Harnessing the Power of Data and AI
A practical roadmap for executives who want their organizations to lead the AI transition instead of reacting to it. Written by John A. Eisenhauer, drawing on twenty-five years of Fortune 500 data and AI work.
Why This Book
In 2025, fewer than 5% of enterprise applications embedded task-specific AI agents. By the end of 2026, Gartner projects that number will reach 40%. The definition of competitive is being rewritten in less than eighteen months, and most leaders are still working from last year's playbook.
Staying Competitive cuts through the hype, the doom, and the half-finished pilots to lay out what actually works: a clear data and AI strategy, an organization built to absorb continuous change, a workforce that is told honestly which roles will be augmented, automated, or eliminated, and an ethical posture that earns trust and keeps regulators satisfied.
It is written for the people who have to make the decisions: CEOs, executive teams, board members, and the leaders responsible for turning an AI budget into business results.
Inside the Book
The Framework
One picture that names the pieces that have to work together, and gives every conversation in the organization the same vocabulary.
The leadership playbook: why the organization is changing and how it will get there.
Workforce: AI in the hands of every knowledge worker. Workflow: AI built into core operational processes. Market: AI that changes how the organization serves its customers. Competitive advantage compounds when all three move together.
A Unified Data Foundation, an Enterprise AI Platform, a Governance and Ethics Framework, and Workforce and Culture Alignment. These are the conditions that let the Domains produce value at all.
Every Domain produces data, and every Domain improves when the right data flows back. The loop is what turns a list of AI projects into a system that keeps getting better.
Contents
Why the change is happening, what has to be in place, how to lead it, and where it goes next.
Included
Appendix A is a structured self-assessment built on the same vocabulary as the chapters: Strategy and Vision, the four Enablers, the three Domains, the Feedback Loop, and Financial Discipline. Many readers skim it first so the framework lands with concrete examples in mind, then return after Part 2 to score their organization honestly. It gives a leadership team a shared starting point for its AI roadmap.
About the Author
John has spent twenty-five years helping Fortune 500 organizations turn data into decisions and decisions into competitive advantage. His career began operating nuclear reactors on U.S. Navy fast-attack submarines, where precision and decision-making with incomplete information were survival skills. He has since led enterprise data and analytics strategy at Humana and McKesson and helped build a Data and AI consulting practice from the ground up. His work has produced more than $25 million in documented ROI from data and analytics programs.
Interested in copies for your leadership team, a keynote or workshop built on the book's framework, or a facilitated AI Scorecard session? Get in touch.