Using AI in Marketing: An Introduction (2024)

Table of Contents

  1. Overview
  2. Publication details
  3. Summary
  4. Key concepts and frameworks
  5. Who it's for
  6. Edition history
  7. How this book compares
  8. Related podcast episodes
  9. FAQs
  10. Related Terms
  11. Related Books
  12. Sources

Overview

Using AI in Marketing: An Introduction is a 2024 book by Greg Kihlström, published by Mercury Learning and Information Systems, an imprint of De Gruyter Brill, that gives marketers a short, non-technical grounding in what artificial intelligence does inside a marketing function and where to apply it first. It is written for marketing professionals with no AI background, and at 136 pages it’s the shortest of Kihlström’s De Gruyter Brill-line titles. The book is organized in four parts: AI fundamentals, four growth areas for marketing (generative AI, personalization, workflow augmentation, and analytics), practical examples including prompt writing, and a closing section on adoption, investment, and the challenges of AI. A second edition is planned for 2027.

See also: Generative AI · Prompt Engineering · Large Language Models (LLM) · Predictive Analytics

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Publication details

FieldDetail
Full titleUsing AI in Marketing: An Introduction
AuthorGreg Kihlström
ForewordYes (p. xvii); author not identified in available sources — see editorial notes
SeriesMLI Generative AI Series (per Google Books listing)
PublisherMercury Learning and Information Systems, an imprint of De Gruyter Brill
Publication dateJuly 22, 2024
EditionFirst; second edition announced for 2027
FormatsPaperback, ebook (PDF and EPUB)
ISBN978-1-5015-2279-6 (paperback); 978-1-5015-1976-5 (PDF ebook, the DOI ISBN); 978-1-5015-1978-9 (EPUB)
DOI10.1515/9781501519765
Length136 pages (index begins at page 131)
Where to buyDe Gruyter Brill, Agile Brand Guide product page, Amazon, Google Books
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Summary

The book is an introduction in the plain sense. It doesn’t argue a thesis about AI so much as give a marketer enough vocabulary and enough examples to make a first investment decision without being led by a vendor. Written in late 2023 and early 2024, it lands in the period after ChatGPT’s release when most marketing teams had tried generative tools informally but few had a plan for them.

Part I, Exploring AI and Marketing, is three short chapters: a history of AI, an explanation of how AI and marketing fit together (machine learning, natural language processing, generative models), and a survey of how marketers were already using AI at the time of writing, often inside existing platforms without calling it that.

Part II, Growth Areas for Marketing and AI, is the core of the book and names four areas. Generative AI gets the longest chapter in the book at roughly 24 pages, covering text, image, and video generation for content at scale. The other three are personalized customer experience, team and workflow augmentation, and data analysis, measurement, and optimization. Each chapter describes the use case, the kinds of tools involved, and what has to be true in the organization for it to work.

Part III, Practical Examples, is hands-on. Chapter 8 is about writing better prompts. Chapter 9 is a set of generative AI cases and examples that runs close to 30 pages, the second-longest section in the book.

Part IV, Integration and Optimization, is where the book becomes a management text. Chapter 10 describes an AI adoption mindset, chapter 11 covers how AI changes a team’s overall approach to marketing, chapter 12 is about when and where to invest, and chapter 13 lists the challenges: accuracy, bias, data privacy, and the organizational friction of changing how work gets done. The book ends with a short epilogue.

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Key concepts and frameworks

Four growth areas. Kihlström’s grouping of marketing AI use cases: generative AI, personalized customer experience, team and workflow augmentation, and data analysis/measurement/optimization. The structure of Part II, and a useful taxonomy for scoping an AI roadmap.

The AI adoption mindset. Chapter 10’s description of the attitudes and habits that separate teams that get value from AI from teams that run pilots indefinitely. Kihlström develops the idea further in AI Isn’t a Goal (or a Strategy) (2025) and Stop Saying “AI” (2026).

Prompt writing for marketers. Chapter 8’s practical guidance; the Martechipedia Prompt Engineering entry covers the same ground as a reference.

When and where to invest. Chapter 12’s criteria for choosing a first AI investment, favoring areas where the team already has data and a measurable process.

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Who it’s for

A marketing manager who has been asked to “do something with AI” and needs to understand the options before talking to vendors. A CMO who wants a short read before an AI budget discussion. A marketing team lead planning an internal training session, since the four-part structure maps cleanly onto a workshop agenda. It is also suited to undergraduate or professional-education courses as a primer.

It is not a technical book and doesn’t cover model architecture, and it predates the agentic AI wave that Kihlström takes up in MarketingOps 3.0 (2026).

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Edition history

EditionYearPublisherNotes
Using AI in Marketing: An Introduction2024Mercury Learning and Information Systems / De Gruyter BrillFirst edition.
Second edition2027 (announced)De Gruyter BrillAnnounced on the author’s site; details not yet published.

Predecessor titles, not editions of this book:

TitleYearPublisherRelationship
The Agile Brand Guide to Marketing & AI2023The Agile BrandShort guide; presumed out of print. Covered similar ground at shorter length.
The Agile Brand Guide: Generative AI2023The Agile BrandShort guide on generative AI specifically; still in print. Overlaps with Part II, chapter 4.
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How this book compares

TitleAuthorYearFocusBest suited for
Using AI in Marketing: An IntroductionGreg Kihlström2024Primer on AI use cases and adoption for marketersFirst-time readers on the subject
The Agile Brand Guide: Generative AIGreg Kihlström2023Generative AI for content at scaleTeams focused on content production
AI Isn’t a Goal (or a Strategy)Greg Kihlström2025Why AI adoption fails when AI is the objectiveLeaders setting AI strategy
MarketingOps 3.0Greg Kihlström2026Operating model for agent-mediated marketingLeaders past the adoption stage
Marketing Artificial IntelligencePaul Roetzer and Mike Kaput2022AI strategy and the Marketing AI Institute’s frameworkLeaders wanting a strategic survey
The AI Marketing CanvasRaj Venkatesan and Jim Lecinski2021Five-stage AI adoption modelTeams planning a phased rollout
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FAQs

Is this a technical book? No. It explains concepts like machine learning and generative AI at the level a marketer needs to make decisions, not to build anything.

What are the four growth areas? Generative AI, personalized customer experience, team and workflow augmentation, and data analysis, measurement, and optimization.

Does it cover prompt writing? Yes. Chapter 8 is about improving prompt writing, and chapter 9 gives generative AI cases and examples.

How long is it? 136 pages, 13 chapters in four parts. It’s the shortest of Kihlström’s De Gruyter Brill-line books.

Is there a second edition? One has been announced for 2027. Details beyond the year haven’t been published.

Does it cover AI agents or agentic AI? Not in depth. It was written in 2023–2024, before agentic systems became a mainstream topic. Kihlström’s MarketingOps 3.0 (2026) covers that.

Who wrote the foreword? The book includes a foreword, but the available publisher and retailer pages don’t name its author.

How does it relate to The Agile Brand Guide: Generative AI? That 2023 guide covers one of this book’s four growth areas in more depth. This book is the broader introduction.

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  1. Generative AI
  2. Large Language Models (LLM)
  3. Prompt Engineering
  4. Machine Learning (ML)
  5. Predictive Analytics
  6. Omnichannel Personalization
  7. Technology Adoption Model (TAM)
  8. AI Governance Board (AIGB)
  9. Agentic AI
  10. Next Best Action
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  • The Agile Brand Guide: Generative AI (2023) — wiki entry pending
  • AI Isn’t a Goal (or a Strategy) (2025) — wiki entry pending
  • Stop Saying “AI” (2026) — wiki entry pending
  • MarketingOps 3.0 (2026) — entry drafted November 2026
  • Marketing Technology Platforms (2025) — entry drafted November 2026
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Sources

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