AI Business
Many believe AI is a ‘silver bullet’ to business transformation. But without this one crucial element, the results it promises will remain out of reach.
By Richard Sapsed, Head of sami at CI Group
AI is sold to the world as a something close to a superpower. One which promises to transform our businesses, condense a month of work into days, increase our revenues, and open up opportunities beyond what we previously believed to be possible. And rightly so. It is indeed capable of all of this, and many organisations are already achieving it.
But there’s an assumption quietly embedded in how AI is talked about: that the technology itself is the lone, magic ingredient, and the results automatically follow. What’s talked about significantly less, and possibly even underestimated, is the level of skill required to actually achieve them.
Because like any other tool, AI’s effectiveness is entirely dependant on the capability of the person using it. Behind every success story is an organisation that understood the problem it was solving, knew how to apply AI deliberately, and built the right structures around it. Below, I explore the central role that building AI literacy plays in driving business results, and the foundations required to turn AI ambition into measurable outcomes.
Tool selection is only the beginning
Yes, choosing the right tools matters. Different platforms lend themselves to different applications, and some carry different risk profiles when it comes to data handling and compliance. A distinction that matters enormously in regulated industries.
But the harder, more consequential challenge comes after those tools are onboarded: knowing how to use them strategically, and building the organisational capability to do so.
What I’m hearing from clients
The conversations I have with clients around AI capability I’m sure will sound familiar to many businesses. Some are large organisations in highly regulated industries who have held back entirely, not because of a lack of interest, but because of legitimate concerns around safety. If you don’t have the knowledge to confidently use AI in a way that keeps sensitive data protected and meets compliance standards, not taking the risk at all is an understandable (and sensible) position to take.
Others broadly understand what AI can do, but know they’re barely scratching the surface. They’re currently using it for everyday tasks like drafting emails and summarising documents, but struggle to move beyond that into more strategic application. Useful as a starting point, but nowhere near the impact they know is possible.
The common denominator in every case is a lack of knowledge, confidence and skill to use it safely and strategically.
The pilot trap
One of the most common patterns I see is what I’d call the pilot trap. An organisation introduces a new AI platform. Teams experiment. Early outputs generate excitement. But the activity never connects to a clear commercial outcome and eventually the pilot grinds to a halt. Not because the technology failed, but because it wasn’t built on the right foundations.
The reason is almost always the same: organisations start with the tool and then look for a problem. The more effective approach is to reverse that sequence entirely. Start with the friction. Where is your organisation losing time? Where are decisions being slowed by manual processes? Where is knowledge hard to access or inconsistently applied? Answer those questions first, and the conversation about which AI capabilities are worth deploying becomes far more grounded.
Building the capability to deliver
Identifying the right problems is only half of it. The other half is ensuring your people have the knowledge and confidence to act on them, which education and training is fundamental to.
AI literacy is the foundation everything else is built on. People need to understand not just how to use AI tools, but how to use them well: how to direct them purposefully, interrogate outputs critically, and recognise where human judgement remains essential.
Building confidence alongside capability is what turns cautious, surface-level usage into genuinely strategic application. Organisations that also create clear governance structures around approved tools, data handling and human oversight give their people the confidence to experiment without exposing the business to unnecessary risk.
Capability is the competitive edge
McKinsey’s 2025 research found that 88% of organisations are using AI in at least one business function, yet fewer than a third are scaling it across the enterprise.
PwC’s 2025 Global AI Jobs Barometer adds another insightful dimension: workers with AI skills command an average 56% wage premium, and the skills employers seek are changing 66% faster in roles most exposed to AI.
The organisations that will benefit most are those investing in human capability, building AI literacy, creating governance structures that allow safe experimentation, and developing the strategic judgment to know where AI creates genuine value in their specific context.
The question worth asking
The results you read about are achievable. But they don’t automatically arrive with the software licence. They come from treating AI adoption as an organisational challenge rather than a technology one, and invest accordingly in the knowledge, skills and structures to use it well.
For many organisations, the most practical and cost-effective route is working with an external partner who can help build internal capability, establish safe governance and accelerate the move from experimentation to impact. For regulated industries especially, that expertise can be the difference between confidently moving forward and staying stuck, or even exposing risk to the company.
If these challenges sound familiar, you’re not alone. They’re something we’ve supported many of our clients with. If you’d like to explore how our structured AI workshops could help your organisation build that capability, we’d love to talk.
Get in touch with Richard.sapsed@cigroup.co.uk.