Goldman Sachs Puts AI Agents to Work and the Back Office Feels it First

Goldman Sachs does not need to be debating with a bot anymore, but delegating the work, and it is doing so with Anthropic.On Friday, 6 February 2026, Goldman confirms that it is constructing AI-powered agents with Anthropic to automate internal banking processes like trade and transaction accounting, client due diligence, and onboarding. Anthropic engineers directly interact with Goldman teams and the work is ongoing, which has been in place for approximately 6 months already. The objective is simple: reduce the time spent on reconciliation of trades, checking of clients and opening accounts.This would be autonomy instead of sounding like normal automation. These applications do not merely imply text. They operate within a workflow: they read documents, retrieve data in internal systems, invoke rules within guardrails and direct work to the subsequent step. That is important in banking since the back office is the place where minor mistakes turn into major problems and where a compliance project silently swallows up its own days.The concept of the AI agent is moving from demos to controlled and high-stakes work. The move by Goldman comes at a time when other players in the market are moving agent infrastructure into the center stage. Individually, OpenAI has released enterprise tooling to assist organisations in creating and managing AI agents, a sign that agent management is emerging as an aspect, rather than an attribute.The concept of AI agents may be unclear, and this is the realistic image of the case: a digital co-worker who has a limited job description.These functions are rule-heavy and constant, and repeatable. They are also the creators of the documentation that the regulators expect a bank to maintain.The CIO of Goldman, Marco Argenti, indicates tthat he most important aspect of the bank is time. When an agent shortens multi-step checks from hours to minutes, the bank does not save money alone. It is quicker in responding to client requests, market moves and compliance inquiries.The majority of AI used in the workplace is still the dumb autocomplete. It assists you in writing a memo, report on a meeting or writing code more quickly. You remain the operator.This is also the reason why enterprise tooling is important. As vendors discuss agents, a lot of businesses now request the other missing component: how to safely deal with them in large numbers. According to TechCrunch, OpenAI is entering the business of managing agents and positioning it as enterprise infrastructure to adopt.Why then should banking be a proving ground? Due to the fact that the banking affairs are already conducted like assembly lines. Each stage has its inputs, outputs, approvals and logs. The latter structure simplifies the process of agent insertion, impact measurement, and rapid failure identification.It also forces discipline. On day one, model risk teams, compliance, and internal audit provide the same questions:

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