Under the EU AI Act, organisations using third-party AI systems remain accountable for compliance obligations, making vendor due diligence and supply chain management critical.

With penalties reaching €35 million or 7% of global turnover, effective vendor compliance strategies can be the difference between regulatory success and catastrophic non-compliance.

The era of “set it and forget it” vendor relationships is over. As the EU AI Act reshapes the regulatory landscape, organisations across Europe—and globally—are discovering that their third-party AI vendors represent both their greatest compliance opportunity and their highest-risk vulnerability.

The regulation’s complex web of obligations doesn’t stop at your organisation’s boundaries. AI Act compliance now extends throughout your entire AI supply chain, creating new responsibilities that demand immediate attention.

Understanding the AI Supply Chain Reality

The modern AI ecosystem is inherently interconnected. To work toward compliance with the EU AI Act, practitioners need to determine the AI systems their enterprises use, create, and deploy. Identifying these systems can mitigate the risk of shadow IT.

Note that not all AI use will be subject to the EU AI Act or handled the same way under the Act.

This interconnectedness creates a complex web of responsibilities. Consider a typical enterprise scenario: your HR department uses an AI-powered recruitment tool from Vendor A, which incorporates machine learning algorithms from Vendor B, running on cloud infrastructure from Vendor C, and using training data provided by Vendor D.

Under the EU AI Act, each entity in this chain has specific obligations, and your organisation’s compliance depends on every link working correctly.

When Third Parties Become Primary Providers

One of the most significant surprises in the EU AI Act is how easily organisations can inherit provider obligations from their vendors. Any distributor, importer, deployer or other third-party shall be considered to be a provider of a high-risk AI system for the purposes of this Regulation and shall be subject to the obligations of the provider under Article 16, in any of the following circumstances: (a) they put their name or trademark on a high-risk AI system already placed on the market.

This means your organisation could become a provider if you:

• Rebrand or white-label an AI system from a vendor
• Make substantial modifications to a third-party AI system
• Change the intended purpose of an AI system to make it high-risk
• Integrate multiple AI components into a new high-risk system

Real-World Example: A financial services company licenses a credit scoring algorithm from a specialised AI vendor. If they modify the algorithm significantly or rebrand it as their own product, they may suddenly find themselves subject to all the obligations of a high-risk AI system provider—including conformity assessments, technical documentation, and quality management systems.

The Written Agreement Requirement by AI Act

The EU AI Act mandates specific contractual arrangements between providers and their supply chain partners. The provider of a high-risk AI system and the third party that supplies an AI system, tools, services, components, or processes that are used or integrated in a high-risk AI system shall, by written agreement, specify the necessary information, capabilities, technical access and other assistance based on the generally acknowledged state of the art.

Essential Contract Elements under AI Act

Information Sharing Requirements:

• Technical specifications and system architecture details
• Risk assessment documentation and mitigation strategies
• Training data sources, quality metrics, and bias testing results
• Performance monitoring capabilities and incident response procedures

Technical Access Provisions:

• Rights to audit AI system performance and compliance
• Access to system logs, decision-making processes, and algorithmic explanations
• Ability to test and validate system functionality
• Integration support for compliance monitoring tools

Ongoing Support Obligations:

• Regular updates on system changes that could affect compliance
• Cooperation during regulatory inspections and conformity assessments
• Assistance with incident reporting and remediation
• Support for evolving compliance requirements.

Due Diligence in the AI Era

Due diligence is crucial when selecting an AI system provider as deployers may be liable for providers’ shortcomings. Modern AI due diligence extends far beyond traditional vendor assessment practices.

Pre-Procurement Assessment Framework

AI System Classification:

• Determine if the vendor’s AI system qualifies as high-risk under Annex III
• Assess potential for system modifications that could change risk classification
• Evaluate alignment with your organisation’s intended use cases
• Review compliance with prohibited AI practices

Vendor Compliance Readiness:

• Verify quality management systems meeting EU AI Act standards
• Review technical documentation completeness and accuracy
• Assess conformity assessment procedures and CE marking status
• Evaluate post-market monitoring and incident response capabilities

Supply Chain Transparency:

• Map the vendor’s own supply chain and sub-processor arrangements
• Assess third-party components and their compliance status
• Review data sources, including training and testing datasets
• Evaluate cybersecurity measures throughout the vendor’s supply chain

Advanced Due Diligence Questions

Technical Governance:

• How does the vendor ensure algorithmic accountability and explainability?
• What measures exist to detect and mitigate bias in AI outputs?
• How are training data quality and representativeness validated?
• What human oversight mechanisms are built into the system?

Regulatory Preparedness:

• Has the vendor completed EU AI Act conformity assessments?
• What documentation can be provided to support your compliance obligations?
• How will the vendor notify you of regulatory changes affecting the system?
• What support is available for your fundamental rights impact assessments?

Risk Management:

• What incident detection and response procedures are in place?
• How are serious incidents defined, tracked, and reported?
• What business continuity measures exist if compliance issues arise?
• How are system updates managed to maintain compliance?

Contract Strategy: Beyond Standard Terms

The EU AI Act has introduced new contractual considerations that traditional vendor agreements don’t address. Organisations need AI-specific contract clauses that allocate compliance responsibilities and create accountability mechanisms.

Model Contract Frameworks

The European Commission has developed Model Contractual Clauses for AI Procurement (MCC-AI) that provide a starting point for compliance-focused contracts. The European Commission (EC) has released an updated version of the Model Contractual Clauses for AI Procurement (MCC-AI), providing further guidance for public-sector buyers navigating AI procurement under the European Union Artificial Intelligence Act (EU AI Act). However, these clauses also serve as a practical tool to help any private organisation meet their legal obligations when providing or procuring AI systems, particularly high-risk AI solutions.

Essential Contract Provisions

Compliance Allocation:

• Clear definition of which party handles specific EU AI Act obligations
• Responsibility matrices for documentation, testing, and monitoring
• Liability allocation for compliance failures and regulatory penalties
• Insurance requirements covering AI-related risks

Change Management:

• Notification requirements for system updates affecting compliance
• Approval processes for modifications that could change risk classification
• Procedures for handling evolving regulatory requirements
• Rights to terminate if compliance cannot be maintained

Audit and Oversight:

• Rights to conduct compliance audits and system assessments
• Access to technical documentation and system performance data
• Requirements for vendor cooperation during regulatory inspections
• Notification obligations for incidents and compliance issues

Data Governance:

• Rights and responsibilities regarding training and operational data
• Data quality standards and bias mitigation requirements
• Procedures for handling data subjects’ rights and requests
• Compliance with data protection regulations alongside AI requirements

Managing Multi-Vendor Complexity

Modern AI implementations often involve multiple vendors contributing different components to a single system. This creates compliance challenges that require sophisticated coordination.

Integration Compliance Challenges

Component Interaction Risks:

• How do individual compliant components interact when integrated?
• Who is responsible for testing integrated system compliance?
• How are conflicts between vendor requirements resolved?
• What happens when one vendor’s compliance affects others?

Responsibility Coordination:

• Defining clear boundaries between vendor responsibilities
• Ensuring no compliance gaps exist between vendor obligations
• Managing overlapping requirements and potential conflicts
• Coordinating incident response across multiple vendors

Ecosystem Management Strategies

Vendor Hierarchies:

• Establish primary vendor relationships with integration responsibilities
• Create clear communication channels between all supply chain participants
• Define escalation procedures for compliance issues affecting multiple vendors
• Implement regular coordination meetings and compliance reviews

Standardization Approaches:

• Develop consistent compliance requirements across all AI vendors
• Create standard contract templates incorporating EU AI Act requirements
• Implement unified monitoring and reporting procedures
• Establish common incident response and notification protocols

Industry-Specific Considerations

Different sectors face unique challenges in managing AI vendor compliance, requiring tailored approaches to supply chain management.

Financial Services

Regulatory Overlap:

• Coordinate EU AI Act compliance with financial services regulations
• Manage algorithmic accountability requirements across multiple frameworks
• Address model risk management expectations from financial regulators
• Ensure compliance with anti-discrimination and fair lending requirements

Vendor-Specific Challenges:

• Credit scoring systems requiring explainability and bias testing
• Fraud detection systems needing real-time monitoring capabilities
• Trading algorithms subject to market manipulation prohibitions
• Customer service bots requiring transparency and human oversight

Healthcare

High-Risk System Prevalence:

• Medical device AI requiring conformity assessments and CE marking
• Diagnostic support systems needing clinical validation
• Patient monitoring systems requiring data protection and accuracy
• Treatment recommendation systems demanding explainability and oversight

Supply Chain Complexity:

• Integration with medical device manufacturers and healthcare IT providers
• Coordination with research institutions providing training data
• Compliance with healthcare-specific data protection requirements
• Management of liability for medical AI decisions and recommendations

Manufacturing and Industrial

Safety-Critical Applications:

• Industrial control systems requiring cybersecurity and reliability
• Predictive maintenance systems needing accuracy and robustness
• Quality control systems requiring bias mitigation and consistency
• Autonomous systems demanding safety certification and oversight

Operational Challenges:

• Integration with existing industrial control systems and safety protocols
• Coordination between AI vendors and traditional industrial suppliers
• Management of intellectual property and trade secret protection
• Ensuring compliance across global manufacturing operations

The Hidden Costs of Non-Compliance

Poor vendor compliance management carries risks that extend far beyond regulatory penalties.

Direct Financial Impact

Regulatory Penalties:

• Fines up to €35 million or 7% of global annual turnover for prohibited AI use
• Penalties up to €15 million or 3% of turnover for high-risk system violations
• Additional costs for corrective actions and system modifications
• Potential suspension of AI system operations pending compliance

Operational Disruption:

• Emergency vendor replacements when compliance issues arise
• System modifications or replacements to meet regulatory requirements
• Audit and investigation costs when compliance issues are discovered
• Legal costs for dispute resolution and regulatory defense

Indirect Business Impact

Market Access:

• Exclusion from EU markets if AI systems cannot achieve compliance
• Competitive disadvantage against organisations with compliant AI systems
• Customer trust issues when AI compliance problems become public
• Difficulty attracting talent concerned about regulatory compliance

Strategic Limitations:

• Reduced AI innovation capacity due to compliance uncertainties
• Limited ability to scale AI operations across jurisdictions
• Vendor lock-in when switching costs include compliance restart
• Reduced merger and acquisition opportunities due to compliance liabilities

Building Compliance-Ready Vendor Relationships

Success in the EU AI Act era requires fundamentally different approaches to vendor relationship management.

Proactive Compliance Integration

Early Engagement:

• Include compliance requirements in RFP processes from the beginning
• Conduct compliance workshops with potential vendors during evaluation
• Build compliance milestones into vendor onboarding and implementation
• Create joint compliance roadmaps with strategic AI vendors

Ongoing Monitoring:

• Implement continuous compliance monitoring for all AI vendors
• Establish regular compliance review meetings and assessments
• Monitor regulatory developments affecting vendor obligations
• Track vendor compliance performance and improvement initiatives

Partnership Development

Collaborative Compliance:

• Work with vendors to develop shared compliance solutions
• Participate in industry working groups addressing AI compliance challenges
• Share compliance best practices and lessons learned across vendor relationships
• Invest in joint compliance technology and process development

Strategic Alignment:

• Align vendor contracts with long-term compliance strategy
• Build compliance considerations into vendor performance metrics
• Create incentive structures rewarding proactive compliance behavior
• Develop preferred vendor programs emphasizing compliance excellence

Technology Solutions for Vendor Compliance

Manual approaches to vendor compliance management cannot scale to meet EU AI Act requirements. Organisations need technology solutions that automate compliance monitoring and management.

Automated Compliance Monitoring

Real-Time Assessment:

• Continuous monitoring of vendor AI system performance and compliance
• Automated alerts when vendor systems deviate from compliance requirements
• Integration with vendor APIs for real-time compliance data
• Dashboard views providing consolidated vendor compliance status

Documentation Management:

• Centralized storage and version control for vendor compliance documentation
• Automated collection and validation of required compliance artifacts
• Integration with vendor systems for seamless documentation updates
• Audit trail management for all vendor compliance activities

Supply Chain Visibility

Vendor Mapping:

• Complete visibility into AI vendor supply chains and dependencies
• Risk assessment across multi-tier vendor relationships
• Impact analysis for vendor changes affecting compliance
• Compliance gap identification across vendor portfolios

Integration Management:

• Monitoring of integrated AI system compliance across multiple vendors
• Automated testing of compliance when vendor systems are updated
• Coordination of compliance activities across vendor relationships
• Centralized incident management across vendor ecosystem

Looking Ahead: The Future of AI Vendor Management

The EU AI Act represents just the beginning of global AI regulation. Organisations building strong vendor compliance capabilities today will be best positioned for the evolving regulatory landscape.

Regulatory Evolution

Global Harmonization:

• Preparation for similar AI regulations in other major jurisdictions
• Development of vendor compliance frameworks adaptable to multiple regulations
• Investment in vendor relationships capable of supporting global compliance
• Building expertise in cross-border AI compliance management

Technical Standards Development:

• Participation in industry efforts to develop AI compliance standards
• Investment in vendor relationships supporting emerging technical standards
• Preparation for automated compliance verification and certification
• Development of vendor assessment criteria based on emerging best practices

Strategic Competitive Advantage

Organisations that excel at AI vendor compliance management will gain significant competitive advantages:

Market Leadership:

• Faster deployment of compliant AI systems compared to competitors
• Access to best-in-class AI vendors prioritizing compliance
• Reputation as a responsible AI adopter attracting top talent and customers
• Strategic partnerships with vendors developing next-generation compliant AI

Operational Excellence:

• Reduced compliance costs through efficient vendor management processes
• Lower risk exposure through proactive vendor compliance monitoring
• Faster innovation cycles enabled by streamlined compliance procedures
• Enhanced decision-making supported by trustworthy AI systems

Final Thoughts: Transforming Challenge into Competitive Advantage

The EU AI Act’s vendor compliance requirements represent a fundamental shift in how organisations must approach their AI supply chains. While the complexity is significant, organisations that invest in robust vendor compliance capabilities will emerge stronger and more competitive.

The path forward requires:

• Comprehensive vendor assessment frameworks incorporating EU AI Act requirements
• Sophisticated contract management with AI-specific compliance provisions
• Continuous monitoring capabilities tracking vendor compliance performance
• Strategic partnerships with vendors committed to compliance excellence
• Technology solutions automating and scaling vendor compliance management

Success in this new environment isn’t just about avoiding penalties—it’s about building the foundation for sustainable AI innovation within a compliant, trustworthy framework. Organisations that master AI vendor compliance will find themselves not just regulatory compliant, but strategically positioned to lead in the AI-driven economy of tomorrow.

The window for reactive approaches is closing rapidly. With high-risk AI system requirements taking effect in August 2026 and vendor relationships requiring months or years to properly establish and optimize, the time for action is now. Your vendor compliance strategy today determines your competitive position tomorrow.

Master Your AI Vendor Compliance Strategy

Are your third-party AI vendors your biggest compliance risk or your strongest competitive advantage? With the EU AI Act’s complex supply chain requirements and penalties reaching €35 million, effective vendor management isn’t optional—it’s mission-critical for any organisation serious about AI-powered growth.

eyreACT’s vendor compliance module (to be released in October 2025 – join the waitlist to gain early access) provides comprehensive tools for assessing, monitoring, and managing third-party AI compliance across your entire supply chain. From automated vendor assessments to real-time compliance monitoring, eyreACT platform transforms vendor relationships from compliance liabilities into strategic assets.