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  • The Business Case for AI

  • A Leader's Guide to AI Strategies, Best Practices & Real-World Applications
  • 著者: Kavita Ganesan
  • ナレーター: Stephanie Richardson
  • 再生時間: 9 時間 11 分

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The Business Case for AI

著者: Kavita Ganesan
ナレーター: Stephanie Richardson
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無料体験終了後は月額¥1,500。いつでも退会できます。

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あらすじ・解説

AI is much more than a sexy marketing gimmick.

At its core, it’s a powerful business tool that can make operations and decision-making more efficient, employees more productive, and customers delighted.

Unfortunately, leaders who want to take advantage of artificial intelligence often don’t know where to start. The process can feel overwhelming—from analyzing existing processes and software systems and choosing where to apply AI automation, to preparing every tier of the organization for the transition.

In this practical guide for business leaders, Kavita Ganesan takes the mystery out of implementing AI, showing you how to launch AI initiatives that get results. With real-world AI examples to spark your own ideas, you’ll learn how to identify high-impact AI opportunities, prepare for AI transitions, and measure your AI performance.

Get ready to discover:

  • What’s true, what’s hype, and what’s realistic to expect from AI and machine learning systems.
  • Ideas for applying AI in your business to increase revenues, optimize decision-making, and eliminate business process inefficiencies.
  • How to spot lucrative AI opportunities in your organization and capitalize on them in creative ways.
  • Three Pillars of AI success, a systematic framework for testing and evaluating the value of AI initiatives.

Simple and compelling, The Business Case for AI gives leaders the information and resources they need without statistics, data science, or technical jargon. Whether you want to jumpstart your AI strategy, manage your AI initiatives for better outcomes, or simply find inspiration for your own AI and machine learning applications, The Business Case for AI is your blueprint for AI success.

©2022 Opinosis Analytics Publishing (P)2023 Opinosis Analytics Publishing

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