Google Cloud has updated its Agentic AI Responsible Use Guidelines with explicit restrictions on fraudulent or unauthorised financial transactions. The document also requires appropriate approval before agents take financial, insurance, regulated, high-impact or reversible actions, and states that customers are responsible for permissions and third-party spending.

The wording matters because it draws a line between a platform’s general safeguards and the customer’s operating controls. An enterprise cannot assume that a cloud provider will determine whether an agent is authorised to move money, bind a customer, change a policy or incur external costs. Those decisions sit inside the organisation’s identity, entitlement and approval architecture.

For banks and insurers, the minimum control set should include purpose-bound identities for agents, least-privilege access, transaction limits, separation of duties and a reliable record of human approval. Reversible actions still need governance because reversal may not repair customer harm, data disclosure or market impact.

The updated guidance also creates a useful procurement test. Buyers should ask how a platform exposes tool calls, authorisation decisions, spend, overrides and failed approvals. The central question is not whether an agent is capable of acting, but whether every consequential action can be attributed, constrained and independently reviewed.

Execution Level Governance- What audit-ready agent governance actually looks like
David Girvin, founder and CEO of Assury argues that model-in-the-loop review, AI governing AI, is fundamentally unreliable for regulated environments: even the best-performing models miss a meaningful share of violations, the reviewing model is typically provided by the same vendor being reviewed, and prompt injection or context poisoning can compromise both the acting agent and its supposed overseer simultaneously. He makes the case for deterministic, architecturally enforced controls instead, walking through Assury's approach of autonomy zones, session risk accumulation, and credential starvation, which lets a compromised agent be cut off from its tools instantly rather than relying on time-boxed access. The conversation touches on why David is sceptical of just-in-time credentialing as a solution for agent security more broadly, since agent sessions don't run on predictable human timescales, along with the current gap between how identity and security vendors are pitching agent protection and what he sees happening at the execution layer in practice. He also discusses the compliance and audit implications of probabilistic decision-making, arguing that regulated industries will increasingly need tamper-evident, hash-chained audit trails that can withstand scrutiny from auditors and regulators who are only beginning to understand agentic risk, and reflects on a named frontier lab's own published framework as an example of the gap between research and practitioner reality. Elsewhere, David reflects candidly on building a bootstrapped security company in an increasingly crowded market, why he turned down aggressive VC funding to stay in control of the product, and what a credible third-party assessment of his own gateway would need to look like given that Assury sits directly in the execution path for every customer's agents.
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