Governance thinking
for enterprise leaders.

Enterprise AI adoption is accelerating. Legal teams use AI for contract analysis. Compliance teams use it for regulatory research. Finance teams use it for risk assessment. Procurement teams use it for supplier evaluation. Each output influences or becomes a business decision.

The role of the General Counsel has expanded beyond legal advisory into enterprise governance leadership. Boards increasingly expect the GC to answer not just "what is our legal position?"

Every vendor relationship begins with a contract. The contract specifies governance requirements: compliance standards, data handling obligations, service levels, reporting commitments, insurance minimums, certification requirements.

Every regulated enterprise has compliance frameworks. Policies are written. Controls are documented. Risk registers are maintained. Audit programmes run on schedule. And yet, the decisions that create the most operational risk happen inside business workflows where none of those controls are enforced.

The conversation about AI governance in regulated enterprises has been dominated by principles. Responsible AI frameworks. Ethics boards. Acceptable use policies published on intranets. Internal guidance documents circulated by email.

Every regulated enterprise has compliance. Policies are written. Controls are documented. Audits are conducted. Reports are produced. The question is whether any of this actually prevents a non-compliant decision from being made.

Enterprise governance is typically organised by function: legal governance, compliance governance, financial governance, procurement governance, risk governance. Each function builds its own frameworks, manages its own tools and runs its own processes.