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Case study

ChatGPT and Gemini Won't Save Your Business — Start Over

5 May 20263 min readListen to the episode

TL;DR

  • The function: one structured, recurring, rule-based function — finance, compliance, ops, sales intelligence, legal review, or customer operations.
  • The lens: a 2-3 person mirror team designing from a blank sheet, not retrofitting existing workflows.
  • The result: top 20% of organisations capture 74% of all AI economic value (PwC, 1,217 executives, 2026).

The framework

The Mirror Function. Pick one function. Run a small parallel version of it alongside the existing one for 6-8 weeks, designed from scratch around AI agents. Measure the gap between mirror and incumbent. The deliverable is not a tool — it is operational knowledge of how that function works when redesigned, not retrofitted.

The agent stack

  • ChatGPT — operational engine for reading, processing, drafting, and synthesis across the workflow.
  • Claude — operational engine for long-context reasoning and large-document analysis.
  • Gemini — operational engine for multimodal tasks and Workspace-native work.
  • Your internal data layer — documents, CRM, finance system, ticketing — feeding the agents.
  • Human reviewer — judgment gate on agent outputs before they reach decision-makers.

Replicate it — step by step

  1. List every function in your business and rank them by share of structured, recurring, rule-based work.
  2. Pick the top one. Just one. Resist the urge to do three.
  3. Write the redesign question on one page: "If we built this function from scratch today with AI agents doing the structured work from the start, what would it look like?"
  4. Ring-fence 2-3 people, a small budget, and a 6-8 week timebox.
  5. Forbid the team from automating the current workflow — their job is to design a new one.
  6. Have them prototype the rebuilt function using ChatGPT, Claude, or Gemini as the operational engine.
  7. Define which decisions agents make autonomously and which require a human judgment gate.
  8. Run the mirror in parallel with the existing function on the same inputs for the full timebox.
  9. Measure output quality, cycle time, and resource requirement against the existing function.
  10. At week 8, present the gap to the board and pick the next function to mirror.

Before / after

  • Worker AI access rose 50% in 2025 (Deloitte, 3,235 leaders, 2026).
  • Only 34% of organisations are truly reimagining operations (Deloitte, 2026).
  • Top 20% are 2x more likely to redesign workflows than add tools (PwC, 1,217 executives, 2026).
  • Top 20% capture 74% of AI economic value; bottom 80% share 26% (PwC, 2026).
  • Education was the #1 talent-strategy adjustment companies made for AI (Deloitte, 2026).
  • [reader: measure your own baseline — cycle time, cost, throughput, decisions automated]

Replicate in one day

  • 09:00 (60m) — Map every function in the business; rank by structured, recurring work.
  • 10:00 (60m) — Pick the top function. Write the redesign question on one page.
  • 11:00 (90m) — Name the 2-3 mirror team members, set the 6-8 week scope, ring-fence the budget.
  • 12:30 (30m) — Lunch. No phones.
  • 13:00 (90m) — Draft the success metrics: output quality, cycle time, resource cost.
  • 14:30 (60m) — Define the agent stack and access permissions for the mirror team.
  • 15:30 (90m) — Brief the team. Confirm: redesign, not retrofit. End of day one.