Artificial intelligence (AI) is beginning to influence not only how research is conducted, but also how its innovation potential is identified, assessed and translated into use. University technology transfer offices (TTOs) are increasingly experimenting with AI to support activities ranging from contract analysis and patent searches to market assessment and innovation scouting.
These developments could significantly change how universities identify promising research results and support their path towards practical application and commercialisation. TTOs play a central role in connecting research with potential users, partners, investors and markets, yet they often have to assess large and diverse research portfolios with limited resources. AI-based tools could help identify promising results earlier, analyse potential applications and reduce the administrative workload associated with commercialisation.
Experiences from European universities already illustrate this potential. At Trinity College Dublin, AI is being used to support activities such as reviewing non-disclosure agreements, comparing contracts with standard templates, assessing invention disclosures and conducting preliminary market and competitor research. By reducing the time spent on routine tasks, these applications can allow technology transfer professionals to dedicate greater attention to more strategic activities and engagement with researchers and industry.
At Tilburg University, AI is also being explored as a tool for innovation discovery. An AI-based scouting system has been used to screen research outputs for potentially valuable inventions and identify related patents, companies and funding opportunities. Such approaches could be particularly useful for uncovering valorisation opportunities that might otherwise remain unnoticed.
However, the growing use of AI also raises questions about the future role of TTO professionals. While some experts envisage increasing automation, universities emphasise the continued importance of human expertise, judgement and relationships, particularly when supporting researchers on their journey towards commercialisation or negotiating complex licensing arrangements.
The emerging picture is therefore less about replacing technology transfer professionals and more about reconsidering where their expertise can create the greatest value. By automating routine processes and strengthening innovation discovery, AI could allow TTOs to dedicate more resources to strategic industry engagement, co-creation and the translation of research into real-world applications.