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Will AI Agents Be Standard in Finance Operations by 2031?

How far agents have come in five years, what the forecasts say, and why adoption won't be even across processes or firms.

In brief

The question for a CFO right now is whether to wait for agents to mature or start now. Nobody can say for sure what 2031 looks like. What I can do is set out how fast things have moved since 2021, what the main forecasters say, and where I think agents will and won't become standard in payments and finance operations.

Five years back

In 2021, automation in finance operations meant rules engines and RPA bots. AI models could write fluent text, but firms didn't use them on ledgers or payments. The changes since then came in a few steps.

WhenWhat changed
June 2020GPT-3 writes convincing paragraphs and makes up facts freely. Nobody lets it near a process.
November 2022ChatGPT. Models become useful for drafting, summarising and answering questions about text you paste in.
June 2023Function calling. OpenAI lets models ask outside code to fetch data or take an action, and other model makers follow. This is the basic building block of an agent.
November 2024Anthropic publishes the Model Context Protocol (MCP), a standard way to connect a model to a firm's systems.
2025 to 2026Finance and payments vendors ship agents to paying customers, in reconciliation (BlackLine, Trintech), AML alert review (Hawk, Unit21) and chargebacks (Justt, Gradient Labs).

How fast it's moving

Two measures give a sense of the pace.

The first is how long a task a model can complete. METR, a research group, measures this as the time a skilled person would need for tasks a model gets right about half the time. GPT-4, in March 2023, managed tasks of about 4 minutes. Claude Opus 4.6, in February 2026, managed about 12 hours. That length has doubled roughly every four months since 2023. Two caveats: the tasks are software tasks, and at an 80% success rate the lengths are several times shorter. Finance teams need far better than 80% before letting an agent near a ledger, which is why the approval step matters.

The second is price. Epoch AI found that the price of reaching a given level of model performance fell by between 9 and 900 times a year, depending on the task. Matching GPT-4 on a set of hard science questions got about 40 times cheaper each year. An agent that's too expensive per case today may not be in two years.

Adoption in UK financial services is further behind the technology. In the Bank of England and FCA survey from 2024, 75% of firms used AI in some form, but only 2% of their AI use cases were fully autonomous.

What the forecasters say

So Gartner expects agents to spread quickly and a large share of early projects to be cancelled at the same time.

Where I think agents will be standard, and where they won't

This is my reading, based on the vendor scan behind ScalePoint Research, which looks at 51 payments and finance processes across six types of firm.

High-volume case work goes first

Reconciliation breaks, chargebacks, AML and sanctions alerts, and payment repairs have a lot in common. There are many similar cases, each one needs several systems, and a person can check the result. Agents for all four are already on sale in 2026, and the cost per case keeps falling. I expect an agent working the queue, with people approving, to be the normal set-up for these processes well before 2031.

Decisions the rules give to a named person stay with a person

Filing a suspicious activity report, deciding a complaint, approving a merchant's risk terms or a deal price all sit with accountable people under the rules. An agent can gather the facts and draft the decision, and that alone saves most of the time. I'd expect the line on who decides to move slowly, and only as regulators get comfortable.

Some processes have no agent products yet

In the scan I found no AI product in Europe for acquirer deal pricing or FX margin review, and none that assesses a complaint against the FCA's complaint rules. These may need building in-house, or they may simply lag.

Big firms and small firms move at different speeds

Large banks are building their own agents. BNY's handles over 10% of its payment repairs, according to a Microsoft customer story cited in coverage of Sibos 2026. Mid-sized firms will mostly buy from vendors. Smaller EMIs and PSPs depend on whether their existing tools add agents, and several UK tools for safeguarding and scheme reporting don't use AI at all yet.

Data access sets the pace

An agent can only use the systems it can reach. A firm whose settlement files, ledger and contracts sit behind APIs can run an agent today. A firm whose contracts are PDFs in a shared drive has groundwork to do first, and that groundwork is likely to decide its timing more than the models will.

What I'd do in 2027

Sources

This is one of four pieces on AI agents in finance and payments operations. The series, and the research map behind it:

martin@scalepointpartners.com