Balancing Caution with Opportunity: The AI Dilemma Facing UK Startups
This won’t come as news to most, but with recent data revealing that 69% of UK CFOs say cutting costs over the next 12 months is a strong priority, it’s initiatives like AI that could end up on the chopping block in even the most ambitious of startups - unless founders are ready to take a leap of faith.
Risk vs reward
The AI race isn’t just for large companies - it’s something that UK startups need to make a priority if they are to compete for a piece of the pie.
While AI adoption accelerates across Europe and the US, most UK SMEs are still holding back on using AI, with many citing a lack of expertise (35%), high costs (30%) and uncertainty around ROI (25%) as key barriers . All of these are valid concerns – after all, small businesses are conscious of the bottom line and investing in the initiatives that move the needle for them.
But it is also short sighted to not think about how AI can help, from minimising admin time and automating tasks, to helping teams focus on the bigger picture and ultimately, the success of the business.
An SME successfully using AI in its business model is Applied, a skills-based recruitment software. Applied helps companies to reduce hiring bias through anonymised applications and predict the best candidates for a role. Recruiters can set skills-based assessments and interviews using AI, create inclusive job advertisements, and monitor how diverse their organisation is through the platform. By integrating AI into some of its features, Applied is allowing companies to streamline the hiring process and find the right candidates through data-driven insight.
Remaining globally competitive
It’s not all doom and gloom though, as 50% of small businesses believe AI is an important long-term strategic goal: something that comes as no surprise as UK entrepreneurs are known for bold ideas. But a clearer focus on how investment into AI infrastructure, talent, and research is achieved and when will help British businesses to stay competitive with their European and American peers.
1. Think Long-Term
AI projects don’t always have to be huge cost factors. Start small, with pilot projects that deliver quick wins to help secure executive buy-in and further investment in the long term.
2. Focus on Key Projects
Focus resources on initiatives that improve efficiency and deliver high impact, such as automating routine tasks, AI-driven customer service, or predictive maintenance. These savings can actually free up budgets to reinvest in further innovation.
3. Expand Data Literacy
Without quality data and skilled talent, AI projects will stall. Double down on data governance, integration, and employee training to build a foundation for success.
4. Leverage Funding
Schemes like Innovate UK grants and R&D tax credits have programmes aimed at SMEs and startups that can offset the cost of AI experimentation and help build confidence in AI.
5. Tackle Regulatory Uncertainty Head-On
Don’t let legal or regulatory uncertainties block innovation. Stay informed about the latest AI regulations and make use of available guides and resources. Engage early with regulators or legal counsel to secure clarity for your AI projects instead of leaving it to the last minute.
The tipping point
The AI race is already underway and it isn’t slowing down. UK startups and SMEs should take a leap of faith as AI soon won’t be optional but rather an essential part of creating a globally competitive business.
