You Don't Need Perfect AI Governance. You Need to Start.

For many finance and business leaders, the honest answer to "what's your AI governance plan?" is some version of: we know we need one, and we haven't started.

If that's you, you're not alone. It's one of the most common situations I encounter, and it's rarely due to a lack of urgency or capability. It's often caused by how the task gets framed. AI governance is usually presented as a massive enterprise initiative: comprehensive policies, new committees, detailed frameworks, months of planning.

Framed that way, it's enough to keep the organization frozen in place before the work even begins.

I don't think AI governance has to work that way. In fact, the organizations making the most progress are often taking much smaller steps. They're not trying to solve every governance challenge at once. They're identifying the areas of greatest uncertainty and improving them over time.

That's how most management disciplines evolve. Financial controls didn't appear overnight. Finance leaders will remember that SOX programs in 2004 looked nothing like the mature capabilities they run today. Cybersecurity programs didn't begin with sophisticated incident response. Quality management didn't start with Six Sigma. Each evolved through a series of practical improvements, and I believe AI governance will follow the same path.

The good news: finance leaders have built governance incrementally before. This is familiar territory, not an alien discipline.

The important thing is to begin.

Two Practical Places to Start

If an executive asked me where to begin tomorrow morning, I'd recommend two things. Notably, neither requires new headcount or a board presentation. Just attention.

1. Understand Where AI Is Already Influencing Your Business

You can't govern what you can't see.

Many organizations have policies governing approved AI tools. Far fewer understand where AI is actually influencing business processes and decisions. Which teams rely on it? What information are employees entering into AI tools? Where is AI generating recommendations, analysis, or work products that others depend upon? Where are important business decisions already being influenced by AI?

Those questions often uncover both opportunities and risks that leadership didn't realize existed.

2. Ask Whether Your Existing Controls Still Work

This is the question I don't hear often enough.

Organizations spend years building controls around how work is performed. AI changes how work is performed. That naturally raises a question few are asking: are our existing controls still effective?

Consider a simple example. Many approval workflows were designed on the assumption that a person prepared the analysis being approved. Someone gathered the data, weighed the alternatives, and could explain the reasoning if asked. If AI now generates that analysis and the approver simply reviews the output, the control still exists, but the assumption underneath it has quietly changed. The reviewer may be validating a conclusion no one on the team actually reasoned through.

That's not an argument against using AI in the workflow. It's an argument for asking whether the control was designed for the way work happens now.

In some cases, the answer is yes, and existing controls hold up fine. In others, AI has introduced new assumptions, new failure points, or new decision pathways that weren't contemplated when those controls were designed. The objective isn't to redesign everything. It's to understand where today's controls remain fit for purpose and where they may need to

evolve.

Progress Over Perfection

Good governance rarely appears all at once. It matures over time. And every organization that eventually develops a strong AI governance capability starts in the same place: understanding how AI is influencing the business today, and taking practical steps to strengthen oversight where it matters most.

That may not feel like a complete governance program.

But it's exactly how one begins.

I'm curious where others are on this journey. What was the first practical step your organization took on AI governance? I'd welcome examples in the comments. The more we share what's actually working, the faster this discipline matures for all of us.

About Root Idea

Root Idea helps CFOs protect the business from AI decision risk. Root Idea works directly alongside finance teams to map AI influence, establishes decision governance controls that hold up to board scrutiny, and delivers training and change management to make governance stick. 

If your organization is scaling AI and governance hasn't kept pace, that's exactly the conversation we're built for. Learn more at rootidea.ai.