As AI adoption accelerates, businesses are entering increasingly complex negotiations with AI providers. This year, AI contracting will become a major focus area as procurement teams push for stronger protections on transparency, data rights, and liability.
One of the biggest challenges in AI contracting is risk allocation. AI providers typically place responsibility on the customer, emphasising that users must validate AI-generated outputs and mitigate risks independently. However, as competition intensifies, buyers are demanding stronger commitments, including:
- Transparency: Detailed disclosures on AI training data and decision-making logic.
- Indemnities: Limited but growing acceptance of indemnities for third-party IP infringement and data misuse.
- Security Commitments: Assurances against unauthorised use of customer data for model training.
Legal teams must also address liability limitations. Most AI vendors exclude liability for errors, biases, or “hallucinations” in AI-generated content. As a result, organisations must establish robust internal oversight processes to manage AI-related risks.
Key best practices for AI contracting:
- Conduct thorough due diligence on AI providers’ governance and compliance practices.
- Align AI contract terms with internal risk policies and regulatory requirements.
- Regularly review and improve AI contracts as legal frameworks evolve.
With the regulatory landscape shifting rapidly, businesses must approach AI contracts with a strategic, risk-aware mindset. 2025 will be the year when AI buyers assert greater influence over vendor terms, shaping the future of AI procurement and governance.
