The foundation that makes your AI yours

Organisations everywhere are investing in AI – knowledge assistants, analytical models, automated reporting, intelligent search. For many, the technology is capable and the pilots look promising. The challenge arrives when they try to scale.

In our experience, the problem is rarely the AI technology itself. It is the knowledge layer underneath it. The data exists, but it is scattered. The documents exist, but only a few people can find them. The expertise exists, but it lives in people's heads and walks out the door when they leave. The reports exist, but two of them say different things about the same number, and nobody is quite sure which one is right.

AI systems are often seen as a shortcut past the hard work of getting your foundation in order. But many of these problems do not disappear with AI – they get amplified. Systems produce confident answers that are slightly off, or even confidently wrong. And confident wrong answers at scale are significantly more dangerous than the inefficiencies that we wanted to replace in the first place.

The organisations that will succeed with AI are not necessarily the ones with the most sophisticated models or the largest technology budgets. They are the ones that did the harder, less glamorous work first – and got their knowledge in order so that AI has something reliable to reason over.