Britain's forgotten middle - why mid-market businesses hold the key to the UK's growth ambitions

Every conversation about the UK's future as a technology hub seems to orbit the same two poles of the FTSE100 giants who have the budgets to adopt whatever tools they like, and the scrappy start-ups whose funding rounds make headlines for record-level capital investment. Sandwiched between them is a mid-market segment that is often mis-classified from a software perspective and untapped in its potential to fulfil Britain's ambition to adopt AI domestically, along with its growth ambitions. 

In my 25 years in software, I've watched waves of technology sweep through corporate Britain. From client-server to cloud, cloud to SaaS, even standard SaaS to AI-integrated, and now the scramble towards realising value from AI. Each wave saw market-leading enterprises with extensive procurement budgets moving first whilst organisations with less headcount and smaller IT teams played catch up. This time, however, many mid-market businesses face the unique challenge of being treated like large enterprises despite having hugely different technology needs and resources. 

What is the mid-market 

The Government's last business report defines a "medium-sized" business as one with 50 to 249 employees, which is useful for tracking other economic indicators like employment rates. But when software vendors talk about the mid-market of businesses it generally means organisations that carry enterprise-grade obligations without the technology procurement budget to match.  

This definition difference is a blind spot in the UK's AI adoption agenda. Many mid-market businesses are classified as "large" because they employ more than 250 people, pushing them outside the official SME category that more closely matches their constraints. Despite contributing to a £2.7 trillion in turnover in 2025, many mid-market businesses are too large to benefit from SME-focused support schemes whilst lacking the resources to invest in technology at the same scale as major enterprises. 

This means that a business like JLA, employing hundreds of employees to sell commercial equipment to large housing and catering enterprises from their Yorkshire HQ, are grouped alongside outdoor equipment vendor Decathlon who operate internationally with close to 100,000 employees. So the mid-market has neither targeted support nor competitive resources, and Britain's AI adoption strategy is missing out on a significant share of the economic engine it's aiming for. 

AI adoption ambition 

The ambition to accelerate AI adoption in high growth sectors across British businesses through the BridgeAI plan is a welcome one. But ambition doesn't close the gap between what large enterprises can do and what the mid-market can actually afford to do.  

For example, based in regional Scotland the beverage brand AG Barr falls out of either category, despite being a longstanding successful British business looking to adopt an affordable AI. Left unsupported, businesses in this scenario have significantly overspent on unsuccessful AI not suited for their needs. Our own research suggests UK businesses are wasting a collective £11.7 billion on ineffective AI spending. These are the agile mid-market UK businesses making budget-savvy procurement decisions designed for quick turnaround and stable growth. Driving businesses in this sector could play an important role in improving productivity and supporting economic growth. A better understanding of what successful AI adoption for this part of the market would help policymakers make more informed decisions on AI, benefiting businesses and British adoptions targets. 

 What's preventing adoption 

Cost is the most obvious barrier, but it's often misunderstood. Mid-market leaders aren't asking for AI to be free, but they are asking for it to be honestly priced for their scale. Too many AI software tools are architected and priced for enterprises with dedicated implementation teams and six-figure change budgets. That's not sustainable adoption for mid-market businesses, or even large businesses. 

Integration is the less visible but equally corrosive problem. Mid-market companies have typically built up a decade or more of "good enough" systems patched with a CRM here, a helpdesk there, or a finance package that nobody wants to touch because it just about works. Real AI adoption is a full-scale renovation project on a house that's still fully occupied. If medium-sized businesses are being encouraged to adopt AI successfully there needs to be an understanding for meeting existing systems where they are. 

Then there's skills issues of both shortages of technical IT specialists and of confidence. Many mid-market leadership teams are experienced, commercially sharp operators but have never had a reason to build deep in-house technology expertise. Increasing AI adoption on a national scale asks them to make significant decisions in an area where they may reasonably feel out of their depth. And again, for many medium sized and mid-market businesses that is often without the peer network or vendor relationships that larger enterprises use to de-risk those decisions. 

What needs to happen 

If the UK wants AI adoption to be a success and a genuine driver of economic growth, the conversation needs to move beyond headline investment announcements and focus on execution. With the new Prime Minister, Andy Burnham, planning to take spending power to regional authorities and creating a new Minister of State for AI, Britain's adoption may become more accessible across the UK. As Burnham looks to deliver change early on, a tangible win would be to ensure AI solutions for this unique market are easy to deploy, quick to realise value, and designed to work with the systems businesses already have in place. 

While much of the UK's new AI growth strategy will be shaped in policy rooms in the North and in the boardrooms of the country's largest companies, delivering Britain's AI adoption ambitions will depend on whether growing businesses across the country receive the right support. If the UK is serious about becoming an AI-powered economy, technology needs to be designed and priced with these businesses in mind.