Decisions keep waiting
Several people are involved, but it is unclear who can decide.
An executive briefing
AI can improve tasks. To turn those improvements into enterprise value, examine how decisions, processes and information connect.
Start with one important workflow. Develop coherence and AI adoption together.
88% of organizations use AI, yet only about 6% attribute 5% or more of their EBIT to it. More tools will not close that gap.
Read the chapter 02For the workflow you want to improve, connect goals, processes, decision rights and data as you develop the AI application.
Read the chapter 03Copilots spread small gains across everyone. Value concentrates where AI is built into one end-to-end process.
Read the chapter 04Parallel work, fewer handoffs and less waiting create the step change.
Read the chapter 05Every agent needs an identity, boundaries and a person accountable for it. Match autonomy to risk.
Read the chapter 06Pick one process, align it end-to-end, measure outcomes, then scale what you built.
Read the chapterOrganizations have rapidly deployed GenAI, mostly as horizontal tools such as copilots and chatbots. These tools help with: Writing, Summarization, Information retrieval, Meeting preparation, Content generation and Individual productivity. The gains are real, but spread thinly across thousands of employees and individual tasks. The business process underneath stays largely the same.
The value gap. Adoption runs roughly fifteen times ahead of meaningful earnings impact. Only about 6% of organizations attribute 5% or more of their EBIT to AI.
Deploying AI broadly is not the same as transforming the business.
AI outcomes depend on both the technology and the organization around it. Waiting decisions, repeated handoffs and unclear responsibilities can limit the value of an otherwise useful application.
Reduce friction before you accelerate. Otherwise agents make the old problems faster.
The organizations that create disproportionate value from AI will not simply deploy more copilots or build more agents. They will identify the processes that matter, redesign them around human and machine capabilities, govern agent autonomy, and connect AI investment directly to measurable business outcomes.
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