AI Value and the Operating Model
Companies with the same AI tools report very different results. The difference is how work, roles and decisions are organized around the tools.
Most companies now have access to the same AI models and platforms. The companies reporting measurable results across the business have changed the operating model: how work is structured, which roles make which decisions, how teams are measured and how fast the organization adopts a change.
An operating model built for people moving information through layers does not use AI well. Approvals wait for meetings. Teams own tasks, and few teams own outcomes. Incentives reward activity. AI completes the task faster, and the process still stops at the same handoffs.
Leading companies redesign end-to-end processes around outcomes. They remove handoffs and approval layers, give each team ownership of a result and the data to manage it, and invest in the managers who lead the change on the front line.
Three priorities for the leadership agenda:
1. Evaluate where work waits: the time each core process spends in handoffs and approvals.
2. Assess whether each result has one team or leader with the authority and information to deliver it.
3. Review the training, measures and time frontline managers have to redesign work in their teams.
Where does work in your company wait for an approval that adds no information?
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