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Inhaltsangabe
AI is not blocked by software alone.
For many organizations, the real constraint is hidden beneath the strategy: latency, bandwidth limits, weak upload capacity, poor Wi-Fi design, flat networks, fragile failover, unmanaged vendor escalation, outdated cabling, and last-mile infrastructure that was never designed for AI-driven operations.
The Hidden Tax on AI is a board-ready executive fieldbook for leaders who need to understand why AI investments succeed, stall, or fail inside the real-world enterprise.
This book argues that AI value depends not only on models, software, and automation tools, but on the physical and operational infrastructure underneath them. Connectivity, resiliency, segmentation, cloud performance, power, vendor governance, and site readiness now shape whether companies can actually capture the promise of AI.
Written for CEOs, CIOs, CFOs, COOs, board members, commercial property owners, enterprise IT leaders, facilities teams, and risk executives, this book translates infrastructure into business language: revenue protection, productivity, cybersecurity, customer trust, property value, and expansion readiness.
Inside, readers will find:
- A clear explanation of the hidden infrastructure tax on AI
- Legacy vs. AI-ready infrastructure frameworks
- Executive diagnostics for latency, bandwidth, congestion, and site readiness
- Commercial property and fiber-readiness strategy
- Risk, resilience, cybersecurity, and segmentation guidance
- Industry use cases for healthcare, finance, manufacturing, retail, professional services, public sector, and life sciences
- Board-level dashboards, scorecards, checklists, and decision tools
- A 30 / 60 / 90 / 180-day action roadmap
AI does not float above the enterprise.
It runs through buildings, fiber, power, rooms, routes, devices, vendors, controls, and decisions.
The companies that win will be the ones that govern the infrastructure beneath the intelligence.
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The Hidden Tax on AI: Why Physical Infrastructure Decides Whether Enterprises Win
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Paperback. Zustand: new. Paperback. AI is not blocked by software alone.For many organizations, the real constraint is hidden beneath the strategy: latency, bandwidth limits, weak upload capacity, poor Wi-Fi design, flat networks, fragile failover, unmanaged vendor escalation, outdated cabling, and last-mile infrastructure that was never designed for AI-driven operations.The Hidden Tax on AI is a board-ready executive fieldbook for leaders who need to understand why AI investments succeed, stall, or fail inside the real-world enterprise.This book argues that AI value depends not only on models, software, and automation tools, but on the physical and operational infrastructure underneath them. Connectivity, resiliency, segmentation, cloud performance, power, vendor governance, and site readiness now shape whether companies can actually capture the promise of AI.Written for CEOs, CIOs, CFOs, COOs, board members, commercial property owners, enterprise IT leaders, facilities teams, and risk executives, this book translates infrastructure into business language: revenue protection, productivity, cybersecurity, customer trust, property value, and expansion readiness.Inside, readers will find: A clear explanation of the hidden infrastructure tax on AILegacy vs. AI-ready infrastructure frameworksExecutive diagnostics for latency, bandwidth, congestion, and site readinessCommercial property and fiber-readiness strategyRisk, resilience, cybersecurity, and segmentation guidanceIndustry use cases for healthcare, finance, manufacturing, retail, professional services, public sector, and life sciencesBoard-level dashboards, scorecards, checklists, and decision toolsA 30 / 60 / 90 / 180-day action roadmapAI does not float above the enterprise.It runs through buildings, fiber, power, rooms, routes, devices, vendors, controls, and decisions.The companies that win will be the ones that govern the infrastructure beneath the intelligence. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9798181934924
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