Building Your Company’s AI Governance Framework to Reduce Risk
As organizations accelerate their use of AI, the legal department plays a critical role in guiding how – and how far – that adoption goes. Move too slowly, and the business risks falling behind competitors or missing valuable efficiencies. Move too quickly, and it may take on regulatory, reputational, or operational risks it isn’t prepared to manage.
Legal’s responsibility isn’t to slow innovation. It’s to help the business strike the right balance, enabling smart, strategic AI adoption while putting the guardrails in place to protect the organization and its people.
The Importance of an AI Governance Framework
Forward-looking legal professionals can help their organizations avoid potentially serious issues by establishing an AI governance framework, which can create a safe environment for innovation while addressing compliance, data security, and ethical use.
This report outlines key steps for building one for your company, covering everything from device management to mitigating risk, and providing trusted guidance for drafting AI usage policies for the modern workplace.
Current State of AI Use at Work
AI has become a powerful tool for many in the workplace. According to a January 2026 report from Gallup, the percentage of U.S. employees who report using AI at least a few times a year jumped from 27% in late 2024 to 46% in Q4 2025.
However, many employees are using AI at work without the benefit of clear standards, which can result in serious harm not only for these employees but also for their organizations.
Enterprise AI Adoption and Managing Risk
Enterprise AI adoption has numerous notable benefits, including related to efficiency and productivity. However, organizations must develop ways to reduce related risks, including those related to privacy, inaccuracies, intellectual property, and bias.
The stakes are particularly high when AI systems generate inaccurate or “hallucinated” outputs, especially in contexts such as medical guidance or emergency response, where errors can pose significant safety risks.
Five Steps to Building an AI Governance Framework
Organizations, in partnership with their in-house counsel or other legal operations professionals, must create a robust AI governance framework that goes beyond a traditional checklist of compliance tasks. Here are five steps to consider:
Step 1: Understand Evolving AI Regulation and Policy
As policymakers establish guardrails for AI, the EU and U.S. are taking notably different paths. The EU has enacted the EU AI Act, while the U.S. lacks a comparable federal law, leading to a complex regulatory landscape.
Step 2: Review and Update Organizational Policies
Governance starts with reviewing and supplementing existing rules. Key areas to review include:
- Employee Code of Conduct: Define your organization’s stance on AI as a management tool.
- Device Management Policy: Regulate AI access on company vs. personal devices.
- Anti-Discrimination and HR Policies: Ensure compliance with EEO laws in AI usage for recruitment.
Step 3: Draft a Clear AI Usage Policy
If you allow AI usage, you must outline specific permissions and requirements. This includes defining what constitutes acceptable versus prohibited AI use, mandating human review of AI outputs, and addressing transparency and disclosures.
Step 4: Mitigate Risk and Confirm Compliance
To mitigate risks such as bias and inaccuracies, consider forming an AI oversight committee composed of stakeholders with diverse skill sets. This committee should identify, assess, and document AI risks while providing training to employees.
Step 5: Consider Vendor Management and Liability Issues
Organizations must manage compliance responsibilities with third-party vendors. This includes reviewing indemnification clauses and ensuring contractual provisions cover AI-related claims.
Conclusion
Designing an AI governance framework is not merely theoretical; it is an operational mandate that touches on risk management, compliance, vendor oversight, and board reporting. Moving from high-level principles to clear, defensible processes is crucial for successfully harnessing AI technology.
By following these steps and utilizing available resources, organizations can confidently adopt AI while minimizing risks and ensuring compliance.
