You’ll remember we discussed earlier this month how having access to AI tools does not equal readiness. Research from that Chartered Management Institute showed us that less than 1 in 10 UK managers think staff receive enough AI training and only 4% of managers have trained on tools such as ChatGPT or Bard.
Allister Frost, author and speaker on future-ready work, says, “Many leaders think AI readiness is attained when the tool is available to all employees and they see some employees making use of it. This can be a huge and costly mistake because it ignores the fact that employees should be benefiting from AI, not just using it. There has to be a meaningful advantage that goes beyond speed, efficiency or perceived productivity gains.”
For startups, being AI-ready is often about experimenting and learning without fully building AI into products. Teams that talk openly about how AI changes their output, check results, and add original thought get real benefit. Frost added, “Every member of the organisation, from the most junior to the most senior, should be embracing AI where it can significantly improve their contribution. How they will use AI will be different for each person, which is why a one size fits all approach is not valid.”
Early use without structured learning can backfire. Quiet, individual use usually leads to surface-level adoption, it won’t have meaningful readiness. Junior staff who test and apply AI help shape the company’s skills for the long term, while leaders who stay distant risk turning AI into simply a task tool.
How Are UK Startups Using AI-First Strategies?
New data from e-Residency shows UK startups are moving fast toward AI-first models. By 2030, 75% of UK entrepreneurs expect most new startups to be AI-first, meaning AI is built into the heart of their products and operations from the start. Liina Vahtras, Managing Director at e-Residency, explains, “UK founders are asking for the right foundations to realise their AI potential. Without that, the UK risks seeing its most ambitious startups build and base their companies elsewhere.”
The research shows that founders see AI as essential to staying competitive. 70% warned that companies not using AI risk being outcompeted within 5 years. These businesses are also spending heavily on digital trust to protect their reputation and compliance. On average, UK startups spend 16% of operational costs on digital trust and security. Vahtras adds, “For UK founders, AI creates the opportunity, but trusted digital first systems will determine who can truly go global.”
Skills shortages in AI, data, and cybersecurity slow growth for 89% of UK startups, and 29% report that the gap has had a critical impact in the past year. Cybersecurity is the most urgent, with 80% of founders noting it as a missing capability. Small teams also struggle with financial pressure, cited by 37%, and work-life balance, noted by 34%.
Why Is Digital Trust Needed In An AI-First World?
Digital trust is now the passport for international business. 88% of UK founders say trust decides which startups succeed globally, and 85% see reliable digital infrastructure as as important as physical infrastructure. AI products only work if customers and partners can rely on them.
The risks are real. In the past year, 73% of founders faced at least one issue that had to do with online risk or misinformation. 26% say AI-generated fakes or profiles have already harmed trust in their sector. For many startups, digital trust becomes a measure of survival, with 84% wanting government support to strengthen systems and 78% noting that companies ignoring trust risk being excluded from major markets.
Vahtras explains that secure digital identity is the starting point. She says, “Digital trust starts with giving every founder a digital identity they can rely on, so they can create and run companies remotely with seamless compliance and access to wider talent, spending more time innovating with AI and less time battling bureaucracy.”
What Sets AI-First Startups Apart from AI-Ready Ones?
The difference is integration vs experimentation. AI-ready companies have tools and begin testing but are learning as they go. AI-first startups design their business model around AI from day one, aligning operations, products, and customer experience with AI.
While AI-ready startups may get efficiency gains, AI-first startups use AI to influence or even inform the value they deliver to customers and the market. They invest in secure systems, digital trust, and specialised skills, making their use of AI sustainable and able to scale globally.
