As the orchestrator of XPlain-R, I should set the scene for this work.

• This is to get AI into productive use for the nost complex of jobs
• Its to help smaller organisations to exploit AI to good affect.
• Public open and transparent methods will best benefit organisations over supplier or provider specific prompt design.
• XPlain will be a community operated entity with a formal Advisory Board as overrsight.

I’ve built my career around technology exploitation—taking emerging tools, working out what they might do, and turning them into practical solutions that make the impossible possible. That was fun… mostly. Whether it meant improving systems, reshaping processes, or helping people work with more clarity and confidence, I’ve always been drawn to problems where technology genuinely makes working—and living—better.

My years as a UK Government strategic consultant reinforced that drive. They gave me a front-row seat to how powerful technology can be when used well, and how damaging it becomes when done badly. It left me with a lasting ambition to put that learning to productive use.

We’re now at the end of a grand first cycle of digital transformation. Many emerging technologies have passed their peak of practical benefit and slipped into a world shaped by commercial excess, misuse, and generational absurdities. Our tools—AI especially—have become so capable they frequently outstrip our cognitive capacity to understand or apply them. Trust has rarely been lower. Fraud, both blatant and legitimised, has become endemic, undermining the miracles we casually carry in our pockets.

This isn’t a new concern for me. Back in the 1990s, I worked as an expert witness and helped shape legal admissibility practices for computer-generated evidence—something people now depend on daily without realising the complexity behind it.

Although I stepped back from earning a living, I continued as an external adviser to a major cloud services provider. With the sudden hype around AI, we explored what was genuinely possible in GRC systems. The results pointed to ways of thinking and working that were truly game-changing—bordering on incomprehensible.

That journey led to work with ISO Switzerland’s Customers Matter programme, aiming to make complex standards more accessible to SMEs. Then, through the International Trade Council and supply chain appraisal work, I am now a “solo artist” with a rather extraordinary hobby.

That same instinct now drives my work on XPlain-R: a common-ownership mechanism to ensure what we get from AI remains legal, decent, honest, and truthful. Not always straightforward when you look at how some ‘actors’ are using the technology.

We’re entering a world where AI isn’t just another tool—it’s becoming a thinking partner. The challenge is no longer capability; it’s whether we can use it well. Professionals need ways to reason clearly, avoid hidden biases, and trust the outcomes they build with AI. It’s compliance 101: everyone in a supply chain or leadership must trust what they’re told.

That’s where XPlain fits. It’s a framework designed to bring structure, transparency, and consistency to complex analysis, enabling humans and machines to think together in ways that are traceable, auditable, and dependable. Its not all my own work; others have contributed much, not always in hours but as ideation and challenge – I thank them for that care and attention.

For me, it’s simply the next step into a new grand technology cycle: using emerging technology not just to get answers faster, but to help people think better.

What fun!

Kenneth Tombs

November 2025

Pont Hebert, France.

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