That speed is exciting. But there’s also risk involved.

The accountability gap that needs to be addressed

When a team member makes an error, the accountability chain is straightforward. When an AI agent makes an error—one that it was authorized to make as part of a workflow you approved—the chain is murkier.

The implications are significant for accountants. You carry professional liability. Your signature, or your firm's name, means something specific and legally consequential. When AI acts on your behalf, your name is still on the output.

The same report found that data security concerns among accounting professionals have risen to 83%, up 7% points in a single year. This concern makes sense. What doesn’t make sense is adopting agentic workflows without building the governance structures to match.

Many tools being marketed as agentic AI are closer to advanced automation, but true agentic systems adapt when conditions shift. That adaptability is their value, and it's exactly what makes accountability harder to pin down.

3 questions to answer before you hand over the wheel

You don't have to pause AI adoption. But before any agent starts acting autonomously on client work, your firm needs clear answers to these:

1. Who reviews and approves? Every agentic workflow should have a defined human in the loop checkpoint. That needs to be a specific role, not just 'a team member,' who is responsible for reviewing AI-generated outputs before they reach a client or are acted on.

2. What can the agent not do? Every agentic deployment should have explicit guardrails. These make it clear which actions it is not authorized to take without human approval.

3. How do you audit what it did? If something goes wrong, you need to reconstruct exactly what the agent did, when, and why. Logs are your professional liability protection.

These answers need to be clearly defined in your firm’s AI strategy and policy. Only 21% of firms actually have these critical pieces of guidance, but those that do are saving more time with AI and reaping more rewards.

Get intentional before you get burned

The productivity gains are seriously exciting: research suggests AI can save firms 21 hours per employee per month, and that number climbs when leadership invests in training. 

Agentic systems promise to push those numbers further. The firms that move thoughtfully will outpace the ones that move slowly, as well as the ones that move recklessly.

The firms that will thrive are the ones that treat AI governance as non-negotiable. That means defining accountability structures before you actually need them.