Key components of effective due diligence standards for evaluating AI-related vendor risks in enterprise technology procurement

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Executive Summary

The AI vendor risk landscape has fundamentally transformed in 2024-2025, demanding a paradigm shift in how organizations evaluate and manage third-party AI providers. Our research reveals that 91% of CISOs report increased third-party cybersecurity incidents, with AI vendors contributing significantly to this growth. Yet paradoxically, only 3% of organizations maintain full visibility into their AI vendor supply chains, creating a critical governance gap as AI adoption accelerates across enterprises.

The proliferation of AI vendors—from foundation model providers to specialized computer vision systems—has introduced unprecedented risk categories that traditional vendor management frameworks cannot adequately address. Organizations face a confluence of challenges: model hallucinations threatening data integrity, algorithmic bias risking regulatory violations, vendor lock-in limiting strategic flexibility, and an evolving regulatory landscape spanning from the EU AI Act to emerging US state legislation.

This white paper presents a comprehensive framework for CISOs to navigate this complex terrain. Based on analysis of recent incidents, regulatory developments, and emerging best practices, we identify five critical imperatives for AI vendor risk management:

1. Implement AI-specific due diligence standards that address unique risks like model drift, data poisoning, and algorithmic fairness

2. Adopt continuous monitoring approaches replacing periodic assessments, as AI models evolve dynamically

3. Establish cross-functional governance structures integrating technical, legal, and ethical perspectives

4. Negotiate AI-aware contracts with specific provisions for data rights, model portability, and bias remediation

5. Build adaptive compliance capabilities to navigate the rapidly evolving global regulatory landscape

Organizations implementing comprehensive AI vendor risk frameworks report 50% improvement in AI adoption success rates and significantly reduced compliance exposure. As AI becomes critical infrastructure for digital enterprises, the ability to effectively evaluate and manage AI vendor risks will increasingly determine competitive advantage and operational resilience.

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