AI governance is becoming an economic activity, not merely a set of principles. Companies now need people who can inventory systems, assign responsibility, test behaviour, document decisions and translate technical evidence into something boards, regulators and customers can use.
The change is visible in the infrastructure around the field. NIST is revising the AI Risk Management Framework while developing evaluation resources such as TEVV-Athlon. The market is moving from asking whether AI should be governed to deciding how governance can be evidenced.
The profession sits between functions
The emerging practitioner is rarely only a lawyer or only an engineer. Useful governance requires product knowledge, risk judgement, security, data and enough technical literacy to understand what an evaluation does not prove.
That creates demand for new combinations of consulting, software, assurance and internal leadership.
Evaluation is becoming commercial infrastructure
Governance becomes operational when a company can test claims. Model evaluation, red teaming, monitoring, documentation and incident processes are therefore moving closer to procurement and deployment.
NIST's 2026 TEVV work is important because it treats evaluation as adaptable to real-world impact and outcomes, including agentic and multimodal systems.
Washington has a structural advantage
Standards, federal technology, security and procurement give Washington a natural role in this market, while New York and other enterprise centres contribute buyers and regulated industries.
The durable opportunity is not compliance theatre. It is the set of tools and professional services that help organisations make defensible decisions about systems they increasingly depend on.