Direct answer: choose an AI governance consulting firm by its ability to put six mechanisms into operation: executive mandate, living inventory, risk classification, proportionate controls, evidence-based assurance and continuous operations. A policy library does not prove governance. Before hiring, ask the firm to show how a real initiative enters the process, who decides, which evidence is required, how exceptions are handled and how the system keeps working after the engagement ends.
AI governance should be neither a layer that merely slows delivery nor a document that states generic principles. It must help an organization make consistent choices about buying, building, testing, launching, monitoring, changing and retiring AI systems. The right partner connects boards and executives with product, technology, data, security, legal, privacy, procurement, risk and operations. The outcome is organizational capability rather than permanent dependence on external specialists.
The MAKINAI Governance Delivery Proof-6
Compare proposals through six proofs: Mandate, Inventory, Classification, Controls, Assurance and Operations. For every proof, require an owner, workflow, artifact, time expectation and test using a real decision. NIST organizes AI risk management into Govern, Map, Measure and Manage. Proof-6 translates that logic into selecting a partner that must implement verifiable organizational behavior.
1. Mandate Proof: who can decide and accept risk?
The consultancy should help define scope, objectives, risk appetite, roles and forums. Ask how conflicts among speed, value, safety, privacy and experience will be resolved. Require a responsibility map separating executive accountability, use-case ownership, specialist review and approval. A committee should not review everything; it should decide exceptions and matters beyond delegated team authority.
- Evidence: charter; principles connected to strategy; RACI; delegated authority; decision calendar; escalation rule; decision record. Test: present a high-value case with incomplete evidence and ask the consultancy to demonstrate who decides, using which criteria and within what time.
2. Inventory Proof: does the organization know where AI exists?
Without inventory, governance covers only visible projects. The partner must discover internal models, APIs, embedded software features, automations, experiments, supplier applications and decentralized use. UK AI Management Essentials guidance describes an AI system record containing technical documentation, impact assessments, model analyses and data records. The inventory should identify owners, purpose, users, data, suppliers, integrations, lifecycle stage and last review.
Ask how new systems enter the record through procurement, security, architecture, data catalogs or development workflows. A one-time spreadsheet decays quickly. Require reconciliation, completeness criteria and a retirement process. The goal is not to count tools; it is to reveal where decisions and risks need management.
3. Classification Proof: do controls change with context and impact?
NIST says profiles and suggested actions should be contextualized; its Playbook is not a universal checklist. The consultancy should create a simple method for classifying impact, autonomy, data sensitivity, affected population, reversibility, scale, third-party dependency and consequence of error. Business teams must understand it, while specialist review remains available for difficult cases.
- Evidence: intake questions; risk criteria; tiers; boundary examples; prohibited or restricted-use handling; reclassification rule; mapping from tier to controls. Test: classify three different cases and verify that similar risks receive consistent treatment.
4. Controls Proof: does the requirement enter delivery?
Policies work only when they become criteria for design, procurement, development, evaluation, launch and change. For every tier, the firm should map controls for purpose, permitted data, evaluation, human review, security, transparency, access, logging, contestability, suppliers and monitoring. ISO/IEC 42001 describes a management system that establishes policies, objectives and processes and continually improves; the proposal must show how that structure enters existing business processes.
Avoid creating a second bureaucracy where security, privacy, architecture, quality and procurement already have mature workflows. The partner should integrate requirements, remove duplication and identify what is specifically new for AI. Ask who implements every control, who tests it, where evidence lives and when an exception expires.
5. Assurance Proof: how does the organization know controls work?
Assurance is neither a team promise nor a certification used as a shortcut. It is sufficient evidence for a decision, proportionate to risk. GAO’s framework organizes accountability around governance, data, performance and monitoring and provides questions for managers, auditors and assessors. The consultancy should create a matrix connecting claim, risk, control, test, result, limit and the person accepting residual risk.
Request evidence examples: evaluation datasets and reports, threat models, access tests, data analyses, experience reviews, logs, simulated incidents and monitoring. Verify independence: for higher-risk cases, the builder should not be the only evaluator. The partner must explain the distinction among self-assessment, internal review, audit and certification without promising automatic compliance.
6. Operations Proof: does the system stay alive after the project?
Governance must respond to changes in models, suppliers, data, purpose, markets and observed behavior. Require reassessment triggers, monitoring, incident management, reporting channels, expiring exceptions and periodic portfolio review. Metrics should expose decision time, inventory coverage, overdue controls, incidents, residual risk and the ability to retire systems.
The consultancy should design an operating model appropriate to the organization’s size and maturity. Smaller organizations may combine roles; larger ones may require a central hub and distributed owners. Both need trained people, budget, proportionate tooling, accessible documentation and a transfer plan.
How to score firms in 24 points
Assign zero to four points to every proof: zero means absent; one, a promise; two, a documented method; three, pilot evidence; four, reproducible operations. Require at least three in Mandate, Inventory, Assurance and Operations. Then run one real use case from registration through decision. Do not let regulatory experience compensate for inability to work with product, engineering and operations. Do not let technical depth replace organizational accountability either.
A recommended first 90-day scope
Begin with a short diagnostic and a real portfolio sample. Define mandate and taxonomy, create a minimum inventory, classify priority cases and implement controls in two or three initiatives. Test the decision forum, produce evidence, simulate an exception and incident, adjust the workflow and enable internal owners. The period should finish with an operating capability and prioritized backlog—not dozens of policies without adoption.
- Minimum outputs: charter; inventory and dictionary; classification matrix; control catalog; intake and decision workflow; evidence model; risk and exception register; incident runbook; indicators; enablement material; transfer and evolution plan.
Red flags and next step
- The proposal starts with policies but no inventory; promises universal compliance; copies one framework without context; every initiative goes to the same committee; delivery and procurement remain disconnected; the consultancy independently assures its own implementation; certification is treated as sufficient evidence; operating metrics are absent; tooling comes before workflow; internal owners appear only at closeout.
Use Proof-6 to compare bidders and structure the engagement with https://makinai.co/insights/en/how-to-write-rfp-ai-services. Compare general capability using https://makinai.co/insights/en/how-to-choose-ai-implementation-company-brazil-scorecard and decide the delivery model with https://makinai.co/insights/en/in-house-ai-team-or-ai-consulting-firm. To connect governance, portfolio and execution, visit https://makinai.co/services/en/ai-strategy-transformation-consulting.