Tool or Threat? Is AI a Good Fit for University–Industry Contracts?

Introduction

Universities face growing pressure to collaborate with industry more efficiently but with fewer resources, while still managing risk, compliance, IP, and reputation.

Add in publication rights, commercial confidentiality, public sector duties, and funder requirements and it’s clear why AI is often pitched as a magic wand, but does it genuinely help or just disguise risk as efficiency.

How AI could help in practice

• Initial review and comparison 

Quickly pinpoint anything missing or unusual in a contract and show how it compares with the university’s usual terms.

• Highlighting risks 

Flag up potentially tricky areas such as who owns intellectual property, who’s responsible for what, or restrictions on publishing research.

• Summarising long contracts 

Break down complex agreements so non-legal colleagues can grasp the key points quickly.

• Overseeing routine work 

Deal with simple, repetitive agreements so the experts can focus on trickier, high-stake contracts that need careful legal judgement.

Potential AI Pitfalls

• Context blindness

  AI can overlook crucial details, like the university’s specific rules, funder requirements, or risks unique to the sector.

  
  

• Data security and confidentiality

  Using AI requires sharing sensitive information, such as unpublished research or trade secrets, so it’s crucial to make sure that data is properly protected.

  
  

• IP complexity

Contracts often involve multiple layers of ownership, pre-existing ideas, and rights to future innovations. AI can struggle to navigate these details, so human judgement is essential.

• Accountability and false confidence

AI might produce text that looks perfect, but that doesn’t mean it’s legally safe. At the end of the day, it’s still humans who carry the responsibility for any risks.

So how should universities use AI?

• Within the constraints of crystal-clear guidelines.

• Restrict its use to approved tools and datasets.

• Treat output as drafting support e.g. flagging unusual terms, missing clauses, or risky provisions for a human to review.

• Maintain strong human oversight, especially for IP-heavy or strategic deals.

• Make sure it’s used in line within the universities governance, ethics, and data protection policies to keep sensitive information safe and compliant.

Conclusion

AI isn’t a silver bullet or an outright threat, its value lies in how carefully its used.

Within the university-industry contracts field the risks are too high for AI to operate alone, but when applied appropriately it can save time and flag potential issues that support better decision-making.

It would be interesting to hear how others are approaching this balance in practice. Where AI has added value, where has it fallen short, and what lessons can the sector learn together.

After all its not long since we worried that spreadsheets might replace an accountant’s judgement or lead to mistakes but now, they are a staple of financial and operational work, saving time and allowing professionals to focus on analysis rather than repetitive calculations.

If you’d enjoy a discussion about the pros and cons of AI let’s have a chat.

Contact Richard Jenkins 024 7698 0613 or richard@clariclegal.co.uk

Disclaimer: This blog is for general information only and isn’t legal advice. For guidance tailored to your situation, please consult a qualified legal professional.