Sinopsis
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: 979-8-9938806-7-9
eBook ISBN: 979-8-9938806-5-5
Library of Congress Control Number: 2026912042
"Sinopsis" puede pertenecer a otra edición de este libro.
Acerca del autor
Nikolay Gul is an author, AI strategist, and business technology practitioner focused on practical AI implementation, cybersecurity decision-making, marketing strategy, and operational clarity. He writes for leaders, operators, consultants, MSPs, IT teams, cybersecurity professionals, finance teams, and business decision-makers who need technology to work inside real organizations, not only in demos.Through Future-Proof Marketing Press, he develops practical business books, implementation frameworks, and companion resources that translate complex AI and cybersecurity topics into usable decision systems. His work emphasizes clear ownership, measurable value, risk control, workflow discipline, and human judgment in technology adoption.
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AI Implementation Blind Spots (Paperback)
Impresión bajo demandaLibrería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
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. Nº de ref. del artículo: 9798993880679
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AI Implementation Blind Spots (Paperback)
Impresión bajo demandaLibrería: CitiRetail, Stevenage, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
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. Nº de ref. del artículo: 9798993880679
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