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The right small changes create disproportionate gains

The right small changes create disproportionate gains

Table of Contents

Sometimes the most valuable improvements are not always large transformation programmes. They may be as simple as:

  • Capturing information in a more structured format
  • Moving validation earlier in a workflow
  • Giving AI access to the right reference material
  • Combining several review stages
  • Automatically drafting work before human review
  • Routing exceptions instead of people reviewing everything
  • Changing when and where a decision is made

AI agents typically add most value by handling the repetitive work so a small redesign at the right point can remove hours of downstream work.

Examples
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1. Change the point of data entry
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A sales team uses AI to summarise customer calls, but staff still enter key details manually into the CRM afterwards. A small process change—having the AI update the CRM directly from the call transcript—removes duplicate work, improves data quality and gives managers a more accurate pipeline.

Small change: automate where information enters the process. Disproportionate gain: hours of admin removed across the whole sales team.

2. Route exceptions, not every transaction
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A finance team uses AI to read supplier invoices, but employees still review every one before payment. By changing the process so AI automatically approves invoices that match a purchase order and only sends exceptions for review, staff stop checking routine transactions.

Small change: humans review only unusual cases. Disproportionate gain: thousands of manual checks disappear without reducing control.

3. Give AI authority within clear limits
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A customer service AI drafts responses, but every reply still requires manager approval. The company creates a set of approved actions the AI can take automatically, such as issuing refunds below £25 or changing delivery dates.

Small change: allow AI to act within defined boundaries. Disproportionate gain: faster resolutions, fewer escalations and much lower management workload.

The common pattern is that the biggest gains rarely come from a more powerful AI model. They come from removing one unnecessary handoff, approval or duplication around it.

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