Evidence-led AI governance, workflow design and accountable human review for high-stakes business decisions. The approach is built on four stated principles: a human stays in the loop at every decision that reaches a client or candidate, with a human approval step in every commercial tier and no exceptions for scale or speed; evidence is prioritised over confidence, with systems built to challenge their own outputs through structural independent review; client and candidate data stays with the client, with systems working only from data the client already holds and has consent to use, and nothing scraped from the open web; and compliance is treated as structural, with regulatory and framework requirements built into the system rather than bolted on as a checklist at the end. Accountability rests with a named human reviewer, and systems are isolated by design.
An AI governance consultant helps an organization manage the risk and compliance obligations of building or using AI systems - work that can include technical audits (bias testing, model documentation, explainability reviews), drafting internal AI use policies, staff training, and building the approval workflows needed before an AI system goes into production.
They overlap but aren't identical. AI ethics consulting tends to focus on values-driven questions - fairness, transparency, societal impact - while AI governance is the broader operational discipline of turning those principles (plus legal requirements) into actual accountability structures, documentation, and processes an organization follows.
Possibly, depending on your industry and jurisdiction. The EU AI Act applies specifically to AI systems used in or affecting the EU market, but many US states and industries (particularly hiring, credit, and healthcare) have their own AI-specific rules. Voluntary frameworks like the NIST AI Risk Management Framework are also increasingly used by organizations with no direct EU exposure, simply as a defensible internal standard.
A general AI consultant typically helps build or deploy an AI system. An AI governance consultant evaluates and documents the risk, compliance, and accountability structure around a system that's already being built or deployed - the two roles can come from the same firm, but they're different scopes of work and worth clarifying separately before engaging.
It varies by scope - a one-time technical audit or policy review is typically a fixed-price deliverable, while ongoing governance (continued monitoring, periodic review as regulations or models change) is usually structured as a retainer. Check individual listings for specifics on engagement model and typical project size.