We've assessed your
AI governance readiness.

You’re at the beginning of the governance journey and the good news is that the first steps are more straightforward than they look. AI is being used in contracting workflows before the governance structure is ready for it, and closing that gap doesn’t require a major program. A few focused decisions, made in the right order, get you most of the way there.

• Start with your data foundations. Before any governance work begins, you need to know where your contract data actually lives. If it’s spread across multiple systems, consolidating it into one place is step one.
• Map what you have. Before anything else, identify which AI tools currently have access to your contract data. One conversation with IT gets you most of the way there.

• Name an owner. Designate one person in legal ops to hold AI governance, even as a partial responsibility. Naming someone changes the accountability dynamic immediately.
• Write a one-page policy. Cover three things: which tools are approved, what human review is required before acting on AI outputs, and who to call when something goes wrong. One page is enough to start.
• Use this report as your opening. Share it with your GC as the basis for a first governance conversation. The groundwork is simpler to lay than it looks.

You have the basics in place: some data structure, some policy awareness, some ownership. The gaps are in coverage and consistency. Governance exists in pockets but does not yet operate as a system. This is where most legal ops teams sit today, and it is the stage with the most to gain from targeted action.

• Get your data foundations in place first. Before connecting AI tools to your workflows, consolidate your contract data into one place. If contracts are spread across SharePoint, email, local drives, and multiple systems, AI has no reliable foundation to work from. Reconcile your data sources, align on a single repository, and make sure your legal positions and playbooks live there too.
• Audit your coverage gaps. Identify the two pillars where you scored lowest and define the single action in each that closes the biggest gap. Avoid trying to fix everything at once.
• Make escalation explicit. Define in writing what triggers a human review of an AI output, name the reviewer for each trigger type, and circulate it to every team that handles contracts.
• Map your downstream dependencies. Identify the two or three systems where contract data should flow but currently does not. Integration gaps are where AI value leaks most quietly.

Your governance posture is established and operating. You have data foundations, policy coverage, named ownership, and some audit capability. The gaps that remain are in depth and consistency; governance that works well in most situations but has edge cases. You are in the top quartile of enterprises at this stage.

• Move from reactive to active oversight. The next stage is not just reviewing AI outputs but proactively measuring AI tool performance against your playbook on a defined quarterly cadence.
• Tighten your audit trail. At your stage, leadership and regulators will increasingly ask not just whether a human was involved, but whether you can prove it. Confirm your logging captures reasoning, not only outputs.
• Test explainability. Ask a non-lawyer in your organization to read an AI recommendation and explain back to you why the AI made it — without your help. If they cannot, your explainability configuration needs work.
• Build the governance narrative. Your stage carries a story worth telling internally to the C-suite and externally to counterparties, auditors, and regulators.

Very few organizations reach this stage, and yours has. AI governance in contracting is operating here as a genuine function, not a checklist. Your contract data is structured and trusted, your policies are current and specific, ownership is clear, and you have an evidence trail that proves human oversight is real. You’ve built something most legal ops teams are still working toward. That’s worth recognizing.

• Extend the model. What you’ve built in legal ops is rare and replicable. Consider extending your governance framework to other high-risk AI workflows across the organization: procurement, finance, HR, and customer operations. You’re the best-placed team to lead that.
• Prioritize your highest-value AI use cases. Your foundation makes agentic AI (autonomous obligation enforcement, dynamic risk scoring, supplier behaviour prediction) both credible and auditable. Move beyond passive AI.
• Invest in governance as a standing discipline. Data drift is the biggest risk at your stage. Clean governance degrades quietly without active stewardship. Protect what you have built.
• Lead the internal conversation. Your C-suite and board are beginning to ask about AI governance. You are positioned to answer with evidence, not aspiration.