If you’ve listened to the AI noise lately, you’d think every CEO in the UK has just two options:
- Build a revolutionary AI strategy, right now
- Get left browsing VHS tapes in Blockbuster while the rest of the world streams movies on Netflix.
It’s exhausting. And it’s not reality.
Yes, AI is changing how work gets done. We’re seeing it first-hand across our partners. But the biggest wins aren’t coming from grand “AI transformation programmes” with glossy presentations and huge promises.
They’re coming from small, unglamorous improvements to everyday work.
That fits our approach perfectly, because we don’t treat AI as a shortcut. We treat it as Kaizen.
What’s Kaizen? It’s a Japanese concept meaning “change for the better”, popularised in business as Japan rebuilt its industries after WWII. The idea is simple: instead of investing all your energy into a big breakthrough, you look for small, daily improvements that everyone can contribute to. Over time, this creates a noticeable shift in quality, speed and consistency, without the disruption (or risk) of constant reinvention.
The Team GB lesson: marginal gains win
You might be more familiar with the idea in a recent sporting context. Team GB cycling attracted attention when David Brailsford took charge and implemented his own deceptively simple version of Kaizen – “the aggregation of marginal gains”. Rather than bet everything on one magic change, he broke performance down into dozens of components and tried to improve each by 1%. Seats were redesigned. Fabrics were tested in wind tunnels. Truck interiors were painted white so dust could be spotted more easily. Riders took their own pillows to hotels. They even brought in surgeons to teach handwashing to reduce the chances of catching a cold and missing training.
None of that sounds heroic on its own. Put together, it transformed outcomes. British cycling went from being an international laughing stock to winning world championships, Olympic golds and Tour de France victories.
The small stuff matters – especially when it’s done consistently.
Where does the time go?
That’s exactly how we think about operational improvement at Smartsourcing. We work with ambitious organisations that get through a lot of administrative and knowledge work, and the thing that slows those businesses down is rarely a single dramatic failure. It’s friction. Manual work creeping into everything. Tasks that are repeated slightly differently every time. Bottlenecks caused by messy inputs and unclear handovers. Capable people spending hours on predictable tasks because “that’s just how it’s done”.
So when AI tools started becoming more accessible, we didn’t panic or scramble to build a glossy “AI strategy”. We treated AI as what it actually is: a powerful accelerant for the Kaizen approach we already live by.
As our CEO Mike Selfe puts it: “Our partners are familiar with our continuous improvement approach. Our Kaizen philosophy means we’re always on the lookout for improvements in tasks and using automation to get those marginal gains. That’s our norm.”
In other words, AI didn’t create a new direction for us. It simply made the existing direction faster. The question wasn’t “how do we become an AI-first business?” It was much more practical: “what could we make 1% better this week, and how could AI help us do it?”
“For us, the introduction of AI has been organic,” Mike says. “Because we work with documented SOPs, we have clear baselines to work from as we iterate with AI, and can stay in control of the quality of the outcomes. It’s not a case of thinking the work ‘feels’ better or faster, we actually see it objectively”
Why ground-up is better than top-down
That’s also why our adoption isn’t top-down. Our learning culture encourages improvement at grassroots level, where Associates get the opportunity to optimise their work with an AI agent. There are so many small processes in day-to-day delivery where an agent can remove steps, reduce rework, and speed up turnaround.
In practice, that means our AI agents (which we train and monitor with extreme care) can take on the repetitive, predictable parts of a job – which frees up our Associates for critical thinking, creativity, self-improvement, and delivering more for our partners.
What’s in it for you?
That shift matters because it changes capacity without immediately changing headcount. It also makes the relationship with our partners more collaborative, because both sides work from the assumption that processes are improvable rather than fixed.
Case study: Automated data collection
A good example is one of our long-standing partners: a high-growth estate agency where manual data collection used to take up a huge amount of time. We built a custom AI agent to gather and analyse information from lots of different sources such as property reports, ownership details and government information. It then cross-references that with market data and pricing trends. It also produces clear summaries, so people aren’t stuck trawling raw inputs and stitching them together by hand.
The outcome is simple and measurable. Manual data collection is now fully automated. The equivalent of two FTEs’ time has been freed up for higher-value work. Turnaround is faster for their clients because the bottleneck has been removed.
“AI isn’t taking away our work,” says our Associate. “It’s giving us the freedom to do more meaningful work.”
That’s the non-hype version of the AI story we keep seeing. Not dramatic reinvention. Not a shiny “AI revolution”. Just a series of small wins that compound – faster delivery, cleaner execution, more capacity, and better value over time.
There’s a learning curve, of course. People have to build confidence, learn how to use tools properly, and understand where AI helps and where it doesn’t. But if you already have a Kaizen mindset, that learning curve becomes part of the improvement cycle rather than a barrier to progress.
The question to ask yourself
A lot of companies are still asking: “Should we adopt AI?” In 2026, we think a better question is: “What did we improve today with AI?” Not in a grand strategic sense. In a practical one. One recurring admin task. One bottleneck. One predictable process that quietly burns hours every week.
Because the marginal gains from that, over months and years, will blow any revolutionary top-down strategy out of the water.
