Edinburgh SMEs Can Get Up to £25,000 for AI Projects

Edinburgh businesses looking to introduce artificial intelligence can apply for between £2,500 and £25,000 through Scottish Enterprise’s AI Adoption Grant.

The scheme covers up to 50% of eligible project costs and can support feasibility work, pilots, implementation, staff capability and governance for responsible AI use. Projects must be completed by 31 March 2027.

For local firms considering AI, the money raises a practical question, alongside which tools to use and what they might save: who checks the work AI produces before somebody acts on it?

Scottish Government figures show why that question is becoming harder to ignore. In June 2026, 34.8% of businesses with 10 or more employees and a presence in Scotland were using some form of AI. Among businesses with 10 to 249 employees, the figure was 33.3%.

AI Is Already Part of Edinburgh Business

Edinburgh already has a strong base of companies working with AI and data.

Skyscanner was founded in the city and still has around 420 people based at its Edinburgh office, with technology and engineering making up a large part of the team. Edinburgh-headquartered CreateFuture is also working with Skyscanner on areas including data and AI tooling.

CreateFuture was also named an OpenAI Select Partner in July 2026, reflecting the level of AI engineering already underway in the city.

And earlier this summer, Multiverse opened an AI engineering hub in Edinburgh, with plans to create 200 jobs across Edinburgh and London. Edinburgh247 covered that move in July.

For most local SMEs, though, AI adoption is likely to be less dramatic. It may start with staff drafting emails, summarising meetings, researching suppliers, analysing data or producing first versions of documents.

That is also where mistakes can quietly slip through.

Not Every AI Mistake Carries the Same Risk

A poor suggestion during a brainstorming session is easy to discard. Incorrect wording in a contract, a misleading summary of a job applicant or an error in financial information is another matter.

Behavioural scientist Dr Gleb Tsipursky argues that businesses should put clear guardrails around AI before it becomes embedded in everyday workflows.

His new book, The Psychology of AI Adoption at Work: From Resistance to Results, puts human judgement at the centre of that process.

“Treat Gen AI as an assistant to humans so you elevate judgment, compress cycle time, and compound learning.” – Dr Gleb Tsipursky

That principle is useful for smaller businesses because it does not require every AI task to be treated the same way. Lower-consequence work, such as brainstorming, rough drafts, and internal summaries, may only need a quick sense check.

Customer-facing or operational work needs more attention. Emails, recommendations, and material that influences another person’s next action should have a named reviewer checking accuracy and context.

Higher-consequence work, including hiring, legal commitments, financial decisions, confidential information, or safety-related tasks, should have clear human approval and accountability.

Tsipursky describes a guardrail map as one of the practical tools businesses can build alongside an adoption plan and measures for tracking results.

For a small firm, that could be as simple as a one-page document explaining what staff can use freely, what needs to be checked, and who is responsible when something goes wrong.

What the Scottish Enterprise Grant Can Support

The Scottish Enterprise scheme is not limited to buying software.

Eligible work includes identifying AI opportunities, testing the feasibility of an idea, running pilots, introducing systems into existing workflows, and building staff capability.

It can also support the processes and governance needed for responsible AI adoption.

Businesses must have more than 10 employees, be based in an area supported by Scottish Enterprise, and have a clearly defined AI project or business challenge.

Funding is competitive, and projects must be approved before funded work begins.

For an Edinburgh company already experimenting with AI, the application process could therefore be a useful point to decide not only what to automate, but also what should remain under human control.

Measure Whether AI Actually Helps

Using more AI doesn’t automatically mean a business is improving. The more useful measures are tied to outcomes: time saved, faster response times, fewer errors, and less rework.

Tsipursky’s book makes the same point, arguing that businesses should build measurement into AI adoption rather than treating usage itself as proof of success.

If staff repeatedly have to correct the same kind of AI output, tighter controls may be needed. In some cases, AI may simply be the wrong tool for that job.

For Edinburgh SMEs looking at the Scottish Enterprise grant, the more useful question may be: where does AI genuinely improve the work, and where should a person remain in charge?

Dr Gleb Tsipursky is a behavioural scientist and author of The Psychology of AI Adoption at Work: From Resistance to Results, published by Georgetown University Press.