New book argues enterprise AI gap is a capability problem

Built for AI Press has published Built for AI: A Practitioner's Guide to Moving Beyond Pilots and Building Enterprise AI Capability at Scale by Punit Vir and John H. Dobbs. The book argues that companies are not failing on AI technology itself, but on the enterprise capability needed to turn AI into measurable business value.

Why it matters: - The book targets a growing gap between AI investment and business results. - Its core argument is that many enterprises can make AI work in pilots, but cannot scale it into operating-model change and measurable value. - The authors frame that gap as a capability problem, not a technology problem.

What happened: - Built for AI Press announced the publication of Built for AI: A Practitioner's Guide to Moving Beyond Pilots and Building Enterprise AI Capability at Scale. - The book is by Punit Vir and John H. Dobbs. - The title is available in ebook, paperback, hardcover, and full-color editions. - Retailer links are available at all retailer links. - The paperback ISBN is 979-8-9972319-7-2. - Amazon lists the book at Amazon.

The details: - The book introduces Enterprise Absorption Capacity, which the authors define as an enterprise’s ability to absorb AI into daily work and convert it into business value. - The framework calls for choosing the right opportunities, redesigning workflows, establishing ownership and decision rights, governing risk, and repeatedly moving AI from technical potential into performance. - The book centers on the Built for AI Framework and the Built for AI Strategy Canvas. - Supporting tools help leaders decide what to scale, where human judgment should remain, which implementation pattern to use, how ready the enterprise is, and how each deployment can increase capability. - The book highlights four actions for leaders: build capability with every implementation, fund the Vital Few initiatives, redesign the work itself, and turn AI investment into measurable business value. - The book is written for executives, transformation leaders, consultants, and managers responsible for making AI work inside large organizations.

Between the lines: - Recent BCG research is used to show the scale of the problem. - BCG's 2025 global study, The Widening AI Value Gap, surveyed more than 1,250 companies and found only 5% generating value from AI at scale, while 60% saw little or no material benefit. - BCG's AI Radar 2026 surveyed 2,360 executives across 16 markets and found companies planning to roughly double AI spending this year. - That combination suggests investment is rising faster than enterprise readiness. - The book also signals a shift in AI strategy language, from asking what AI can do to asking what the enterprise must become.

What's next: - Built for AI is now available across major retail channels. - Media materials, including the cover, author photos, fact sheet, and interview topics, are posted at media materials. - The authors are available for interviews, podcasts, and executive briefings at press@builtforai.ai. - The book is positioned as a practitioner guide for leaders trying to move from experimentation to scaled execution.

The bottom line: - The book’s central thesis is blunt: enterprise AI success depends less on better models and more on whether an organization can redesign itself to use them well.