execute unnecessary actions, bypass intended goals or retry tasks without learning, Demis Hassabis, CEO of AI research lab Google DeepMind, wrote in a Feb. 21 blog post.
These errors often occur because of:
- Poorly defined goals;
- Missing logic that determines task completion; and
- Human-in-the-loop inadequacies.
For FIs, the consequences of these errors could snowball quickly because AI agents travel in swarms, FairPlay’s Saleh said.
For example, an insurance company may instruct an AI agent to respond quickly to customers, Saleh said. The ambiguity of this request could cause an agent to prematurely deny a claim, and a swarm of other agents may mimic this behavior shortly after.
“Now you’ve got emergent misbehaviors like algorithmic collusion, where the agents tend toward anti-competitive behaviors,” Saleh said.
These patterns also lead to “coordination failures,” which occur when agents misunderstand task boundaries or sequences, he said.
“And then you’ve got this problem of cascading errors, where a mistake or a false assumption by one agent now becomes an input to a series of other agents,” he said.
Other potential issues with runaway agents include data leaks and adversarial attacks that manipulate machine learning models, he said.
Agentic AI risks are surfacing at a time when FIs are using the technology to drive efficiencies in areas including:
- Customer service;
- Lending;
- Sales; and
- Payments.
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