PUTTING DATAAND AI to work.
How to choose the first project, make the funding case, build the team, and keep the system useful after launch. For the people responsible for delivery.
The Decision Company
Start with an everyday decision, find what makes it difficult, and choose the smallest change worth making.
Firmitas, utilitas, venustas
Three questions for enterprise software: does it do the job, will it last, and can people understand it?
Standing up an AI & data program
What to settle first, which projects to fund, and how to build the team that will keep them running.
Talking about AI in dollars
Count the full cost of a use case and distinguish a promising estimate from a result finance can verify.
Governance that keeps delivery moving
Agree data access, review responsibilities, and release checks early enough to shape the design.
Designing a hub-and-spoke operating model
Divide responsibilities between a shared engineering team and the business teams that use its work.
The pathfinder playbook
Use the first live projects to test your delivery process and prepare the internal team for the next release.
The data behind autonomous agents
Give AI workflows reliable business definitions, limited permissions, and actions the application can check.
Building capability from within
Develop the people who know the business and hire specialists for the gaps that remain.
Work through a question from your own program.
Tell us what you are weighing up and where you need another perspective.