AI change management
AI change management: The work of helping people adopt AI-changed workflows: redefining roles, training, communicating limits and building trust through visible review and measurement.
Why it matters
Many technically sound AI systems fail because the people expected to use them were not involved. Involve the team that does the work in discovery, show them the review UI early, make clear what the system will and will not decide, and measure usage alongside quality after launch.
Related terms
- AI adoption: The extent to which people in an organisation use AI tools. Adoption measures usage; AI transformation measures whether workflows and outcomes changed.
In practice
In a Sudo Sapient engagement this is settled in the one-week Discover phase, before any build starts. The studio's process is on sudosapient.com.