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{ "item_title" : "Leading the Intelligent Enterprise", "item_author" : [" Nancy B. Amert "], "item_description" : "AI promises productivity. Executives must deliver profit.Across large and mid-sized organizations, AI pilots are multiplying. Yet many business cases count labor savings before the work has been redesigned-and ignore the full cost of models, cloud or on-premises infrastructure, data readiness, cybersecurity, integration, governance, adoption, and operating change. The result is activity without enterprise value.Leading the Intelligent Enterprise gives senior leaders a practical framework for making the decisions that determine whether AI becomes an expensive experiment or a durable operating advantage.Inside, you will learn how to: Expose the complete AI P&L-not merely the model or software price.Convert time saved into margin, growth, service, resilience, or strategic capacity.Redesign work and labor economics without confusing technical potential with bankable savings.Unify risk, IT, data, cybersecurity, finance, workforce, and AI under one transformation system.Choose among cloud, hybrid, private, and on-premises AI architectures with financial and risk discipline.Build governance that accelerates responsible scale instead of becoming a late-stage approval barrier.Fund what earns the right to scale-and stop initiatives that cannot prove value.Written for CEOs, board members, CFOs, CIOs, CHROs, business-unit leaders, risk executives, and transformation leaders, this handbook connects technology choices to the income statement, workforce, and enterprise operating model.The central message is direct: AI does not produce profit by itself. Leadership does.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/9/79/819/051/9798190511932_b.jpg", "price_data" : { "retail_price" : "24.99", "online_price" : "24.99", "our_price" : "24.99", "club_price" : "24.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Leading the Intelligent Enterprise|Nancy B. Amert

Leading the Intelligent Enterprise : How Executives Can Fund AI, Redesign Work, Govern Risk, and Turn Productivity into Profit

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Overview

AI promises productivity. Executives must deliver profit.

Across large and mid-sized organizations, AI pilots are multiplying. Yet many business cases count labor savings before the work has been redesigned-and ignore the full cost of models, cloud or on-premises infrastructure, data readiness, cybersecurity, integration, governance, adoption, and operating change. The result is activity without enterprise value.

Leading the Intelligent Enterprise gives senior leaders a practical framework for making the decisions that determine whether AI becomes an expensive experiment or a durable operating advantage.

Inside, you will learn how to:

  • Expose the complete AI P&L-not merely the model or software price.
  • Convert time saved into margin, growth, service, resilience, or strategic capacity.
  • Redesign work and labor economics without confusing technical potential with bankable savings.
  • Unify risk, IT, data, cybersecurity, finance, workforce, and AI under one transformation system.
  • Choose among cloud, hybrid, private, and on-premises AI architectures with financial and risk discipline.
  • Build governance that accelerates responsible scale instead of becoming a late-stage approval barrier.
  • Fund what earns the right to scale-and stop initiatives that cannot prove value.

Written for CEOs, board members, CFOs, CIOs, CHROs, business-unit leaders, risk executives, and transformation leaders, this handbook connects technology choices to the income statement, workforce, and enterprise operating model.

The central message is direct: AI does not produce profit by itself. Leadership does.

This item is Non-Returnable

Details

  • ISBN-13: 9798190511932
  • ISBN-10: 9798190511932
  • Publisher: Independently Published
  • Publish Date: August 2026
  • Dimensions: 9 x 6 x 0.74 inches
  • Shipping Weight: 0.8 pounds
  • Page Count: 298

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