The Executive Guide to Artificial Intelligence : Cutting Through the Hype - How to get the most from AI in your Organization

This book, now in a thoroughly revised and updated second edition, takes a pragmatic and hype–free approach to explaining artificial intelligence and how it can be utilised by businesses today. At the book’s core is a framework which describes, in nontechnical language, the nine core capabilities of Artificial Intelligence (AI). Each of these capabilities, ranging from image recognition, through prediction, to Generative AI, is explained using real–life examples and how they can be applied in a business environment. The advent of Large Language Models has put AI front and centre of Board discussions. AI has the ability to deliver step–change benefits to organisations and enables forward–thinking business leaders to rethink their business models or create completely new businesses. But most of the real value of AI is hidden behind marketing hyperbole, confusing terminology, inflated expectations and dire warnings of ‘robot overlords’. Any business executive who wants to know how to exploit AI in their business today is left confused and frustrated. As an advisor in AI, Andrew Burgess regularly comes face–to–face with business executives who are struggling to cut through the AI and LLM hype. The knowledge and experience he has gained in advising them has provided him with the skills to help business executives understand what AI is and how they can exploit its many benefits. Through the distilled knowledge included in this book, business leaders will be able to take full advantage of this most disruptive of technologies and create substantial competitive advantage for their companies. Preface Contents About the Author List of Figures 1 Don’t Believe the Hype Introduction Introducing the AI Framework Defining AI A Brief Technology Overview About This Book 2 Why Now? A Brief History of AI The Role of Big Data The Role of Cheap Storage The Role of Faster Processors The Role of Ubiquitous Connectivity What Is Machine Learning? The Barriers to AI Applying AI Conclusion 3 AI Capabilities Framework Introduction 4 Associated Technologies Introduction AI and Cloud AI and Robotics AI and the IoT AI and Crowd Sourcing 5 AI in Action Introduction How AI Is Enhancing Customer Service Chatbots Recommendation Engines Image Recognition How AI Is Optimising Processes Image Recognition Speech Recognition Natural Language Understanding Prediction Optimisation Generative AI How AI Is Generating Insights Clustering Prediction Natural Language Understanding Generative AI 6 Starting an AI Journey Introduction Aligning with Business Strategy Understanding Your AI Ambitions Assessing Your AI Maturity Creating Your AI Heat Map Developing the AI Business Case Understanding Change Management Developing Your AI Roadmap Creating Your AI Strategy 7 AI Prototyping Introduction Build Versus Buy Versus Platform Accessing and Implementing LLMs Creating Your First Build Understanding Data Training 8 What Could Possibly Go Wrong? Introduction The Challenge of Poor Data Understanding the Lack of Transparency The Challenge of Unintended Bias Understanding AI’s Naivety Becoming Over-Dependent on AI Choosing the Wrong Technology Preparing for Malicious Acts Conclusion 9 Industrialising AI Introduction Building a Scalable AI Capability Develop an AI Playbook Beyond the AI Strategy Data Science Vision Data Strategy Technology Strategy Data Ethics Strategy Data Science Training Strategy Data Science Marketing Plan Resourcing an AI Eco-System Strategy Prototyping AI Vendor Implementation RPA and Associated Technologies Vendor Change Management Support Selecting the Right AI Vendor Proof of Capability Proof of Value References Pricing Model Cultural fit Future-proofing Foundation Client Technical Requirements Professional Services Requirements Selecting the Right AI Service Provider Experience People Partnerships and Independence Cultural Fit Approach Pricing Model Knowledge Transfer Recruiting AI Specialists Understand the Role Competitive Compensation Offer Flexibility Growth Opportunities Invest in Tools and Technology Cultivate a Data-Driven Culture Provide Challenging Work Encourage Collaboration Career Pathing Networking Opportunities Building an AI Organisation Ways of Working Centre of Excellence AI Management Data Science Governance Board Data Owners Innovation Lab Opportunity Creation Technology Data Science Platform Data Catalogue 10 Living with AI Introduction The Democratisation of AI AI and Society AI and its Users Data Ethics Data Ethics Framework Data Ethics Forum AI and Business Resources Culture Commitment 11 Where Next for AI? Introduction The Next Opportunities for AI Image Recognition Speech Recognition Natural Language Processing and Natural Language Understanding Clustering and Prediction Optimisation Generative AI Understanding Future-Proofing Your Business Final Thoughts Index