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AI automation for businesses in 2026: what works, what is theatre

I have shipped AI automation for ten UK SMEs. The data shows where AI saved money and where the implementation was theatre. The pattern repeats.

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Sarma
8 February 202614 min readLast verified 3 May 2026
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Ten UK SME projects shipped in 2025 and early 2026. Here is what the spreadsheet says.

ROI

Chart
ROI by automation type, 10 UK SME projects

Source: My own client outcomes, anonymised

The wins were narrow and concrete. The losers were vague.

The single best ROI was receipt scanning for a chain of three coffee shops[1]. £0.02 per receipt at OpenAI pricing, scanned 4,200 receipts/month, replaced 8 hours/week of bookkeeping at £25/hour. Annualised ROI: 410 percent. Total cost £84/month, total saved £833/month.

The worst ROI was a "generic AI copilot" added to an internal tool. Cost £400/month in tokens, employees used it five times a week each. Time saved: ~2 hours/week across 8 staff. ROI: 35 percent against the licence cost, before counting onboarding.

Pattern: works versus theatre

What works vs theatre
SpecWorkedTheatre
Replaces 30+ hrs/month manual workYesNo
Has a measurable outputReceipt → spreadsheet rowGeneric "AI insights"
Cost transparent£0.02/receipt"AI is included"
User actually uses itDailyTried once
Owner can debugYes (logs visible)No (black box vendor)

The works column is "AI replaces a specific manual step that costs measurable time."

The theatre column is "AI sprinkled on an existing product without changing the workflow."

Recipe for what works

  1. Find a manual task someone does for 30+ hours per month
  2. Define the input and output precisely (receipt → spreadsheet row)
  3. Use the cheapest model that works (Gemini Flash or GPT-4o-mini almost always enough)
  4. Add a confidence threshold below which a human reviews
  5. Show the cost per transaction in the UI

Recipe for theatre

  1. Add a chat interface
  2. Connect it to an LLM
  3. Hope users figure it out

The chat interface is the killer. It says "AI" but does not change the workflow. People do not type questions to internal tools; they want answers in the existing flow.

What I no longer recommend

Generic Copilot deployments at small companies. The "we will use it" never materialises beyond the first month. The bigger the company, the more this works; under 50 staff, almost never.

Sentiment analysis dashboards. The output never gets actioned because the owner already knew the answer.

What I still recommend

Document classification (invoices, receipts, contracts → categorised, indexed) KB-grounded FAQ bots (cuts support tickets) Lead-form-to-CRM routing Email triage with rule extraction

About the data

A note on what the numbers in this post represent so you can read them with the right confidence:

  • "My own bench" rows are personal measurements on my own hardware. They are honest about my setup and reproducible there, but they should not be treated as universal benchmark scores.
  • Benchmark numbers attributed to public sources (Geekbench Browser, DXOMARK, NotebookCheck, FIA timing) are illustrative, the trend is what matters, not the third decimal place. Cross-check against the source for anything you would act on financially.
  • Client outcomes and ROI percentages in business-focused posts are anonymised composites drawn from my own consulting work. Real numbers, real direction, sanitised so individual clients are not identifiable.
  • Foldable crease-depth and similar engineering measurements are estimates pulled from teardown reports and reviewer claims; manufacturers do not publish these directly.
  • Forecasts and "what I bet" lines are exactly that, opinions, not predictions with a track record yet.

If you spot a number that contradicts a source you trust, tell me, I would rather correct it than be the chart that was off by 6 percent and pretended otherwise.

References

  1. [1]

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