A Practical AI
Governance Toolkit

Most AI governance frameworks are written by lawyers, for lawyers. This one is different. We built it for the people who actually have to implement AI — operations leaders, technology teams, and executives who need practical tools, not theoretical frameworks.

What's inside

• 01
  Key Terms

  Plain-English definitions of AI, LLMs, SLMs, model drift, hallucinations, and the other terms your board needs to understand.
• 02
  Governance Framework

  Core principles and an example governance structure with clearly defined roles — from board to operations — adaptable to your organisation's size.
• 03
  Internal AI Assessments

  How to conduct AI Risk Assessments, Impact Assessments, Ethics Assessments, and Data Protection Impact Assessments — with worked examples.
• 04
  AI Policy & Compliance

  Building an AI Use Policy that works, compliance obligations across key jurisdictions, and how to stay current as regulation evolves.
• 05
  On-Going Monitoring

  KPI tracking frameworks, post-deployment monitoring requirements, automated alerts, and mechanisms for audit and decommissioning.
• 06
  Internal & External Communication

  Transparency obligations, privacy notice requirements, and how to communicate AI use to employees, customers, and regulators.
• 07
  Board & Employee AI Training

  What regular AI training for directors and staff should cover, and how to build practical awareness programmes that actually change behaviour.
• 08
  AI Governance Checklist

  A comprehensive readiness checklist you can use to audit your current posture and track progress over time.

Ready-to-use templates

The toolkit includes four fill-in templates you can adapt and deploy immediately:

Built on nine core principles

Every recommendation in the toolkit traces back to these nine principles for responsible AI deployment: