Profiting from science: the development and valuation of Artificial Intelligence new ventures and engagement with the science base

  • Salter, Ammon (PI)
  • Baruffaldi, Stefano (CoI)

Project: Research council

Project Details


Context: The UK government seeks to position the UK as a leader in Artificial Intelligence (AI). In this context, AI is often seen a new transformative, General-Purpose Technology (GPT). However, we lack evidence and understanding of how AI technologies are being used by new ventures to create and capture value. Novel GPTs, like AI, can reshape industries' dynamics, leading to the development of new products, services, and business models. Science-based new ventures often play a critical role in overcoming regulatory, market, and technical uncertainty in emerging GPT technologies. Yet, AI is characterized by a dual nature between its academic roots and application-driven software development, making its development pathway potentially different from other recent GPTs, such as biotechnology and software. Moreover, the "science-based" category does not capture the broader spectrum of scientific engagement approaches that AI firms are adopting. Indeed, some AI new ventures appear to be leading actors in scientific communities, while others, at an opposite extreme, have little or no interaction with science.

Objectives: At present, our understanding of how AI new ventures interact with and profit (or not) from the research base is modest. The objective of this proposal is to break new ground in understanding this question. It draws on three tightly integrated projects to generate new insights into how new ventures profit from science. First, it will lead to the development of a new AI Venture and Research Observatory (AIVRO) that will reveal the universe of AI new ventures in the UK and their engagements with the research base. The research will develop a taxonomy of new ventures' scientific engagement by drawing together data from company reports, scientific publications, conference proceedings, research collaborations and other sources. This dataset will be a unique resource to map the UK AI innovation eco-system, offering a significant research tool for other researchers. Second, the project will assess the impact of scientific engagement on new ventures' commercialisation strategies, innovative outputs, and business performance, providing direct evidence about the interactions with the research base may shape venture growth and development. Third, using an experiment, the research will causally assess the value ascribed to scientific engagement for AI new ventures by potential investors.

Expected benefits: The research will provide robust evidence to inform and underpin management and policy concerning the development of AI and the research base in the UK. It will also extend our understanding of how new ventures mobilise external resources, especially within the science system, to help them overcome the challenges they face and to help garner support for external actors. The new database will enable other researchers to build and extend this analysis to capture new and different aspects of AI new ventures. We also plan to strengthen the research community. We will do so through the creation of a new dataset of AI ventures and their engagement to the research base, an Early Careers Researchers workshop, symposia at key conferences, and publications in leading journals. In addition, the project will engage a broad range of practitioners, through our Industry and Policy Advisory Board, and policy workshops and reports. Our AVRIO database will also offer a user-friendly opportunity for analysis and visualisation of the links between research and companies in the UK AI eco-system.
Effective start/end date1/07/2330/06/26


  • Economic and Social Research Council

RCUK Research Areas

  • Management and Business studies


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