IntuitionLabs
AI Technology Vision

AI Policy & Governance

Clear policies, data classification frameworks, and compliance guidelines that let your team use AI confidently while protecting sensitive data and meeting regulatory requirements.

Why Your Company Needs an AI Policy

Without clear AI governance, employees will use AI tools on their own terms -- often sharing confidential data, skipping review processes, or creating compliance risks they do not even recognize. A recent survey found that 68% of employees using AI at work have never disclosed it to their employer.
  • Confidential clinical data entered into consumer AI tools
  • AI-generated regulatory content submitted without human review
  • Intellectual property shared with AI platforms that train on user inputs
  • No audit trail for AI-assisted decisions in GxP environments
  • Inconsistent practices across departments creating compliance gaps
Adrien Laurent
Adrien Laurent
Founder & Principal Engineer
25+ years enterprise software. Developed AI policy frameworks for regulated industries.

The Risk of No Policy

68% of employees using AI at work have never disclosed it to their employer. In regulated industries, this creates serious risks -- from confidential data in consumer AI tools to AI-generated content in submissions with no human review.

Policies That Enable, Not Block

We develop policies that enable AI adoption rather than restrict it. The goal is clear guardrails that let employees use AI confidently, knowing exactly what they can and cannot do with different types of data and different AI tools.

Built for Regulated Industries

Our framework addresses FDA 21 CFR Part 11, HIPAA, EU AI Act, and GxP requirements -- mapped to specific AI tools and use cases relevant to pharma and biotech operations.

Data Classification Framework

A 4-tier framework that maps directly to AI tool permissions, making it simple for employees to know what data can be used where.

Tier 1: Public

Information that is publicly available or intended for public disclosure.

AI Permission:

Any approved AI tool

Examples:

  • Published research papers
  • Press releases
  • Public website content
  • Industry news

Tier 2: Confidential

Internal business information not intended for public disclosure.

AI Permission:

Enterprise AI tools only

Examples:

  • Internal presentations
  • Meeting notes
  • Draft communications
  • General business plans

Tier 3: Restricted

Sensitive business information with limited access.

AI Permission:

Approved tools with restrictions

Examples:

  • Financial data
  • Competitive intelligence
  • Unpublished research data
  • Employee information

Tier 4: Sensitive / Regulated

Data subject to regulatory requirements or legal restrictions.

AI Permission:

No AI tool usage

Examples:

  • Patient / PHI data
  • GxP records
  • Regulatory submissions
  • Clinical trial data

Policy Deliverables

Complete, ready-to-implement policy documents tailored to your organization. Not recommendations -- actual documents you can approve and deploy.

Master AI Usage Policy

Comprehensive policy document covering approved tools, acceptable use, data handling requirements, review processes, and enforcement. Ready for your document management system.

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Data Classification Matrix

Complete mapping of your data types to the 4-tier classification framework with clear AI tool permissions for each tier. Includes decision tree for edge cases.

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Employee Guidelines

Plain-language quick reference guide for employees covering dos and do-nots, approved tools, data handling rules, and escalation procedures. Designed to be printed or posted on intranet.

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Department-Specific Rules

Customized guidelines for each department (Clinical, Regulatory, Commercial, Finance, etc.) with role-specific examples and approved use cases relevant to their workflows.

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Training Materials

Slide deck, handouts, and assessment quiz for rolling out the AI policy to your organization. Can be delivered by your team or by IntuitionLabs trainers.

Workshop options

Review Framework

Quarterly review schedule, update process, incident reporting template, and criteria for triggering policy updates. Keeps your policy current as AI evolves.

Ongoing support

Compliance Considerations

Our AI policy framework addresses the regulatory requirements most relevant to pharmaceutical and biotech companies.

21 CFR Part 11
Ensuring AI-assisted processes maintain electronic record integrity, audit trails, and electronic signature requirements. Defines when AI-generated content requires formal validation.
HIPAA
Strict prohibitions on entering protected health information (PHI) into AI tools. Guidelines for de-identification, business associate agreements with AI vendors, and breach notification protocols.
EU AI Act
Classification of AI systems by risk level, transparency requirements for AI-generated content, and documentation obligations for high-risk AI applications in healthcare and life sciences.

Frequently Asked Questions

AI tools introduce unique risks that traditional IT policies do not address: employees sharing confidential data with AI chatbots, AI-generated content being used in regulatory submissions without review, intellectual property concerns with AI training data, and liability for AI-generated errors. A dedicated AI policy provides clear, specific guidance for these new scenarios.
A comprehensive AI policy framework typically takes 4-6 weeks from kickoff to final approved documents. This includes stakeholder interviews, drafting, legal review, and revisions. If you need an interim policy quickly, we can deliver a baseline policy within 2 weeks that covers the critical guardrails while the full framework is developed.
The policy framework is tool-agnostic and covers all categories of AI tools: general-purpose chatbots (ChatGPT, Claude, Gemini), productivity copilots (Microsoft Copilot, GitHub Copilot), research tools (Deep Research, Perplexity), and any future tools your team may adopt. We also include guidelines for evaluating new AI tools as they emerge.
We implement a 4-tier data classification framework (Public, Confidential, Restricted, Sensitive/Regulated) and map it to specific AI tool permissions. For example, Public data can be used with any approved AI tool, while Sensitive/Regulated data (patient data, GxP records) cannot be entered into any AI tool. Each tier has clear examples relevant to your organization.
Our policy framework addresses FDA 21 CFR Part 11 (electronic records), HIPAA (patient data), EU AI Act (AI system classification and requirements), ICH guidelines, and GxP requirements. We also incorporate emerging FDA guidance on AI/ML in drug development and manufacturing.
Yes. Policy development includes training materials (quick reference guides, decision trees, examples) and we can deliver policy training as a standalone session or integrate it into our AI workshops. We recommend combining policy training with hands-on tool training so employees understand both the rules and how to work within them effectively.
We recommend quarterly reviews of your AI policy given how rapidly the AI landscape is evolving. Our policy framework includes a review schedule, update process, and criteria for triggering out-of-cycle updates (such as new regulatory guidance, new tool deployments, or significant AI incidents). Our retainer service can handle ongoing policy maintenance.
We deliver complete, ready-to-implement policy documents -- not recommendations. This includes the master AI policy, data classification matrix, employee guidelines, department-specific rules, training materials, and a review framework. All documents are formatted for your internal document management system and ready for approval workflows.
Ready to Govern AI Responsibly?
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Ready to Govern AI Responsibly?

Book a call to discuss your AI policy needs. We will help you create clear, practical governance that enables adoption while protecting your organization.

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