AI Governance & Policy Development
AI governance for operational AI systems
Organisations are deploying AI but lack clear policies on what's allowed, who approves what, how to handle incidents, and what data models can access. Legal and compliance teams block projects out of caution. Teams build AI tools without oversight. Risk is real but poorly managed.
AI Governance & Policy Development establishes practical guardrails - use case evaluation criteria, approval workflows, data access controls, incident response procedures, and escalation paths. This is operational policy that helps teams move forward safely, not academic frameworks that sit on shelves.
For organisations that need clear AI governance to enable deployment, not prevent it.
What you get
Operational AI governance framework with clear policies, approval workflows, and incident procedures. Our customers use this to accelerate AI deployment by giving teams clear boundaries and reducing legal/compliance friction.
- Timeline:
- 3-6 weeks
- Deliverable:
- AI governance policy documentation, use case evaluation framework, approval workflows, data access controls, incident response procedures, team training materials
How it works
Use Case Risk Assessment
Evaluate AI use cases by risk level, customer-facing vs internal, sensitive data vs general, high-stakes vs low-impact, to determine appropriate guardrails.
Approval Workflow Design
Define who approves what, which AI applications require legal review, security review, executive approval, and establish clear escalation paths.
Data Access Controls
Determine what data AI models can access, what requires special handling (PII, financial, health), and how to enforce boundaries technically and procedurally.
Incident Response Procedures
Establish what constitutes an AI incident (hallucinations affecting customers, data leakage, bias issues), who responds, and how to contain and communicate.
Policy Documentation & Training
Document policies clearly, train teams on what's allowed and what requires approval, create practical guidance trees for common scenarios.
What's required
Legal, compliance, and security stakeholder involvement. Clarity on organisational risk tolerance. Examples of use cases under consideration (actual, not theoretical). Commitment to practical guardrails, not perfection.
Good governance enables AI deployment by providing clear boundaries, not blocking everything out of caution.
"The governance framework gave our legal team confidence to say yes. We deployed three AI tools within six months of establishing it."
General Counsel, Healthcare Technology (UK)
Common questions about governance services
Common questions about governance services
What does the AI governance service include?
Practical governance built around each AI-supported workflow: ownership, inputs, human review points, approvals, escalation paths and how performance is tracked. The focus is the workflow and accountability, not policy documents that sit on a shelf.
Who is it for?
Operations, IT, risk, compliance and business leads who want clear control over how AI is used across customer service, sales, marketing, finance, ecommerce, product data and operational workflows.
How does it work around existing policies and systems?
We work with the data protection, security and audit requirements you already have. Governance is added at the workflow level so it fits with existing policies rather than replacing them.
Where should approval and human review sit?
Wherever the output touches customers, suppliers, pricing, money or anything not yet fully proven. Internal drafting and reporting need lighter controls. The aim is sensible review at the points that matter.
Does governance slow useful work down?
It should not. Governance is sized to the risk of the workflow. The point is to keep useful automation moving while making sure people stay in control of anything sensitive.
Where should a business start?
Usually with the workflows already using or about to use AI. We make ownership, inputs, review and outcomes explicit for those first, then extend the same pattern as more workflows come on board.
Related across WithPraxis
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