9798993880679 - AI Implementation Blind Spots: How to Make AI Adoption Work in Real Business Systems de Gul, Nikolay (2 resultados)

Paperback. Condición: new. Paperback. AI Implementation Blind Spots is a practical field manual for leaders, operators, consultants, AI strategists, MSPs, IT teams, cybersecurity professionals, finance teams, healthcare administrators, portfolio operators, and business decision-makers who need AI to work inside real organizations - not just look impressive in demos.Most organizations do not fail with AI because they lack tools. They fail because they confuse speed with value, pilots with proof, adoption with implementation, and output with trusted usable work.This book gives readers a decision-first system for reducing AI rework, defining human-versus-AI boundaries, measuring real ROI, controlling risk, and deciding which AI projects deserve scale - and which should stop.Inside, readers learn how to recognize the Velocity Trap, avoid AI Theater, measure the Rework Tax, build Evidence Packs, design Decision Boundaries, protect against Shadow Ledger risk, and apply practical AI implementation playbooks across revenue, operations, finance, cybersecurity, healthcare administration, procurement, and regulated environments.This is not a prompt guide, vendor brochure, or AI hype book. It is a practical business field manual for turning AI speed into measurable, governed, and trusted results.Paperback ISBN: 979-8-9938806-7-9eBook ISBN: 979-8-9938806-5-5Library of Congress Control Number: 2026912042 A practical field manual for turning AI adoption into measurable business value through decision architecture, Rework Tax measurement, risk control, and scale-or-stop discipline. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condición: new. Paperback. AI Implementation Blind Spots is a practical field manual for leaders, operators, consultants, AI strategists, MSPs, IT teams, cybersecurity professionals, finance teams, healthcare administrators, portfolio operators, and business decision-makers who need AI to work inside real organizations - not just look impressive in demos.Most organizations do not fail with AI because they lack tools. They fail because they confuse speed with value, pilots with proof, adoption with implementation, and output with trusted usable work.This book gives readers a decision-first system for reducing AI rework, defining human-versus-AI boundaries, measuring real ROI, controlling risk, and deciding which AI projects deserve scale - and which should stop.Inside, readers learn how to recognize the Velocity Trap, avoid AI Theater, measure the Rework Tax, build Evidence Packs, design Decision Boundaries, protect against Shadow Ledger risk, and apply practical AI implementation playbooks across revenue, operations, finance, cybersecurity, healthcare administration, procurement, and regulated environments.This is not a prompt guide, vendor brochure, or AI hype book. It is a practical business field manual for turning AI speed into measurable, governed, and trusted results.Paperback ISBN: 979-8-9938806-7-9eBook ISBN: 979-8-9938806-5-5Library of Congress Control Number: 2026912042 A practical field manual for turning AI adoption into measurable business value through decision architecture, Rework Tax measurement, risk control, and scale-or-stop discipline. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.