Large companies are surging ahead with the use of AI, but what about SMEs? Cien Solon, CEO and Founder of LaunchLemonade, explains how the next stage of the AI revolution will focus on companies building their own AI to solve their own unique challenges. And unless AI creation is democratised, SMEs may find themselves locked out of the productivity and growth potential AI can achieve.
AI is no longer confined to Silicon Valley labs or global boardrooms. It is here embedded in everyday business tools, automating workflows, analysing data and shaping decisions at speed. According to a recent McKinsey survey, 62% of respondents say their organisations are at least experimenting with AI agents and 64% say AI is actively enabling innovation. Yet despite this momentum, only 39% report a meaningful profit impact at the enterprise level.
Beneath these headline figures lies a more troubling reality: while large enterprises surge ahead, SMEs risk being left behind. Most SMEs lack the access, expertise and affordability to build AI tools that solve their challenges. The next phase of the AI revolution will not be defined by who can build the biggest model or invest the most capital, but by who can access, shape and own AI tools that solve individuals’ unique challenges. And unless AI creation is democratised, SMEs may find themselves locked out of the productivity and growth potential AI can achieve.
An uneven playing field
Today’s AI landscape overwhelmingly favours large enterprises. They have the budgets to hire specialist teams, the data to train sophisticated systems and the scale to absorb the cost of experimentation. For SMEs, the picture looks very different. Off-the-shelf AI tools often feel generic, expensive or poorly suited to niche operational challenges. Meanwhile, custom solutions typically require technical expertise and investment far beyond the reach of smaller firms.
AI has been sold as a plug-and-play solution, but in reality most tools are built with enterprise needs in mind. SMEs are expected to adapt their processes to the technology, rather than the other way round.
This imbalance matters. SMEs make up over 99% of UK businesses and account for a significant share of employment and economic output. If they cannot fully participate in the AI revolution, productivity gains will be uneven, innovation will stall and national competitiveness will suffer.
From AI consumption to AI creation
The next stage of AI adoption is a shift from consumption to creation. For most businesses today, AI is something they buy, subscribe to or bolt onto existing systems. However, true transformation happens when organisations can design and deploy AI tailored to specific workflows, customers and decision-making needs.
For SMEs, the real value of AI isn’t using the same chatbot as everyone else, it’s creating intelligent agents that understand their unique context – whether that’s managing client onboarding, forecasting cash flow or automating compliance tasks.
Historically, this level of customisation has required developers, data scientists and long implementation cycles. But advances in no-code platforms are changing that equation. By abstracting away complexity, these tools allow non-technical users to build AI agents using visual interfaces, prebuilt components and natural language instructions.
This results in AI creation becoming accessible not just to engineers but also operation managers, founders and frontline teams who understand the business best.
Practical gains for everyday businesses
SME-driven AI brings tangible results. Custom-built AI agents can automate repetitive administrative tasks, freeing up staff to focus on higher-value work. They can improve decision-making by surfacing insights from data that would otherwise go unused. They can also enhance customer experience through faster, more personalised interactions.
Crucially, these gains translate directly into improved margins. For small businesses operating on tight budgets, even modest efficiency improvements can have a great impact on profitability. Rather than replacing jobs, AI becomes a force multiplier, enabling lean teams to achieve more with less.
It’s vital to point out that there is a misconception that AI is about cutting headcount – in reality, for SMEs it’s about reducing manual workload and burnout and giving people the tools to work smarter.
The cost of exclusion
Limiting AI access for SMEs carries broader economic risks. Productivity growth in the UK has lagged behind peer economies for years and digital adoption is a key lever for improvement. If AI-driven productivity gains accrue primarily to large enterprises, inequality between firms – and regions – will widen.
There is also the risk of innovation bottlenecks. Many of the most creative solutions to real-world problems come from small businesses close to their customers and communities. Without the ability to experiment with and deploy AI, these ideas may never scale.
The UK Government’s AI Growth Plan recognises the strategic importance of AI and outlines ambitions to turbocharge adoption across the economy. However, policy must go further in supporting grassroots AI creation, not just high profile research hubs or major corporations.
Investment in skills, funding for SME experimentation and incentives for accessible AI platforms are essential. Otherwise, we risk building an AI economy that only works for the few.
Lowering the AI barriers
Platforms like LaunchLemonade aim to address this gap by enabling SMEs to build, deploy and even monetise their own AI agents without hiring technical teams. Users can create intelligent copilots and automations that integrate directly into their workflows, from sales and marketing to operations and finance.
The underlying philosophy is simple: the people closest to the problem should be able to build the solution. By lowering the barriers to entry, these platforms help close the AI literacy gap and ensure innovation is not confined to those with coding skills or deep pockets.
This approach also fosters a more diverse AI ecosystem. When businesses of different sizes and backgrounds can create AI, the resulting tools are more likely to reflect a wider range of needs, values and perspectives.
A shared responsibility
Democratising AI creation is not the responsibility of one group alone. Policymakers must ensure funding and regulation support SME access and experimentation. Technology providers must prioritise usability, affordability and transparency. And SMEs themselves must be willing to invest time in learning and adopting new tools.
Everyone has a role in working towards a significant end goal: a more inclusive, innovative and resilient economy where AI works for all businesses, not just the biggest players.
The question is no longer whether AI will transform business, but who will benefit from that transformation. If SMEs are empowered to become the creators, not just the consumers, AI has the potential to level the playing field rather than entrench existing divides. The future of work and growth may depend on it.
