The emperor’s new robot

WALK THE floor at any major cleaning or FM trade show and you know exactly what you're going to see. Autonomous scrubbers doing their thing in the aisles. AI-enabled robots pulling a crowd. Sensor-driven building management systems with a sales pitch that promises to change everything. The technology is impressive. It’s also, in many cases, genuinely useful and this article isn’t going to tell you otherwise.

But there’s a conversation the sector isn’t having and it’s costing businesses money.

While capital investment in visible, operational technology continues to grow - the UK cleaning robot market alone is projected to nearly quadruple in value by 2030 - a significant proportion of cleaning and FM businesses are overlooking a category of AI that costs between £20 and £30 a month, requires no technical integration, and is already delivering measurable returns across every business function now.

Two very different technologies

I’m going to clarify what tech we’re talking about, because the term ‘AI’ is being widely used at the present time.

Operational AI - the robots, the autonomous scrubbers, the sensor networks and building management platforms - is capital-intensive technology. It requires procurement, infrastructure, technical integration and significant lead time before you see a return. Industry benchmarks suggest payback periods of between 18 and 36 months are typical for autonomous mobile equipment. That’s not a reason not to invest. It’s a reason to have done your homework seriously and to have a plan.

Generative AI - tools like ChatGPT, Claude and Microsoft Copilot - is an entirely different proposition. These tools write, research, analyse and create content. They work across every department, don’t need IT infrastructure, project integration or capital investment. And at business grade, they cost around £20-30 per user per month.

These aren’t competing technologies. They are radically different in what they demand from a business and how quickly they deliver. And at the moment, the sector’s attention and its budgets are heavily weighted towards one of them.

The bid software question

Nowhere is this clearer than in how businesses approach tendering.

AI-driven bid management platforms have become an increasingly common purchase in the sector. Some are sophisticated tools with genuine capabilities. But they also come with significant subscription costs, implementation requirements and learning curves. I regularly meet businesses that have invested in them without fully appreciating that a well-trained team using a standard generative AI subscription can produce comparable first drafts - tailored to their tone of voice, their sector knowledge and case studies for a fraction of the price.

I’m not saying bid software has no value. For high-volume, complex procurement pipelines it can absolutely earn its place. But for most cleaning and FM businesses, the question worth asking before signing up is: do we actually need this, or do we need to get better at using the tools we already have?

Tender responses that used to take a full day are being completed in two to three hours. Client reports that consumed half a morning are taking twenty minutes. These aren’t projections. They’re what’s happening in businesses in this sector that have invested properly in training their teams to use generative AI well.

The pattern that keeps repeating

At Interclean Amsterdam 2026, I delivered two sessions to audiences spanning multiple continents and businesses of every size. The enthusiasm for AI was genuine and widespread. The ability to demonstrate what it was actually returning was almost entirely absent.

That mimics what we found closer to home. Research conducted at the Manchester Cleaning Show found that 70% of businesses were not tracking any return on their AI investment. They had bought access but hadn’t built the capability.

This isn’t a technology problem. The RAND Corporation’s research into AI project failure found that more than 80% of AI initiatives don’t progress beyond initial implementation and the cause is almost never the technology itself. It’s the absence of leadership literacy, proper training and governance frameworks.

UK-wide data makes the same point. Analysis drawing on government research found that 97% of UK businesses have at least one AI skills gap and that organisations are missing an estimated 40% of potential AI productivity gains simply because their teams can’t use the technology they’ve already purchased. Fewer than 5% of UK employees use AI in advanced ways, despite 83% claiming to use it daily.

What this means in practice

The businesses getting the strongest returns from technology right now are the ones who have answered three questions before they spend.

Do our people understand what this tool is for and how to use it properly? Do we have a clear policy governing how it’s used, what data goes into it and who is responsible for the output? And are we measuring anything - time saved, quality improved, revenue influenced - so we can tell whether it’s working?

Those questions apply to a £150,000 autonomous scrubber fleet and they apply equally to a £25-a-month generative AI subscription. The difference is that the consequences of skipping them cost a lot more when the initial outlay is higher.

For most cleaning and FM businesses, the honest starting point is generative AI. Not because the bigger technology isn’t worth pursuing but because the foundations you build by adopting generative AI properly are exactly the foundations, you’ll need to make operational AI deliver. Data discipline, training culture and a leadership team that understands what they’re buying and why.

The bigger picture

The title of this piece is a provocation, not a verdict. The emperor’s new robot is real; it works and the sector’s investment in it reflects genuine ambition. But ambition without awareness is expensive.

The businesses that will lead on technology over the next five years won’t necessarily be the ones with the most impressive kit on the floor. They’ll be the ones who understood the whole picture. What each tool is for, what it demands from the organisation and what it can realistically return before they committed the budget.

If your business hasn’t yet got to grips with generative AI - not just played with it, but properly adopted it with training, policy and measurement in place then that’s where you should start. It’s low cost, low risk and the return is fast, and it will make every other technology investment you make more likely to succeed.

Ceris Burns is managing director of CBAi, which provides specialist AI training and strategy for the cleaning, FM and environmental sectors. 

For more information, visit www.cbai.co.uk