Our AI governance consulting services help organisations use AI responsibly and at scale: clear policies, risk controls, ownership and oversight that align with the EU AI Act, NIST AI RMF, ISO/IEC 42001 and data-protection law, built to fit how your teams actually work rather than slow them down.
AI governance is the set of policies, roles, processes and controls that decide how AI is chosen, built, used and monitored in your organisation. Done badly, it becomes paperwork that slows every project. Done well, it gives teams clear rules, speeds up approvals and lets leadership scale AI knowing the risks are understood and managed. That is the kind of AI governance our consultants put in place.
Start with a governance health check or build a complete responsible AI programme. Each service produces practical, written deliverables your legal, risk, technology and business teams can use straight away.
AI governance framework
Responsible AI principles
AI lifecycle controls
Implementation roadmap
We design an AI governance framework sized to your organisation: guiding principles, scope, roles, decision rights, risk tiers and the lifecycle controls every AI system passes through, from idea to retirement.
AI acceptable-use policy
AI vendor and tool policy
AI data-use rules
AI incident procedure
Clear, readable AI policies people will actually follow: acceptable use of public AI tools, approved models and vendors, data that may and may not be used with AI, human review requirements and incident reporting.
AI risk and impact assessments
Risk classification tiers
AI risk register
Control mapping
We assess AI systems for risks to people, the business and compliance, covering bias, privacy, security, accuracy, safety and third-party risk, classify them by severity and define proportionate controls and owners.
EU AI Act readiness assessment
Obligation and gap analysis
Technical documentation support
DPIA and privacy alignment
We help you understand which AI rules apply to you, including the EU AI Act, GDPR and sector regulations, and translate them into concrete technical and organisational requirements, working alongside your legal counsel.
GenAI use and data rules
LLM guardrail standards
Output evaluation criteria
AI agent oversight controls
Governance built for LLMs and generative AI: rules for prompts and data, guardrails against hallucinations, harmful content and data leakage, evaluation standards, human review of outputs and controls for AI agents that can take actions.
AI system and model inventory
Shadow AI discovery
Model cards and documentation
Third-party AI vendor reviews
You cannot govern AI you cannot see. We build an inventory of AI systems, models and vendors in use, including shadow AI, and set consistent governance across in-house models, third-party APIs and AI features inside SaaS tools.
Bias and fairness audits
Explainability methods
Impact on affected groups
Mitigation plans
We test AI systems for unfair outcomes across groups, recommend mitigations, and put explainability in place so decisions affecting customers or employees, such as credit, hiring or pricing, can be understood and challenged.
AI governance committee charter
Roles and RACI
AI review and approval workflow
Staff AI literacy training
We help you set up the people side of AI governance: an AI governance committee and charter, decision rights, a lightweight review and approval process, and training so every team knows its responsibilities.
AI monitoring requirements
Audit logs and evidence
Periodic model reviews
Audit preparation support
Governance continues after launch. We define what to monitor, including accuracy, drift, bias, incidents and usage, set up dashboards and logs, and organise the evidence auditors and regulators will ask for.
Book a governance health check. We will review how AI is used across your organisation today and give you a prioritised list of gaps and quick wins.
Every effective AI governance framework, whatever the size of the organisation, is built on the same six components. We tailor each one to your risk profile and ways of working.
What AI should and should not do in your organisation, written as clear rules people can apply.
Named owners for each AI system, a governance committee and clear decision rights.
A living register of AI systems, models, vendors, purposes and data used.
Risk tiers that decide how much review and control each AI use case needs.
Checks at design, build, testing, launch and change, proportionate to risk.
Ongoing oversight, incident handling and records of every significant decision.
AI rules are multiplying and overlapping. We map the ones relevant to your business into a single set of controls, so you are not running a separate programme for each. Legal interpretation and sign-off remain with your counsel.
Risk-based obligations for providers and deployers of AI used in the EU, including prohibited practices, high-risk system requirements, transparency duties and AI literacy. We help you classify your systems and prepare.
The Govern, Map, Measure and Manage functions give a practical, widely adopted structure for identifying and managing AI risk.
The international standard for AI management systems. We help structure your governance so it can map to ISO/IEC 42001 if you pursue certification.
Guidance on AI risk management that complements ISO/IEC 42001 and existing enterprise risk processes.
Lawful basis, data minimisation, DPIAs and rights around automated decision-making when AI processes personal data.
HIPAA, PCI DSS, SOC 2 and financial-sector model risk expectations, applied to AI systems that touch regulated data or decisions.
State and local rules such as the Colorado AI Act and New York City's requirements for automated hiring tools, plus sector guidance.
Internationally recognised principles for trustworthy AI that many national policies build on, useful as a baseline for your own AI principles.
Many AI governance frameworks look good on paper and fail in practice because they ignore how AI is really built and used. Our governance consultants work alongside engineers who build AI systems every day, so the controls we recommend are technically realistic and fit your delivery process.
Choose the level of support that matches your AI maturity and regulatory exposure.
A short review of current AI use, policies and risks that ends with a gap report and prioritised quick wins.
Design and roll out a complete AI governance framework: principles, policies, roles, risk tiers, lifecycle controls and templates.
Inventory and classify your AI systems, map obligations by role and create an action plan with your legal team.
A fractional AI governance lead who supports your committee, reviews new use cases and keeps the framework current as rules change.
Governance needs differ sharply by sector: credit decisions in finance, clinical support in healthcare, hiring tools in HR. We tailor risk tiers and controls to the rules and expectations of your industry. Explore the industries we work in:
Good governance is supported by the right tooling for inventory, monitoring, fairness testing, explainability, guardrails and data protection. We recommend and configure tools that suit your stack and budget.
Azure AI Content Safety
Amazon SageMaker Clarify
Amazon Bedrock Guardrails
MLflow Model Registry
NVIDIA NeMo Guardrails
Our AI governance process is designed to deliver usable controls quickly, then mature them over time, without stopping the AI work already under way.
We map AI systems, tools, vendors and shadow AI across the organisation, and review existing policies and risk processes.
We agree principles, risk tiers, roles and decision rights, and map applicable regulations and standards to controls.
We write clear policies, templates and checklists that teams can follow without specialist help.
We build reviews and approvals into your delivery, procurement and change processes and tools.
We train leaders, builders and users on their responsibilities, and pilot the process on real use cases.
We review how governance performs, track new regulations and update the framework as your AI use grows.
Tell us how your organisation uses AI today and what worries you most, whether regulation, data, reputation or shadow AI. We will suggest the most useful first step.
Discuss your AI use, regulatory exposure and current controls.
Scope, deliverables, timeline and cost for the right engagement.
Clear policies, controls and ownership your teams can act on.
AI governance is the framework of policies, roles, processes and technical controls that guides how an organisation selects, builds, uses and monitors artificial intelligence. Its purpose is to make sure AI is effective, safe, fair, secure, compliant with the law and accountable, so that someone is responsible for each system and its decisions can be explained.
Without governance, AI adoption tends to be inconsistent and risky: staff paste sensitive data into public tools, models make unfair or wrong decisions nobody notices, and new regulations such as the EU AI Act catch the business unprepared. Good AI governance reduces those risks, builds trust with customers and regulators, and actually speeds up adoption because teams know the rules and approvals are predictable.
An AI governance consulting firm helps you set up and run AI governance: assessing current AI use and risks, designing a framework and policies, mapping regulations and standards to controls, setting up committees and approval processes, training staff and preparing for audits. Our AI governance consulting services also cover the technical side, such as logging, evaluation and monitoring, because we build AI systems too.
Start by inventorying the AI you already use. Then agree principles and risk tiers, assign owners and a governance committee, write policies for use, data and vendors, define controls for each stage of the AI lifecycle proportionate to risk, embed reviews into existing processes, train people, and monitor and update the framework regularly. Aligning with the NIST AI RMF or ISO/IEC 42001 gives a proven structure to follow.
Data governance manages the quality, ownership, access and privacy of data. AI governance covers the models and systems that use that data: their purpose, risks, fairness, transparency, human oversight and behaviour in production. The two overlap heavily, since poor data governance undermines AI, so we design them to work together. See also our data analytics services.
It can apply even to companies outside the EU if they provide AI systems used in the EU or whose outputs are used there. Obligations depend on your role (provider or deployer) and the risk level of each system, and they are phasing in over several years. We help you inventory and classify your AI systems and map the obligations; final legal interpretation should come from your counsel.
ISO/IEC 42001 is the international standard for an AI management system (AIMS). It sets requirements for policies, roles, risk assessment, lifecycle controls and continual improvement for organisations that develop or use AI, and it can be certified by accredited bodies. We help structure your governance to align with it; certification itself is carried out by an independent certification body.
An AI governance committee brings together leaders from technology, legal, risk, data, security and the business to set AI policy, approve higher-risk use cases, resolve trade-offs, oversee incidents and track the organisation's AI risk. We help define its charter, membership, decision rights and a lightweight review process so it enables projects rather than stalling them.
Cost depends on the size of the organisation, how many AI systems are in scope, regulatory exposure and the depth of support needed. A governance health check or EU AI Act readiness sprint costs far less than a full framework build with training and ongoing advisory. We provide a fixed quote once the scope is agreed.
No. We are governance and technology consultants: we design frameworks, policies, risk processes and technical controls and help you align with regulations and standards. Legal interpretation of laws and final compliance sign-off should come from your legal counsel, and certification from accredited auditors. We work closely with both.
CodeBase Coders offers AI governance consulting services from health checks and EU AI Act readiness to complete responsible AI frameworks, generative AI and agent governance, bias audits and audit preparation, backed by engineers who can implement the technical controls. For broader AI strategy see our AI consulting services. Contact us to book a discovery call.
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