Britain’s AI strategy will succeed or fail on a single decision: will government treat universities as consultees, or as the core engines of AI-driven growth? Dr Andrea Taylor, CEO of Edinburgh Innovations, writes in The Times
The Scottish Government’s new AI Strategy points to a tantalising prospect: £23 billion in additional annual GDP by 2035. But AI-powered productivity requires deep expertise and access to rich datasets and world-class infrastructure - all connected to a serious commercialisation pipeline that can turn ideas into firms, jobs and exports.
The University of Edinburgh is unusual in having these factors at national scale. That makes it a strategic economic asset for Scotland and the UK.
For more than 60 years, Edinburgh has been a global leader in artificial intelligence. Today, that legacy lies in strengths from natural language processing to robotics, causal inference and trustworthy AI, providing a bedrock on which products and services can be built.
This expertise is plugged into real-world data. Through facilities like the Edinburgh International Data Facility and Dataloch, researchers and companies can work with secure, high-quality datasets in finance, climate and health. Projects like NeurEYE, which uses AI to detect dementia risk through high-street eye tests, show how mission-led innovation can simultaneously improve lives and create new markets.
Expertise and data are then supercharged by infrastructure. Edinburgh hosts the UK’s national supercomputing facilities, with ARCHER2 already returning an estimated £8 to the UK economy for every £1 invested. A £750 million investment pipeline will power everything from climate-change modelling to the performance testing of new drugs. Alongside this sits the Edinburgh Genome Foundry, an automated biolaboratory for designing and building DNA. Bringing AI together with engineering biology opens new frontiers in advanced therapeutics, industrial biotechnology and sustainable materials.
Yet none of this translates into economic growth without commercialisation - particularly licensing technologies and venture creation - as the bridge. Last year alone, Edinburgh launched 31 new companies aligned with a mission of harnessing data, digital and AI for good. New ventures are helping businesses adopt quantum software (Qinara), using AI platforms to target aggressive cancers (Trogenix), and building smarter, lower-carbon energy systems from Scotland’s natural assets (SeaWarm and Exergy3).
To transform an AI ecosystem into an AI economy, policymakers must treat universities as strategic partners, providing proof-of-concept funding for the difficult early stages of research commercialisation, for example, as prioritised in the Scottish Government’s recent Ideas to Impact report.
We need businesses to see universities as early co-creators, testbeds and gateways to specialised talent and infrastructure. And investors must cultivate the patience and sectoral understanding to back deep tech ventures that take longer to mature but generate more durable value.
For their part, universities should keep lowering barriers to entrepreneurship, simplifying IP and data governance, and opening up innovation pathways to a more diverse range of staff and students.
For the UK to shape and export AI, grounded in our own values and institutions, we must recognise universities like Edinburgh as the engines at the heart of the machine, turning world-class AI into companies, careers and long-term national prosperity.
This article was published in The Times on April 1, 2026
