How do we stop our teams rejecting AI?

An AI tool is rolled out, presented, accompanied by training. A few weeks later, teams use it little, work around it or go back to their old methods. People then talk about resistance to change.

Most of the time, it is not the technology that is rejected. It is a tool designed without the people who use it: it ignores a step they consider essential, it adds checks without taking any work away, or it shifts the load onto a colleague. Teams see these flaws straight away, because they know the real work.

• Working around a tool is information.When teams avoid a tool, they are often pointing to a flaw the project did not see.
• Unspoken worry slows things down more than difficulty.A team that does not know what the tool changes for its jobs moves forward cautiously.
• Teams involved early stand up for the tool.They have shaped it, and know why it is designed the way it is.

1. 01Involve two or three people who will do the work day to day from the design stage.
2. 02Ask the teams what the tool should take off their plate, not just what it should bring them.
3. 03A month after launch, go and see how the tool is really being used, and correct course.

When teams work around a tool, we start by understanding why, with them.

• Will AI cut jobs in our company?→
• Should everyone be trained before launching anything?→
• Are our managers ready?→
• Can automating one department unbalance another?→