Europe's new AI Act sets out strict rules for how artificial intelligence is developed, sold and used across the EU. As the first wide-reaching law of its kind, it sorts AI systems by level of risk and introduces tough penalties for getting it wrong. The Act covers everything from banned uses to strict requirements for high-risk tools in sectors like healthcare, jobs and law enforcement.

This regulatory push means contract templates and supplier agreements can't stay the same. Any deal touching AI technology or data now carries fresh compliance risks. A legal health check on contracts helps organizations spot gaps, clarify who's responsible and align with the new rules before they take effect in 2025. In the sections ahead, you'll find out which types of contracts need closer review and how to start preparing for these changes.

What the EU AI Act Requires

The EU AI Act builds a legal roadmap for anyone using, developing, or supplying artificial intelligence within the European Union. Its core idea is clear: regulate AI in proportion to how risky it could be for people, their rights, or safety. This risk-based approach shapes everything from identifying banned uses to deciding how tough the compliance checklist will be.

Photo by Google DeepMind

The Act separates AI systems into four main categories, each with its own regulatory weight. Knowing where a system falls isn’t just a tick-box exercise. It shapes contract terms, due diligence, documentation, and supplier vetting.

The Risk-Based Structure: Four Tiers of AI Risk

AI systems under the EU AI Act slot into one of four risk bands. Here’s a breakdown:

• Unacceptable Risk: These AI uses are outright banned. Any system that manipulates vulnerable groups, does social scoring (like rating citizens), or enables real-time remote biometric ID in public is prohibited. These aren’t up for negotiation or contract, as the Act forbids their use within the EU altogether.
• High Risk: The most demanding rules apply here. Systems considered high risk include AI in medical devices, recruitment tools, biometric identification, law enforcement, and essential services. This band also covers any AI listed under Annex III of the Act. What makes a system “high-risk” is its potential to impact safety or fundamental rights. Detailed guidance is available in Article 6: Classification Rules for High-Risk AI Systems.
• Limited Risk: Think of chatbots, emotion recognition in cars, or AI that generates images. These aren’t banned, but do come with transparency requirements like making AI-generated content clearly labeled. Users should always know when they’re interacting with a machine.
• Minimal or No Risk: Most AI applications today fall here—these pose little threat to safety or rights. Minimal-risk systems aren’t directly regulated, but developers are encouraged to stick to basic responsible AI principles.

A quick comparison makes it easier to scan:

Risk Level	Requirements	Examples
Unacceptable	Prohibited altogether	Social scoring, subliminal manipulation
High	Rigorous compliance, detailed documentation, oversight	Biometric ID, medical devices, employment tools
Limited	Transparency (tell users AI is involved), clear labeling	Chatbots, deepfakes, emotion analysis
Minimal/No Risk	None specific; general good practice encouraged	Spam filters, basic automation

High-Risk Systems: Core Legal Obligations

If a contract involves a high-risk AI system, the compliance load is significant. The Act requires that providers and deployers handle risk throughout the product’s lifecycle, from design to daily operation. Core obligations include:

1. Comprehensive Risk Management
   • Organizations must set up repeatable, auditable processes to identify, evaluate, and control risks.
2. Detailed Technical Documentation
   • High-risk AI must come with clear, up-to-date records explaining how it works, the data sources used, and decision logic.
3. Human Oversight
   • Systems must allow for meaningful human intervention or controls if things go wrong.
4. Robust Data Governance
   • Controls must address data bias, accuracy, privacy, and relevance. Only high-quality, representative datasets are allowed.
5. Transparency
   • Users must get clear information about AI capabilities, limitations, and instructions for use.
6. Ongoing Monitoring and Incident Reporting
   • Issues or near-misses have to be tracked, and certain incidents reported to authorities.
7. Cybersecurity and Resilience
   • Security protections are essential for the whole system lifecycle.

For an expert summary of requirements, see the High-level summary of the AI Act.

These guardrails are not just internal company policy. They must show up in supplier agreements, customer contracts, and technical annexes. Any service contract or procurement agreement tied to high-risk AI now needs explicit clauses handling compliance and documentation responsibilities.

Why Risk Classification Shapes Legal Strategy

Contract negotiation starts with clear risk classification. Whether you’re building, buying, or selling AI, knowing if your solution is banned, high risk, limited, or minimal-risk changes everything. High-risk means stricter terms, longer timelines, documentation handover, and often more insurance or liability clauses. If you get risk classification wrong, non-compliance can trigger legal, financial, and reputational fallout.

Staying up to date with evolving guidance on high-risk AI systems is a smart move for any legal or procurement team. Each update gives more clarity about what regulators expect and how AI providers need to prepare documentation.

Getting to grips with the EU AI Act isn’t only about technology—it’s about reshaping how we handle risk, manage relationships, and set legal expectations for any product or service touching AI.

Contract Types Most Exposed Under the Act

Once you identify where your AI system lands on the risk scale, the next step is to ask: what kinds of contracts carry the greatest risk? The EU AI Act doesn't just rewrite compliance rules, it raises the stakes for how businesses source, license, process data, and maintain AI tools. Procurement, licensing, data, and service contracts in regulated fields like healthcare and digital health are especially in the spotlight. A careful legal review is now essential for these agreement types.

Procurement and Vendor Contracts

Photo by Matheus Bertelli

Procurement and vendor contracts for AI systems must go under the microscope. These deals lay the foundation for compliance by setting out who is responsible for meeting the Act’s high-risk obligations.

Key points to stress:

• Clear risk allocation: Contracts must state who handles risk classification, performance testing, and corrective action.
• Defined obligations: The supplier’s duties (conformity assessment, technical documentation, and cooperation with authorities) need to be explicit.
• Conformity assessment requirements: Agreements should mirror model clauses like the MCC-AI to cover audit rights, certification processes, and evidence retention.
• Regulated industries: Where healthcare, digital health, or finance are involved, there’s no margin for error. Even one missing obligation can trigger serious non-compliance.

Gaps or vague language about risk or data responsibility will be a red flag for regulators and can lead to disputes if things go wrong.

Licensing and SaaS Agreements

Licensing and SaaS agreements are directly affected by the Act, as AI software is most often delivered through these models. Detailed rules for transparency, technical documentation, and post-market accountability must now appear in the contract.

What to scrutinize in these agreements:

• Technical documentation handover: Providers should guarantee regular delivery of up-to-date system documentation.
• Transparency guarantees: Users must easily access information about AI decisions, logic, and limits. Any embedded AI must be clearly flagged.
• Post-market obligations: Both sides need a clear plan if problems arise, such as critical updates, incident reporting, or admitting faults.

For SaaS and licensing deals, see how the EU AI Act is already changing the rules for AI-specific SaaS agreements. If the contract is silent on these new duties, businesses risk falling out of step with incoming regulations.

Data Processing and Sharing Agreements

Contracts covering the data used to train or run AI now face extra scrutiny. The AI Act adds a fresh layer of demands on top of the GDPR, especially for datasets that may impact system fairness, privacy, or audit readiness.

Consider these hot spots:

• Data governance: The contract must specify how data quality is checked, audited, and improved over time.
• Record-keeping: Parties should document how data is collected, labeled, and handled, echoing the Act’s record-keeping duties for high-risk AI.
• Alignment with GDPR: Make sure the agreement addresses both the AI Act and GDPR, such as lawful grounds for data use, data minimization, and response rights for data subjects.
• Inputs and outputs: Who owns the training data? Who can access and audit model outputs? The contract should leave no uncertainty.

These deals can become a compliance bottleneck if they’re not updated—especially in sensitive areas like digital health.

Service and Consultancy Agreements

Deployment, operation, or maintenance of AI systems is rarely a one-time event. Service and consultancy agreements now need a sharper focus on accountability, transparency, and compliance support throughout the lifecycle.

Priorities for these contracts:

• Ongoing transparency: Service providers must commit to regular updates about system changes, vulnerabilities, or limits.
• Oversight mechanisms: There should be clear terms for monitoring and reporting, not just a one-off compliance snapshot.
• Support for conformity: Maintenance contracts must acknowledge obligations for re-certification and readiness to support audits or regulatory requests.

In heavily regulated fields, a weak service contract can unravel months of compliance work in an instant. Make sure these foundational agreements are up to date and fully mapped to the Act’s core requirements.

Key Legal Health Checkpoints for Affected Contracts

Before putting pen to paper on any contract involving AI, a legal health check is now a must. The EU AI Act introduces layers of responsibility, technical obligations, and tough penalties. Missing even a single requirement in your agreements could mean trouble down the road. Below, we break down the most important legal checkpoints organizations should review to protect themselves and keep deals fit for the future.

Photo by Kampus Production

AI System Risk Classification

Every affected contract should verify how the AI system in question is classified under the Act. This is not just paperwork; it dictates the compliance path for everyone involved.

• Confirm classification status. Require parties to clearly state if the AI is high-risk, limited, or otherwise, in writing.
• Reference up-to-date standards. Ask vendors to explain their method, relying on public sources like Article 6: Classification Rules for High-Risk AI Systems.
• Keep responsibilities current. Add terms that require immediate notice if the AI system’s status changes following guidance updates.

Clarity here steers everything else. If a system looks borderline high-risk, don’t leave it to chance—document what makes it fit the risk band and who made the final call.

Roles and Responsibilities

Clear separation of duties builds trust and prevents future disputes.

• Who handles compliance tasks such as risk assessments, documentation, and responding to regulators?
• Spell out who leads on sending information, updating technical files, or cooperating with audits.
• Assign who must report incidents to authorities and in what timeframe.
• For shared responsibilities, add a roadmap: who does what, when, and with what resources.

Tip: Use job titles, not just company names, to eliminate confusion if teams or providers change during the agreement.

Conformity Assessment Requirements

High-risk AI triggers strict conformity assessment rules. Contracts must:

• Mandate technical audits prior to launch and after significant changes.
• List the evidence that suppliers must deliver (certifications, declarations of conformity, audit trails).
• Refer to standards or model clauses like those discussed in industry guidance (for example, the EU AI Act summary for deployers).
• Allow for inspection rights, so buyers can check compliance whenever needed.

By anchoring these points, you keep compliance measurable and help avoid finger-pointing if issues surface.

Documentation Obligations

Updated, thorough paperwork is the backbone of compliance. Make sure contracts demand:

• Delivery of technical documentation at regular intervals, not just once.
• Maintenance of audit logs that record system changes, errors, and updates.
• Easy access for all parties to check compliance status and past reports.
• Rules for archiving documentation, both digital and hard copies, for the full lifespan required by law.

A table like the one below can help you track documentation needs:

Type of Documentation	Who Provides?	Frequency	Storage Duration
System technical file	Vendor	On request/annually	10 years min
Risk assessment reports	Both	After updates	10 years min
Audit logs (development)	Vendor	Rolling, as updated	10 years min
Compliance declarations	Vendor	Before contract end	10 years min

Keeping everything up to date avoids last-minute scrambles and proves your diligence if inspected.

Liability and Indemnity

With new compliance duties come bigger risks. Tidy up liability terms so you're not left carrying the bag if something goes south.

• Cap liability carefully, but make exceptions for regulatory fines or gross negligence tied to AI compliance.
• Require suppliers to indemnify you for non-compliance with the EU AI Act.
• Set out a clear process for dealing with claims, including notification deadlines and decision timelines.
• Specify insurance requirements for both data and regulatory risks.

Smart liability clauses create balance—protecting your business without scaring off key suppliers.

Practical Tips to Strengthen Contract Clauses

Don’t just patch up old contracts. Build strong, future-ready terms with these tactics:

• Insist on transparency: Every party should agree to share relevant AI documentation and notify of key changes immediately.
• Schedule compliance health checks: Plan annual or semi-annual reviews to spot gaps before they widen.
• Embed audit rights: Allow for third-party audits or “spot checks” to confirm ongoing compliance.
• Stay flexible: Add amendment procedures so you can quickly adapt contracts when the rules or tech changes.
• Consult public resources: Keep current by referencing helpful overviews such as the EU AI Act: first regulation on artificial intelligence or updates on risk classification.

Getting these health checkpoints right is like installing a safety net—catching issues before they turn into costly problems, and keeping everyone focused on responsible, legal use of AI.

Managing Ongoing Compliance and Risk

Staying compliant with the EU AI Act is not a one-time job. Meeting the regulations is an ongoing process, requiring active monitoring and governance at each stage of the AI lifecycle. As the Act rolls out in phases over the next several years, organizations will need to regularly update their contract management, risk controls, and oversight tools to avoid both compliance failures and regulatory penalties.

Photo by Markus Winkler

New rules are not static: responsibilities shift as new updates and interpretations are published, and organizations must keep governance processes agile enough to respond.

Continuous Monitoring Under the EU AI Act

For contracts involving high-risk AI, the law calls for regular, real-time monitoring of systems even after deployment. This is more than just a best practice—it’s a legal mandate defined in Article 9: Risk Management System.

Key steps for sustainable monitoring:

• Stay alert to system changes. Even small tweaks in coding, data, or functionality may trigger new risks or compliance gaps.
• Document everything. Keep detailed, up-to-date logs of risk assessments, technical changes, user feedback, and any detected failures.
• Schedule regular reassessments. Set calendar reminders for periodic risk reviews, even if no issues are reported.
• Integrate human oversight. It's not enough to trust automation alone; assign people the job of reviewing and acting on monitoring results.

Monitoring contracts must include terms spelling out these obligations, timelines, access to necessary records, and accountability if red flags arise.

Post-Market Requirements and Governance

Once an AI product or service hits the market, providers and deployers must implement robust post-market monitoring. These rules, set out in Section 1: Post-Market Monitoring, aim to ensure that compliance continues as systems learn and adapt over time.

Here’s what post-market governance looks like in practice:

• Post-market monitoring plans. Every affected contract should require a documented approach for detecting and correcting problems as they emerge.
• Incident reporting duties. The law obligates providers to report serious incidents and malfunctions to authorities in a timely manner.
• Customer support for updates and corrections. Contracts should detail how fixes, corrections, or upgrades are communicated and delivered to users.

For more on operational impact, see the analysis of post-market monitoring and enforcement impacts.

Updated governance frameworks mean designating responsible roles, establishing escalation paths, and making sure no issue falls through the cracks.

Adapting Contract Management Processes

The EU AI Act is not rolling out all at once. Key requirements become effective on various dates, with the first major rules kicking in by mid-2025 for high-risk AI. Businesses must plan contract updates well before each implementation deadline to avoid last-minute confusion.

To stay ahead:

• Map phased obligations. Keep a calendar of when new parts of the law apply to your contracts.
• Review and revise templates. Build in language that addresses ongoing monitoring, reporting, and the potential for legal changes.
• Educate business partners. Make sure all parties, from suppliers to customers, know their evolving compliance duties as rules phase in.
• Support end-to-end oversight. Address risk and updates across the value chain—from development and training to deployment and support.

Contract management tools and processes should be flexible, allowing organizations to track compliance obligations and amend terms when future EU guidance or enforcement practice changes.

Governance Across the AI Value Chain

Strong compliance does not stop at internal policies. Supply chain partners, vendors, distributors, and resellers all carry responsibility for managing ongoing risk. Every agreement needs to address who does what, when, and how information about risks, incidents, or updates is shared.

A few essential steps for robust value chain governance:

• Require prompt notification if anyone detects a high-risk event or noncompliance.
• Mandate cooperation across organizations for investigations, remediation, and reporting.
• Share updates on regulatory changes and best practices to keep everyone up to speed.

Ultimately, managing ongoing compliance and risk means moving from one-off contract reviews to dynamic, living processes—where accountability, transparency, and improvement are always on the table. Strong contract terms and clear oversight not only reduce the chance of a breach, but make it easier to react quickly if issues arise.

You can find a summary of high-level compliance steps and phased timelines in the official topics overview. Adopting these practices keeps compliance strong, whatever changes future updates bring.

Conclusion

Early contract reviews have become a critical step in preparing for the EU AI Act. Contracts that touch AI or data now carry greater legal, financial, and operational risks, especially as new rules for high-risk systems and general-purpose AI models take effect throughout 2025 and 2026. Addressing these risks through careful contract updates keeps your organization protected, avoids regulatory penalties, and builds trust across your value chain.

Continuous contract assessment is not just a one-off task. It’s a practical way to keep pace with shifting requirements and maintain strong governance as the law evolves. Start reviewing and updating your contracts now so you are ready for full compliance and any surprises the next phases may bring.

Take action today—gather your legal and procurement teams, audit existing agreements, and prioritize fixes for the highest-risk areas. You’ll set your organization on firmer ground as AI compliance moves from a future concern to a daily reality. Thank you for reading. If you have experiences or questions about contract updates under the EU AI Act, share your thoughts below.