The AI and data revolution : understanding the new data landscape / Martin De Saulles.

Format:

Book

Author/Creator:

De Saulles, Martin, author.

Language:

English

Subjects (All):

Artificial intelligence.

Information technology--Management.

Information technology.

Physical Description:

1 online resource (xviii, 170 pages) : digital, PDF file(s).

Edition:

First edition.

Place of Publication:

London : Facet, 2025.

Summary:

We are entering a new phase in the information revolution driven by the introduction of innovative artificial intelligence (AI) technologies. From the rise of mass media, mass communications and the expansion of the internet, to mobile computing, social networks and Generative AI, this important and authoritative book outlines the key changes over the last thirty years that have led to this moment.<br><br>Drawing on established frameworks, theories, historical research and empirical evidence, this book argues that the current wave of AI-driven innovations represents a step-change in how organisations can extract value from data and that this will have significant implications for business innovation and how companies compete. Individual chapters explore (a) the history of the information industry and key milestones in artificial intelligence, (b) an overview of the data and AI landscape, (c) the opportunities and challenges of the AI revolution, (d) the ethical, policy and legal issues of data-driven AI, (e) and scenarios for where the data revolution is heading up to 2030.

Contents:

Endorsements

Title page

Contents

About the Author

Introduction

CHAPTER 1 How Did We Get Here?

A brief history of the information industry

The role of technology

Data-driven innovation

A brief history of AI

CHAPTER 2 The Current AI and Data Landscape

How much data is there?

Sources of data

Case study 2.1 - The London Datastore

How data is used

Changing business models

Case study 2.2 - Strava

Case study 2.3 - Harbr

The AI landscape

CHAPTER 3 The Emerging Data-Driven AI Revolution

AI opportunities

Case study 3.1 - SinglePoint

Case study 3.2 - WPP Open

Case study 3.3 - The NHS AI Lab

Case study 3.4 - A&amp

O Shearman

AI challenges

Prompt engineers: the new librarians?

CHAPTER 4 Ethical, Policy and Legal Issues of Data-Driven AI

Ethical concerns

AI and data policies

AI and data legislation

CHAPTER 5 Looking Ahead

Predicting the future

Social and economic implications of the AI and data revolution

Data and AI technologies to 2030

AI in the real world to 2030

The regulatory and commercial environment to 2030

CHAPTER 6 Pulling the Threads Together

References

Index.

Notes:

Title from publisher's bibliographic system (viewed on 22 Aug 2025).

Includes bibliographical references and index.

ISBN:

1-78330-710-2

1-78330-711-0