AI insights, articles and news

Vibe coding makes software faster to build. It also skips every checkpoint that normally exists between an idea and a deployed system. This article argues that the risk is not in the tool itself, but in the absence of process around it, and that most organisations using it have not yet mapped where that gap actually sits.

Most SMEs treat AI as a tool. This article argues that is the wrong frame. At the integration stage of AI maturity, AI becomes embedded into sales, finance and service workflows, delivering measurable returns through time compression, error reduction and margin protection. The real barrier is not access. It is the operational discipline and process clarity that makes integration possible.

AI adoption in regulated sectors like financial services and legal is being held back by governance gaps, not regulatory barriers, and firms that build compliance frameworks now gain competitive advantage.**

Most SMEs don't adopt AI deliberately, they drift into it. This article explores what the AI readiness and foundations stage looks like in practice, why unmanaged adoption creates real GDPR and data sovereignty risks, and how to introduce governance simply and proportionately.

AI adoption in mid-market organisations is more likely to redeploy people into higher-value work than replace them, and the real risk for leaders is not job displacement but mismanaging the transition.

Most SMEs are exploring AI informally, yet lack a clear starting point due to enterprise-focused messaging and uncertainty around cost, governance and ROI. This article outlines a practical framework for moving from AI curiosity to structured adoption, focusing on operational friction, assisted AI and early governance. The real risk is not starting too late, but allowing AI adoption to develop without direction, structure or measurable intent.

AI is widely discussed, but rarely explained in a way that reflects how SMEs actually operate. This article breaks AI into practical categories and argues that the real challenge is not access, but applying the right approach to real operational problems.

AI is often framed as a technical capability, with discussions about skills centred on data scientists and machine learning engineers. This article explores why successful AI adoption depends on a much broader set of organisational capabilities, from data foundations and governance to domain expertise and change management.

In the UK, over 99% of businesses are SMEs, yet AI is still framed as an enterprise transformation agenda. This article challenges that narrative, arguing that for smaller organisations AI is not a board-level spectacle but a practical lever for productivity, margin protection and operational scale. The real risk is not lack of access, but unstructured adoption without commercial intent.

Jake and I recently had the opportunity to attend the Cloud & AI Infrastructure London 2025. This event brought together top industry leaders, innovators, and professionals from across the cloud and AI sectors to explore the latest advancements in technology and infrastructure.