Business and Economics

Technology

Artificial Intelligence for Business Strategy

By Theo Riven

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Length3h 10m

About this audiobook

Artificial intelligence is no longer just a technical tool—it is now a business advantage. Artificial Intelligence for Business Strategy gives leaders, entrepreneurs, managers, consultants, and professionals a practical guide to understanding and applying AI for growth, innovation, productivity, and long-term competitiveness. This book explains how AI is reshaping industries, transforming decision-making, improving operations, personalizing customer experiences, and creating new business models. Readers will learn how to assess AI readiness, identify high-value use cases, build an AI strategy, manage risks, measure ROI, and lead responsible AI adoption. Written in clear, accessible language, this guide is ideal for business readers who want to move beyond AI hype and develop a practical roadmap for using artificial intelligence as a strategic advantage.

Artificial Intelligence Futuristic

Audiobook details

GenreBusiness and Economics, Technology

Length3 hrs 10 mins

Narrated byListen with 1,000+ voices

FormateBook with Audio

Publish dateJun 12, 2026

LanguageEnglish

1Chapter 1: The AI Revolution in Business – Why Every Leader Needs a Strategy Now

2Defining AI's Role in Modern Business

3Key Trends and Statistics for 2025 and Beyond

4How AI Is Reshaping Industries: Successes, Failures, and Lessons

5Exploring the Economic Impact of AI Adoption

Show all chapters

6Assessing Your Organization's AI Readiness

7Summary of Key Takeaways

8Exercises and Challenges

9Chapter 2: Demystifying AI Fundamentals – Building a Strong Foundation for Beginners

10Core Concepts: What AI Really Is, Explained Simply

11Types of AI: Narrow vs. General, and Supervised vs. Unsupervised Learning

12Essential Terminology and Tools: Your AI Vocabulary and Starter Kit

13Neural Networks: From Basics to "Under the Hood" Peek

14Real-World Applications: Fundamentals in Action

15Simple Starter Projects: Hands-On Experiments

16Project 1: Supervised Learning – Predict Flower Species (Iris Dataset)

17Project 2: Unsupervised Learning – Customer Clustering

18Project 3: Neural Network Basics – Simple Image Classifier Teaser

19Summary of Key Takeaways

20Exercises and Challenges

21Chapter 3: Crafting Your AI Vision – Aligning Technology with Business Goals

22Core Concepts: Building Blocks of an AI Vision

23Conducting an AI SWOT Analysis: Mapping Your Landscape

24Setting Measurable AI Objectives: From Vision to Metrics

25Engaging Teams and Executives: Turning Vision into Shared Momentum

26Integrating It All: Your High-Level AI Roadmap Template

27Summary of Key Takeaways

28Exercises and Challenges

29Chapter 4: Spotting AI Opportunities – Auditing Your Business for Transformation

30Core Concepts: What an AI Audit Is and Why It Matters

31Step-by-Step Guide: Mapping AI Potential Across Departments

32Marketing Department Checklist

33Operations Department Checklist

34Finance Department Checklist

35Industry-Specific AI Use Cases: Inspiration from Peers

36Prioritizing Projects: Based on ROI Potential

37Overcoming Common Barriers to Adoption

38Summary of Key Takeaways

39Exercises and Challenges

40Chapter 5: Data: The Fuel for AI Success – Strategies for Collection and Preparation

41Core Concepts: Data Fundamentals Explained Simply

42Building a Data Governance Framework: Rules for Sustainable Fuel

43Privacy and Compliance Basics: Guardrails for Ethical Data

44Hands-On Data Prep Tutorials: Free Platforms for Non-Techies

45Tutorial 1: Sourcing and Basic Cleaning in Google Sheets (No-Code)

46Tutorial 2: Structuring and Governance in Airtable (Visual Database)

47Tutorial 3: Advanced Prep in Google Colab (Light Code for Scaling)

48Summary of Key Takeaways

49Exercises and Challenges

50Chapter 6: Selecting and Deploying AI Solutions – From Off-the-Shelf to Custom Builds

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