01The use cases.
| Case | What happened | The impact | Why it matters |
|---|---|---|---|
| 04The chatbot was replaced twice before anyone looked at what it was reading | Successive chatbots failed, the software vendor was blamed for the first, the digital team for the wrong answers that followed. The cause was the landscape the chatbot read. | Internal disruption, the cost of 3 deployments, and time spent chasing the wrong cause, with wrong answers reaching citizens throughout. | A widespread problem. The chatbot answers from the estate as it finds it, and the organisation answers for what it says (Air Canada, cited briefly). |
| 162 AI tools, 2 different answers, and consequences the organisation could not see in full | Search and Gemini present materially different pictures of the same organisation. Access, source selection and processing can contribute; no single cause is asserted without evidence. | Applicants told different courses and dates by different tools. Wrong mileage repayment details from government information. | Lost confidence, and the human cost of dealing with the challenges that follow. |
| 30Applicants acted on entry requirements the university had already changed | Course pages, fees, entry requirements and prior-cycle prospectuses stay reachable. Different tools return different answers to applicants. Applicants decide on them. | Complaints and consumer-protection questions, cycle after cycle. | 73% of student AI users received incorrect information, including wrong grade requirements. |
| 35The estate the digital team had warned about for years | The digital team warned of the sprawl for years; the first step in correcting AI was the footprint. Higher education instance: a university replatformed to a single platform, single point of governance and control, and removed the old sites. A 9-month project the team had wanted for 3 years, brought forward by what AI was surfacing. | Ongoing savings: operating cost, and beyond it better information, more confidence, better-informed applicants and control of the message. | The positive case. The team was right, and the return is measurable. |
02The other sectors.
The same library, by sector: Government, Listed companies, Financial services, Life sciences, Chemicals and Consumer brands. The full list of 45 is on the use cases page.
Next step
Talk it through, in your terms.
The briefing sets the cases that apply to you in your organisation’s terms, and the discussion follows your questions.
Cases marked Illustrative or Scenario are written from the mechanism; the others are observed or documented. No organisation is named.