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MHCAI — Mindacks Human-Centred AI InstituteMHCAI — Mindacks Human-Centred AI Institute
AI Governance · Policy Design

AI Policy & Responsible UsePolicies that enable. Governance that protects.

Most AI usage policies are written by legal teams and read by no one. The best AI policies are written by people who understand both the business and the risk — and designed to guide behaviour, not just protect the organisation. This programme teaches leaders and governance professionals how to design AI policies that actually work.

Virtual · In-Person
8 Hours
Governance Workshop
Governance professional reviewing AI policy documentation in a professional office setting
What You'll Gain

Outcomes that change
how you work.

  • Design a practical, readable AI usage policy for your organisation, team, or function
  • Identify the key risk areas your AI policy must address: data, accuracy, bias, and accountability
  • Build responsible use guidelines that employees will actually follow
  • Create a monitoring and enforcement framework that is proportionate and effective
  • Navigate the data protection implications of AI tool use in a workplace context
  • Design clear approval processes for AI tools and use cases
  • Build a communication and training plan that brings your policy to life
  • Update and iterate your policy as AI capabilities and regulations evolve
Who This Is For

Built for specific people.

  • HR & People Leaders

    HR directors and managers responsible for workforce policy who need to extend existing technology use policies to cover AI specifically and practically.

  • Legal & Compliance Teams

    Legal, compliance, and risk professionals who need to understand the practical dimensions of AI policy — not just the legal ones — to write policies that work.

  • IT & Information Security

    Technology and security leaders responsible for data protection, acceptable use, and vendor management who need to bring AI tools into existing governance frameworks.

  • Operations & Team Leaders

    Managers and operations leaders who want to build clear, practical AI guidelines for their specific teams and workflows.

Problems This Solves

Real challenges. Real solutions.

  • Employees are using AI tools without any guidance

    In most organisations, employees are already using consumer AI tools at work. Without policy, data protection, accuracy, and confidentiality risks are unmanaged.

  • Existing AI policies are too restrictive or too permissive

    Policies that ban AI entirely drive it underground. Policies that are too permissive create unacceptable risk. The right policy calibrates guidance to risk and context.

  • Policies are written but never followed

    Policy without training, communication, and monitoring is just documentation. This programme teaches how to design policies that change actual behaviour.

  • Leaders don't know which AI risks to prioritise in policy

    The AI risk landscape is vast. This programme identifies the highest-priority risks to address in policy — so governance effort is focused where it matters most.

Programme Overview

AI policy that works in practice, not just on paper.

The MHCAI AI Policy Framework provides a structured approach to policy design that balances risk management with operational reality. Good AI policy enables the use cases that create value while protecting against the risks that create harm — and it is written in language that employees understand and leaders can enforce.

Risk-Calibrated

Policy Design

Behaviour-Change

Focus

8h

Workshop

Duration8 Hours
DeliveryVirtual · In-Person
FormatGovernance Workshop
Programme Modules

What the programme covers.

01

The AI Policy Landscape

  • Why standard technology acceptable use policies fail to address AI-specific risks
  • The five categories of AI risk that every policy must address: data, accuracy, bias, accountability, transparency
  • Regulatory context: what GDPR, EU AI Act, and ISO 42001 require of organisational AI policy
  • Policy design principles: enabling value while managing risk proportionately
02

Designing Your AI Usage Policy

  • Scope definition: which tools, users, and use cases does the policy cover?
  • Permitted use categories and the approval process for new AI use cases
  • Data classification for AI inputs: what can — and cannot — be put into AI tools
  • Accuracy, verification, and human review requirements for AI-generated outputs
03

Responsible Use Guidelines

  • Writing responsible use guidelines that are practical, specific, and memorable
  • Role-specific guidance: what responsible AI use looks like for different functions
  • AI transparency requirements: when employees must disclose AI use
  • Prohibited uses: the absolute limits that protect the organisation and its people
04

Implementation, Communication, and Monitoring

  • Building the communication and training plan that makes the policy real
  • Monitoring AI use: proportionate oversight without creating surveillance culture
  • Incident response: what happens when the policy is breached or AI causes harm
  • Policy review cadence: how to keep AI policy current as the technology evolves
Practical Use Cases

See it applied in the real world.

HR Director at a Professional Services Firm

Partners are using AI for client deliverables without disclosure. There is no policy. A client has raised concerns about confidential information being shared with a consumer AI tool. The firm needs a policy urgently.

Uses the workshop framework to design a comprehensive AI usage policy in 3 days. Policy covers data classification, prohibited inputs (client data), disclosure requirements, and approval processes. Published within 2 weeks. Incident rate drops to zero.

Head of IT Security

The CISO has asked for an AI tools governance framework that prevents data leakage without blanket-blocking tools that the business relies on for productivity.

Designs a risk-tiered AI governance framework. Tools are categorised as approved, conditionally approved, or prohibited based on data handling practices and business context. Business productivity maintained; data leakage risk addressed. Framework adopted by the CISO.

Operations Director at a Healthcare Provider

Clinical and administrative staff are using AI tools informally. The organisation needs a policy that addresses the clinical safety and GDPR dimensions specific to healthcare AI use.

Designs a healthcare-specific AI policy with tiered guidance: different requirements for clinical AI use vs. administrative AI use. Policy integrated with existing CQC compliance framework. Staff training completed within one month of publication.

Live Demos & Hands-On Labs

Learn by doing, not watching.

Lab 01

AI Risk Assessment Workshop

Map the AI tools currently in use in your organisation or team. Assess each against the five risk categories — data, accuracy, bias, accountability, transparency — and identify your priority policy gaps.

Lab 02

Policy Drafting Sprint

Use the MHCAI policy template to draft the core sections of your AI usage policy — scope, permitted use, data classification, responsible use guidelines, and prohibited uses — in a single session.

Lab 03

Responsible Use Guidelines Workshop

Write role-specific responsible use guidance for 3 functions in your organisation. Apply the test of specificity: would an employee know from this guidance what to do and what to avoid?

Lab 04

Communication and Training Plan

Design the communication and training plan for your AI policy launch. Map audiences, messages, channels, and timing — with a measurement framework to evaluate policy adoption.

Tools & Platforms

You will work with the real tools.

ChatGPT
Claude
Copilot
NotebookLM
Why MHCAI · Mindacks

Different by design.

Practical, Not Theoretical

Every session starts with a real business problem. Concepts are introduced only when they serve a specific outcome you need to deliver.

Real Use Case Focus

We teach through scenarios drawn from real professional contexts — Finance, HR, Marketing, Leadership — so learning transfers immediately.

Designed for Simplicity

Complexity is hidden. Clarity is foregrounded. You get exactly what you need to act — without being overwhelmed by what you don't.

Tool Adoption Science

Our methodology is built on behavioural science and habit formation principles — so you actually use what you learn, not just remember it.

Neuroscience Principles

Learning design based on how brains retain and apply information. Spaced repetition, active retrieval, and contextual practice built in.

ISO 42001 Certified

MHCAI is the only AI learning institute that combines ISO 42001 certification, role-specific academies, and a human-centred methodology.

Ready to Start?

Build an AI policy your organisation will actually follow.

Available as an open workshop for governance professionals or as an in-house session for leadership and compliance teams. Contact us to design the right format for your organisation.