The Chaos
Chaos: The Blue Blob and the Very Real AI Bill
Discovery: The AI bill already has a fixed due date, the benefit delivery date appears to be waiting the promise date for the benefits.
The Chaos
Discovery: The AI bill already has a fixed due date, the benefit delivery date appears to be waiting the promise date for the benefits.
The AI cost stack is becoming harder to ignore but the benefit stack often has a softer, less tangible flavour in nature. Once AI spend becomes material, the gap between invoice and proof becomes impossible to hide.
Guides
AI value often gets lost because cost and benefit live in different places. Use this when AI costs is visible, or leadership keeps asking when the benefits will show up.
The Chaos
Discovery: A fixed benefit savings number appears to have been estimated from use cases currently being mapped.
A savings number without a work map is not value, check that it is not a wish with a currency symbol. Savings only become real when work changes, cost changes, revenue changes, quality changes, risk changes or time is genuinely freed and reused.
Guides
A target can be useful, but once the number becomes official, everyone starts protecting the number instead of testing whether the work actually improved. Use the AI Savings Reality Check to confirm your targets.
The Chaos
Discovery: The most exciting AI announcement email appears to have made the employees nervous. The threads on the discovery investigates the whys.
Guides
Use this when a team is nervous, people keep asking whether AI will change their jobs while everyone replies with 'exciting opportunities.' The answer to 'what changes for me on Monday?' should be transparent.
The public conversation around AI anxiety is now impossible to ignore, many people are quietly wondering whether the next cheerful AI announcement is really about their job, their skills, their team, or the work they thought they understood.
The Chaos
Discovery: Experts appear to be required from Beginner stage after training but Beginners work is now being done by AI. Find out more...
Guides
Use this when students, graduates, trainees, junior employees or career-switchers are using AI tools heavily in work that used to be learned through practice.
As AI is very good at producing tidy-looking analysis, a workplace can become more productive on paper while slowly reducing the opportunities people need to develop judgement and creativity.