A striking data point from CFO Dive: only 43% of CFOs say they trust their own organisation's AI governance. That figure was uncomfortable when AI tools were mostly assistive, drafting a memo, summarising a report, suggesting a forecast adjustment. It becomes far more consequential as agentic AI moves into finance functions, because agents do not just suggest, they act. An agent that can initiate a transaction, adjust a model, or trigger a workflow without a human in the loop changes the nature of the risk entirely, and the CFO Dive piece is right to flag that most governance frameworks were not built with that shift in mind.
What this means
For a founder, a PE portfolio-company operator, or an SME owner, this is not an abstract governance debate happening at large enterprises with dedicated risk teams. It is a live question about whether the tools you are already adopting, or about to adopt, have any real controls around them. Sub-$100M businesses tend to move faster on new technology precisely because they lack the bureaucracy of a large corporate, but that speed advantage becomes a liability the moment an AI agent has access to financial data, forecasting models, or transaction workflows without a defined boundary of what it can and cannot do on its own. The CFO trust gap the source highlights is not really about whether AI works. It is about whether anyone can explain, after the fact, why the agent did what it did.The wider picture
Finance functions have absorbed a wave of AI tooling over the past few years, largely on the assumption that human review would always sit between the tool's output and any real-world action. Agentic AI removes that assumption. As vendors push agents that can execute multi-step tasks autonomously, the pressure on finance teams shifts from evaluating whether the output is accurate to evaluating whether the process that produced it can be trusted and traced. This is playing out across audit, reporting, treasury, and deal execution, wherever finance data touches a system with the ability to act rather than just advise. The businesses that get ahead of this are not the ones adopting AI fastest, they are the ones building the governance layer at the same time as the capability, rather than retrofitting it after something goes wrong.How we think about it
Our approach to AI readiness starts with an assessment, not a rollout. We look at where AI tools already sit in a client's finance and deal processes, where agentic capability is likely to arrive next, and what decisions genuinely need a human checkpoint versus what can be safely automated. From there, we help deploy assistants and agents with governance built into the design: defined permission boundaries, clear escalation points, and an audit trail that records what an agent did and why, so that if a regulator, an investor, or a buyer asks the question later, there is a straight answer. This is deliberately practical work, sized to the resources an SME or a portfolio company actually has, not a framework lifted from a large enterprise that nobody will maintain.Where we can help
If you are already using AI tools in finance, or planning to, the question worth asking now is whether you could explain every consequential action one of those tools has taken in the last quarter. If the answer is uncertain, that is the gap to close before it closes on its own terms. We help SME owners, founders, and portfolio-company operators build that readiness properly, so AI becomes a genuine advantage rather than an unmanaged exposure sitting inside the finance function.If you want your firm AI-ready, safely, Book a consultation.
