Many organizations deploy artificial intelligence systems through third-party vendors rather than developing the technology internally. While vendor-provided AI tools can accelerate adoption, they also introduce new legal and operational risks. Companies relying on external AI providers must therefore conduct appropriate due diligence before integrating these systems into business operations.
Vendor due diligence helps organizations evaluate how AI systems are developed, how data is handled, and whether adequate safeguards exist to reduce legal exposure associated with automated decision systems.
Why AI Vendor Due Diligence Matters
When organizations deploy AI systems provided by vendors, responsibility for harmful outcomes may be shared between the vendor and the company using the technology. Courts and regulators often examine whether companies evaluated vendor systems before relying on them for important decisions.
Failing to conduct adequate due diligence may increase the likelihood of legal liability if an AI system produces harmful or inaccurate results.
Key Areas to Review When Evaluating AI Vendors
- How the AI system was trained and what data sources were used
- Whether the vendor provides documentation explaining how the system operates
- Testing procedures used to evaluate model performance
- Security and privacy safeguards protecting sensitive data
- Procedures for monitoring system performance after deployment
Reviewing these factors helps organizations understand how the vendor’s technology operates and whether risks associated with automated decision systems are being managed responsibly.
Contractual Protections for AI Deployments
In addition to technical due diligence, companies often rely on contractual provisions to allocate risk when working with AI vendors. These agreements may include indemnification clauses, liability limitations, and warranties regarding system performance.
Carefully structured contracts help clarify responsibility if AI systems produce harmful outcomes.
Why Vendor Risk Management Is Increasingly Important
As artificial intelligence systems become more complex and widely used, vendor risk management programs are expanding to address AI-specific concerns. Organizations deploying automated technologies increasingly evaluate vendor governance practices, testing procedures, and risk management policies.
For a broader discussion of contractual risk allocation involving artificial intelligence systems, see AI Contractual Risk & Vendor Liability.
You can also explore how responsibility is evaluated when AI systems cause harm in AI Liability: Who Is Responsible When Artificial Intelligence Causes Harm?.