AI and Book Publishing: The Use Cases

Keith Riegert, CEO of Ulysses Press and Perfect Bound, presented at the Publishers Weekly U.S. Book Show in May 2024, offering the most comprehensive overview I’ve seen about AI use cases within publishing companies. Though Perfect Bound is a sponsor of this report, I stand by that statement. Keith offers “20 practical ways you, as a publishing professional, can start using AI right now.”

His presentation, Getting Started with AI, can be viewed and downloaded from the Perfect Bound website.

Software for the automated typesetting of books dates back to at least the 1970s. In the mid-1980s I supervised a software project called PageOne, based on Donald Knuth’s TeX, which could typeset a book in minutes. SGML appeared around the same time, based on a document standard introduced in 1969. It was largely succeeded by XML, introduced in 1996. These robust markup languages create solid structures for automation.

Desktop publishing ushered in another round of automation for QuarkXPress and Adobe InDesign, as well as Adobe Illustrator and Adobe Photoshop. Publishing workflows can be managed with various programs and systems.

An organization to watch is the Coko Foundation. They offer a suite of open source production and publishing management tools, including Kotahi, a scholarly publishing platform, and Ketty for book production, which includes an AI Assistant. The Kotahi AI PDF Designer, “transforms PDF design into a straightforward, interactive process.”

There are some early initiatives to bring AI into InDesign workflows. In April 2024 Adobe announced a Text to Image feature. Third parties may be getting ahead of Adobe here: the innovative prepress and editorial production vendors in India, such as Hurix Digital and Integra, are showing more initiative than Adobe in harnessing AI for production.

The ‘low-hanging fruit’ for AI in marketing seems obvious. Ask Chat AI to help with a product description or a press release. Ask it to suggest some keywords. This it can do, without breaking a sweat. But most publishing professionals can do the same thing, with only a little moisture on the brow.

Keith Riegert’s use cases, linked above, include suggestions for brainstorming titles, drafting a digital marketing report, and creating a digital marketing campaign tracker in Google Sheets.

Shimmr software, described above, hints at the shape of automated marketing to come.

Veristage (a sponsor of this book) supports marketing and sales activities, including helping you define the target audience for a book, and its unique selling points, and can provide auto-generated advertising copy to be used in marketing, email, PR, and social campaigns.

Metadata is core to book discoverability. You’ve heard that enough times to be nauseated by the admonition. It’s off-putting mainly because “metadata” remains elusive to most non-techies. If you say, “it’s just the basic info about the book, the title, description, price, subject categories, that kind of thing,” people exhale. That they’re comfortable with. But that’s about all.

I regret to remind you that there’s actually far more to metadata than just a few details about the book. There’s so much more. Much more than I can encompass in this little book. I’ve co-authored a whole book on the topic. Ingram publishes Metadata Essentials, an excellent short volume. I’ll say it here, and not for the last time: authors and publishers pay short-shrift to their metadata at their peril.

AI can help with metadata generation. For example, self-publishing vendor PublishDrive, offers an “AI-Powered Book Metadata Generator” which offers AI recommendations for the book title, blurb, Amazon categories, BISAC categories, and keywords.

Insight, from Veristage, described above, can generate descriptions, keywords, and define optimal BISAC categories.

With his typical deep wisdom, Graham Bell, EDItEUR’s director, notes that “one reaction to (the controversies surrounding AI) is to forswear use of AI or to avoid trading in AI-created products. A more realistic option is simply to be transparent with trading partners and readers when AI has been used. And as some resellers limit or ban AI-based content from their platforms, it is important for reputable publishers to highlight those products that do use generative AI techniques to create content.”

Bell goes on to outline ways that publishers can specify in metadata:

• AI contributors

• AI-based voices in audiobooks

… as well as a method to indicate in the metadata for digital products that the publisher explicitly opt outs of text and data mining (TDM) for uses other than research. There’s also a way to specify a separate license covering commercial TDM.

As is often that case, what is specified in ONIX may not be uncovered down the food chain, but at least a best effort has been made.