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(EPUB) eBook The Secrets of AI Value Creation A Practical Guide to Business Value Creation with Artificial Intelligence from Strategy to Execution 1st Edition By Michael Proksch , Nis

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Document details

Pages: 179
File size: 7.4 MB
Format: Digital PDF
Course: Artificial Intelligence
Category: eBook[PDF]

About this ebook

The Secrets of AI Value Creation: A Practical Guide to Business Value Creation with Artificial Intelligence from Strategy to Execution is a comprehensive business framework book published by Wiley. Co-authored by Michael Proksch, PhD, Nisha Paliwal, and Wilhelm Bielert, PhD, the text outlines how organizations can transition AI initiatives from speculative hype to tangible corporate value. [1, 2, 3]

The book's framework explores AI integration across five key perspectives—business, technology, data, algorithmics, and psychology—and organizes these concepts into four parts and 14 distinct chapters: [1, 2]

Part I: Value Creation Potential

The Journey of AI Achievers: Examining strategies used by organizations that have successfully generated business growth via AI.
Three Factors of AI Business Value Creation: Unpacking the foundational requirements needed to catalyze ROI.
Four Types of AI Value Creation: Analyzing different value models, including optimization, augmentation, automation, and AI-driven products or services. [1, 2, 3]

Part II: Overcoming Value Challenges

AI-Centric Elements: Mapping out the unique components needed to sustain an AI architecture.
Collecting Valuable Data: Shifting focus from merely acquiring massive data volumes to gathering targeted, high-utility assets.
Creating Actionable Insights: Designing analytical systems that reliably inform executive and operational decisions.
Building Stakeholder Trust: Navigating user adoption by addressing security, transparency, and ethics.
Managing AI's Decision-Making: Developing transparent, explainable frameworks to monitor automated outputs. [1, 2, 3]

Part III: Enterprise Integration

Crafting an AI Strategy: Building long-term roadmaps aligned with broader corporate financial objectives.
Leading Successful Projects: Structuring project management methodologies specific to the iterative nature of machine learning.
Cultivating an AI-Friendly Culture: Preparing human talent, overcoming organizational friction, and fostering cross-departmental collaboration. [1, 2, 3]

Part IV: Required Capabilities

Technology: Scaling infrastructure and computing resources to handle enterprise workloads.
Data Management: Implementing data governance protocols to safeguard information quality and availability.
Talent: Training, recruiting, and structuring teams composed of domain experts, engineers, and change leaders. [1, 2, 3]