Governance & risks of generative AI in the enterprise
Control the risks of generative AI with a pragmatic governance framework: authorized uses, protected data, systematic validation.
Book a 30-min callRéponse courte
AI governance sets a simple framework to regulate the use of generative AI: a policy of authorized uses, validation roles, data protection and logs. A pragmatic framework in 3 documents that secures adoption without slowing it down.
In 30 seconds
AI governance sets usage rules, validation roles, data management and logs to reduce risks (leaks, bias, false answers) and increase adoption safely. It's not a 200-page document — it's a simple framework that says what is allowed, what isn't, and who validates what.
Typical problems
The signs that this solution is right for you.
Unregulated use of ChatGPT
Your teams already use ChatGPT — but without rules. Confidential data ends up in prompts, false answers are taken at face value.
Legal and regulatory risks
GDPR, intellectual property, liability in case of error — the legal risks of generative AI are real and often ignored.
Hallucinations and misinformation
LLMs invent facts convincingly. Without control, business decisions get made on false information.
Resistance to change
Without a clear framework, teams hesitate to use AI (fear of doing it wrong) or use it carelessly (no rules). Governance unlocks adoption.
Our approach
A proven method, in clear steps.
Diagnosis of current uses
We map how AI is used today in your organization: which tools, which use cases, which identified risks.
Definition of the usage policy
We define what is allowed, what requires validation and what is forbidden. In plain terms, not legal jargon.
Setting up roles and controls
Who validates what? Who is responsible in case of a problem? We define the roles (AI lead, validator, user) and the control processes.
Team awareness
We train teams on the rules and best practices. Not theory: concrete examples of what to do and what not to do.
What you get
- AI usage policy (ready-to-distribute document)
- Roles and responsibilities matrix (RACI)
- Compliance checklist (GDPR, data, security)
- Best practices guide for teams
- Risk assessment template per use case
- Awareness plan
The 4 major risks of generative AI in the enterprise
Data leaks (confidential data sent to external APIs), hallucinations (false answers presented as true), bias (discrimination in results), and dependency (vendor lock-in). Each of these risks has simple solutions — provided you address them before deployment, not after.
A simple framework, not bureaucracy
Our approach to AI governance comes down to 3 documents: (1) a usage policy (1 page, what's OK / not OK), (2) a RACI matrix (who does what), (3) a checklist per use case (data, risks, validation). That's enough for 90% of companies. The remaining 10% need a more formal framework — and we support them too.
Related offers
The Digit-AI services that complement this solution.
Related solutions
Enterprise AI maturity assessment
Assess your AI maturity and get a prioritized roadmap with a first actionable quick win — in 10 business days.
LLMOps: industrializing generative AI in production
Move from POC to production with proven LLMOps practices: testing, security, monitoring and continuous improvement.
Articles on this topic
Dig deeper with our detailed analyses.
Claude Mythos Preview: Anthropic builds an AI too powerful to be made public
Anthropic unveils Claude Mythos Preview, a model able to detect previously unknown security flaws. But it is reserved for a club of 40 tech giants. What this means for SMB cybersecurity and unequal access to the best technologies.
Read the article
Risks and governance of office AI: what every decision-maker should know
Misinformation, data leakage, bias, vendor dependency: the risks of AI in office work are real but manageable. Discover the recommended governance framework, usage policies and best practices to deploy Copilot and Gemini securely.
Read the article
The AI Act comes into force: what changes for businesses
The European AI regulation (AI Act) comes into force. Which systems are affected, which obligations apply and how to prepare right now.
Read the article