When Suppliers Use AI: Contractual and Data Risks for Businesses

Artificial intelligence is increasingly embedded in the way professional services are delivered. Even where businesses have not adopted AI directly, suppliers may be relying on AI tools behind the scenes to generate content, analyse data or automate processes.

For many organisations, this creates a new category of legal and commercial risk. Contracts often assume services are performed entirely by people, yet elements of the work may now be generated or influenced by AI systems.

Understanding how suppliers use artificial intelligence, and how risk is allocated contractually, is becoming an important consideration in modern commercial relationships.

AI Is Quietly Entering Supplier Relationships

Artificial intelligence is no longer something businesses purchase only through clearly defined software platforms. It is increasingly integrated into everyday business tools and service delivery models.

Marketing agencies may use generative AI to draft content before it is refined by human editors. Recruitment consultants may rely on AI tools to screen CVs or identify candidates. Outsourcing providers may use machine learning systems to analyse operational data or optimise workflows.

In many cases, the client organisation has not procured “AI services” directly. The technology simply forms part of the supplier’s internal processes.

However, this distinction does not remove legal risk. Where AI plays a role in producing deliverables or analysing data, the contractual framework governing the services may need to address issues that traditional service agreements did not contemplate.

Intellectual Property and Ownership of AI-Assisted Outputs

One of the first questions businesses should consider is ownership of deliverables created using generative AI.

Traditional service contracts typically assume that outputs are created by individuals and that intellectual property rights can therefore be assigned to the client. AI-assisted outputs complicate that assumption. Under UK law, certain “computer-generated works” can attract copyright protection where there is no human author, but how these rules apply to modern generative AI systems remains legally uncertain.

Businesses should consider:

• whether AI-generated outputs are capable of attracting copyright protection
• whether the supplier has the right to assign those rights to the client
• whether similar outputs could be generated for other clients
• whether the supplier’s use of third-party AI tools affects ownership rights

These questions are particularly relevant where AI is used to produce marketing materials, reports, software documentation or other commercially valuable content.

Clear contractual drafting can help ensure that the ownership and use of deliverables is properly defined.

Copyright and Infringement Risk

Generative AI systems are typically trained on large datasets, the provenance of which may not always be fully transparent. Ongoing legal disputes in several jurisdictions are testing whether certain forms of AI training involve the unauthorised use of copyrighted works.

As a result, businesses should consider whether AI-generated outputs could inadvertently reproduce elements of existing protected material.

If a business publishes or commercially exploits such content, it may face an infringement claim. The question then becomes whether the supplier is contractually responsible for that risk.

Many suppliers rely on third-party AI platforms and may therefore limit the scope of intellectual property indemnities they are willing to provide. Understanding those limitations is an important part of assessing the overall risk profile of the relationship.

Confidential Information and Data Use

Another key issue is the handling of confidential information where AI systems are involved.

If a supplier inputs business information into an AI platform, organisations should understand what happens to that data once it enters the system.

Important considerations include:

• whether the AI provider retains input data
• whether that data could be used to train or refine the model
• whether it might influence outputs generated for other users
• whether the data can be deleted when the supplier relationship ends

For businesses dealing with sensitive commercial information or proprietary data, these questions are critical.

Contracts may need to include restrictions on how AI tools are used and clear protections governing the treatment of confidential information.

Data Protection and Regulatory Considerations

Where personal data is involved, the use of AI introduces additional regulatory considerations.
If suppliers use AI tools in areas such as recruitment, performance monitoring or customer profiling, organisations may need to consider the requirements of UK GDPR. Issues such as transparency, fairness and automated decision-making safeguards may become relevant.

In many situations, regulatory responsibility will often sit with the organisation that commissioned the service, even where the AI system is operated by a third-party provider.

This means that businesses should understand how AI is being used within supplier processes and ensure that appropriate data protection safeguards are in place.

Accuracy, Bias and Reliability

AI systems can produce outputs that appear authoritative but contain inaccuracies or reflect bias embedded in training data.

These risks can have real commercial consequences. Incorrect AI-generated outputs may lead to reputational damage, operational disruption or regulatory scrutiny if relied upon without proper oversight.

To mitigate these risks, businesses increasingly require:

• human review of AI-generated outputs
• clear quality assurance processes
• defined service specifications
• appropriate liability provisions in supplier contracts

Rather than relying solely on implied legal protections, organisations are focusing on practical governance mechanisms that ensure AI-assisted work remains subject to professional oversight.

Contractual Safeguards Businesses Should Consider

In most commercial environments, prohibiting suppliers from using AI entirely is neither realistic nor desirable. AI tools can increase efficiency and improve service delivery.

A more pragmatic approach is to ensure that contracts clearly define how AI may be used and how associated risks are managed.

Common contractual protections may include:

• transparency around the use of AI in service delivery
• restrictions on the use of client data within AI systems
• clear ownership provisions for deliverables
• intellectual property indemnities where appropriate
• confidentiality protections relating to AI platforms
• business continuity provisions if AI tools become unavailable

These measures help ensure that innovation can continue while risks are appropriately managed.

Reviewing Supplier Contracts in an AI-Enabled World

Artificial intelligence is already embedded in many supplier relationships, often in ways that clients may not immediately see.

As a result, organisations may have service agreements in place where AI is playing a meaningful role in delivery, even though the contract itself does not address the issue.

Reviewing supplier arrangements with this in mind can help ensure that contracts reflect the reality of modern service delivery and that risk is allocated appropriately between the parties.

How Flint Bishop Can Help

As artificial intelligence becomes more widely embedded in supplier services, businesses may need to reassess whether their existing contracts properly address the associated legal and commercial risks.

Haroon Younis, Partner and Head of Commercial Contracts, advises organisations on commercial contracts, technology arrangements and data governance. He works with businesses to review supplier agreements, negotiate appropriate contractual protections and develop practical frameworks for managing AI-related risk.