Why AI Contract Experience Is Becoming a Priority for In-House Legal Teams

AI is changing commercial contracts, and the experience in-house legal teams need to manage them. 

As AI becomes embedded in products, platforms, and third-party services, agreements are introducing new questions around data usage, privacy, intellectual property, liability, vendor risk, and regulatory obligations. 

For employers, that is making AI contract experience an increasingly important consideration when hiring commercial legal talent. 

Araly Soto, Executive Director at Larson Maddox USA, is seeing this across industries: 

The requirement is not limited to technology companies either. Araly has worked with clients across multiple sectors who are searching for lawyers who understand transactional agreements containing AI provisions. 

AI is entering contracts across sectors 

AI does not need to be a company's core product for it to affect its contracts. Businesses may encounter AI when buying software, working with technology vendors, or agreeing how a supplier can process company or customer data. 

That creates new questions for the lawyers negotiating those agreements. 

Araly gives the example of a company outside the traditional technology sector that was looking for someone with “really strong experience handling transactional agreements specifically that have AI language in there.” 

That experience needed to extend beyond negotiating the commercial terms. The employer also wanted someone who understood developing regulations and the implications for areas such as privacy. 

As Araly explains: 

This is already affecting how businesses approach technology transactions. As organisations adopt third-party AI tools and AI-enabled services, commercial legal teams are increasingly encountering AI considerations within agreements that may previously have been treated as standard technology or vendor contracts. 

For in-house teams, AI contract knowledge is therefore becoming relevant well beyond companies that develop AI themselves. 

Why AI language can change the risk profile of an agreement 

A familiar technology agreement can carry different implications once AI is involved. 

Data usage is one example. A business may need to establish whether its data can be used to train or improve a vendor's AI model, whether information is shared with other model providers, how data is stored and protected, and what happens to it when the commercial relationship ends. 

But data is only one part of the contract. 

AI provisions can also raise questions around: 

• Intellectual property and ownership 
  Who owns inputs and AI-generated outputs, and does the vendor have the necessary rights to the technology or training material? 
• Privacy and confidentiality 
  What information can enter the AI system, where does it go, and can it be reused? 
• Liability and indemnification 
  Who carries the risk if an AI system produces an inaccurate, infringing, or otherwise harmful output? 
• Vendor risk 
  Does the supplier rely on third-party models, and what obligations flow through the AI supply chain? 
• Regulatory compliance 
  Which party is responsible for complying with applicable AI, privacy, or sector-specific requirements? 
• Commercial obligations 
  Can AI-related terms, policies, or functionality change during the life of the agreement? 

These considerations are increasingly shaping how AI agreements are negotiated. The American Bar Association has highlighted issues including ownership, warranties, indemnification, privacy, and intellectual property risk. 

This also means that commercial counsel needs to understand how AI provisions affect the organisation’s risk and ensure contracts provide appropriate protection. 

Why commercial counsel needs AI fluency 

However, not every commercial lawyer needs to become an AI regulatory specialist. Yes, they increasingly require enough AI fluency to recognise when seemingly standard contract language creates a different risk. 

For example, permission for a software provider to use customer data to “improve its services” may require closer examination if those improvements include training an AI model. Ownership provisions may also need to distinguish between the underlying technology, company inputs, and generated outputs. 

The skill is not about knowing AI terminology but is the ability to translate how the technology affects contracts and be able to provide practical advice that protects the business. 

That combination is becoming more important to the employers Araly works with. 

Clients are looking for lawyers who understand both “the language, the laws, and the regulations” surrounding AI contracts, she says. 

It also reflects the wider US hiring market Larson Maddox is seeing. Demand is growing for lawyers who can advise on areas including AI governance, privacy, vendor oversight, product liability, cybersecurity, and technology contracting.  

What should employers assess when hiring? 

AI contract experience is still developing, so employers should be careful about making a specific AI job title the only evidence of relevant expertise. Instead, hiring teams can assess what candidates have actually encountered in their work. 

Useful areas to explore include whether a candidate has:

• Negotiated technology or vendor agreements containing AI provisions
• Advised on how suppliers can access, process, or use company and customer data
• Considered ownership and permitted use of AI inputs and outputs
• Negotiated liability, indemnification, or warranty provisions relating to technology
• Worked alongside privacy, product, security, compliance, or procurement teams
• Interpreted emerging regulation and translated it into practical contractual advice
• Identified AI-related risk even when AI was not the primary purpose of the agreement

These capabilities are already visible in the market. Current Larson Maddox searches for US technology transactions counsel include responsibilities spanning data-sharing arrangements, data rights and ownership, vendor diligence, privacy, security obligations and risk allocation, illustrating how closely commercial contracting and technology risk are becoming connected. 

Employers should also consider the context in which that experience was gained. 

A lawyer who has negotiated AI provisions for a healthcare business, for example, may have encountered different privacy and regulatory considerations from counsel supporting a software company. The underlying commercial contracting skills may transfer, but the risk profile can naturally differ. 

The objective is, as an employer, to get a clearer picture by assessing the depth and relevance of the candidate's experience with the underlying issues. 

Building AI contract capability into the legal team 

AI contract experience is likely to become more relevant to a broader range of in-house legal teams as businesses increasingly buy, sell and integrate AI-enabled products and services. 

For employers, that makes it worth understanding where AI-related agreements already sit within the business and whether the legal team has the experience to assess them. 

The answer may not always be additional headcount. Existing commercial counsel may be able to develop that expertise, while other organisations may need to recruit lawyers with stronger technology, privacy, product, or regulatory backgrounds. 

Where hiring is required, defining the actual contractual risks the lawyer will be expected to manage can create a more useful brief than simply asking for “AI experience.” 

Larson Maddox specialises in connecting organisations with legal professionals across commercial, technology, privacy, and regulatory functions. Explore Larson Maddox's in-house legal recruitment expertise or speak to the team about the legal capabilities your business needs.