OpenAI's Deep Research on AI & Book Publishing

The frontier model takes a look at our field.

I asked OpenAI’s Deep Research tool to compile a detailed report on the current and future applications of large language models (LLMs) in book publishing:

“… focusing on research from the last five years while including landmark studies. The report will balance theoretical foundations and practical implications, with more emphasis on practical applications. It also provide a comparative analysis of traditional vs. AI-assisted workflows as an appendix, address ethical considerations concisely, and assume AI adoption will continue. Writing, editing, and reading applications will be examined in greater depth, and major publishing houses will be discussed while incorporating insights from independent publishers.”

Deep Research is only available via ChatGPT Pro, which costs $200/month, so it remains to be seen whether I will keep the subscription. My gut reaction to the following is that it is detailed and thorough, but

the voice is boring, so it’s not a plug-and-play replacement for anything except a B+ graduate student.

I’ve marked a few places where I definitely disagree with the word choices using strikethrough. Since this was kind of pricey, I am putting about 2/3 of it behind the paywall. If you are interested in deeper dives on particular topics, let me know.

Best,

Fred

AI in Book Publishing: Current and Future Applications

[A Report by OpenAI’s Deep Research]

Introduction

Artificial intelligence has steadily infiltrated book publishing over the past decade, but the recent advent of large language models (LLMs) has accelerated its impact. These AI systems, especially generative models like OpenAI’s GPT series, can produce human-like text, images, and even speech, creating both excitement and anxiety in the industry. In late 2022, OpenAI’s ChatGPT brought AI text generation to a massive user base virtually overnight – reaching 100 million users in two months (How Publishers Can Navigate the AI Revolution) – and prompting publishers to confront questions about AI’s role in their workflows. AI is not entirely new to publishing; for years, publishers and authors have used “invisible” AI in everyday tools (from spell-check to email filters). As one analyst noted, “for an author or editor to say ‘I don’t want AI used on my manuscript’ is...all but impossible, unless both they and their editors work with typewriters and pencils” (How Publishers Can Navigate the AI Revolution). But today’s generative AI goes beyond background assistance, offering capabilities to write, edit, illustrate, and market books in ways that were previously unimaginable.

This report provides an overview of current and emerging applications of LLM-driven AI in book publishing, balancing theoretical underpinnings with practical implications. We survey how AI is being applied at each stage of the publishing process – from writing and editing to cover art, marketing, and publicity – and analyze key developments in these areas. The focus is on the last five years, when breakthroughs in machine learning and transformers revolutionized AI’s creative potential (Is AI the Bitter End—or the Lucrative Future—of Book Publishing?), though we also note earlier landmark moments. Perspectives from major publishing houses (the “Big Five” and others) are included alongside insights from independent publishers and self-publishing authors. We address ethical considerations (such as intellectual property and authenticity) with the assumption that AI adoption will continue, prompting the need for responsible strategies rather than outright avoidance. Finally, an appendix offers a comparative look at traditional vs. AI-assisted publishing workflows.

Overview of AI Applications in Book Publishing

AI technologies are now touching almost every aspect of book publishing. Below is a brief overview of how different stages and tasks in the publishing process are leveraging AI:

• Content Creation (Writing) – Generative text models assist authors in drafting prose, developing story ideas, or even writing complete novels. AI can also generate poetry, non-fiction content, or dialogue, serving as a “co-author” or brainstorming partner. (Discussed in detail in the next section.)

• Editing and Proofreading – AI-driven editing tools check grammar and style, suggest rewrites, and summarize manuscripts. More advanced LLM-based systems can analyze a book’s structure or flag inconsistencies, supporting human editors in both copyediting and developmental editing tasks. (Discussed later.)

• Illustration and Cover Art – Image generation models create artwork for book covers and illustrations. AI can produce concept art or final images in various styles, offering a faster and cheaper alternative to human artists – though not without controversy in the artistic community.

• Production and Formatting – AI assists in layout design, typesetting, indexing, and even automated audiobook narration. For instance, text-to-speech AI can produce human-sounding audiobook recordings, and neural machine translation can help translate books into multiple languages more efficiently (ChatGPT and Publishing: 3 Ways Publishers Are Responding to AI — Alyssa Matesic | Professional Book and Novel Editing) (ChatGPT and Publishing: 3 Ways Publishers Are Responding to AI — Alyssa Matesic | Professional Book and Novel Editing).

• Marketing and Publicity – AI tools generate marketing copy (like book descriptions, ad slogans, and social media posts) and optimize advertising campaigns. Machine learning algorithms also help target the right audience for a book and analyze reader data. Some publishers use AI to generate press releases or personalize outreach to media and readers.

• Distribution and Reader Experience (Reading) – AI recommendation systems suggest books to readers based on their preferences (a long-standing use of machine learning on platforms like Amazon since 1998) [I added this link.—Ed.] LLMs create new reader experiences, such as interactive story chatbots or personalized content. AI narration allows readers to listen to books in synthetic voices. Additionally, readers themselves are using AI (e.g. ChatGPT) as “reading companions” to summarize or discuss books, which could influence how content is consumed.

In the following sections, we delve deeper into the most critical areas – writing, editing, and reading – with emphasis on recent developments. We also examine how illustration, marketing, and other functions are evolving. Throughout, practical examples are highlighted, drawing on both industry experiments and user (reader/author) feedback.

AI in Writing and Content Creation

LLMs as Co-authors: Text Generation in Practice

One of the most headline-grabbing uses of AI in publishing is automated writing. Modern LLMs can generate fluent text on virtually any topic or in any genre, raising the prospect of AI-authored books. In the past five years, progress has been swift: transformer-based models introduced around 2017 culminated in OpenAI’s GPT-3 (2020), a landmark capable of producing long-form text that often reads plausibly human (Is AI the Bitter End—or the Lucrative Future—of Book Publishing?). By 2022–2023, GPT-3.5/4 (accessible via ChatGPT) made such capabilities widely available, and authors – especially in the self-publishing community – began experimenting with AI-generated prose.

Self-publishing boom: The result was a mini-boom of AI-written e-books. By February 2023, Amazon’s Kindle store already listed over 200 titles with ChatGPT as an author or co-author, spanning how-to guides, fiction, and poetry (Focus: ChatGPT launches boom in AI-written e-books on Amazon | Reuters). The true number of AI-written books is likely higher, since many authors do not disclose AI involvement (Focus: ChatGPT launches boom in AI-written e-books on Amazon | Reuters). On YouTube and TikTok, tutorials exploded with tips on “how to write a book in hours” using ChatGPT (Focus: ChatGPT launches boom in AI-written e-books on Amazon | Reuters). For example, one self-published author demonstrated creating a 119-page science-fiction novella in less than a day with AI assistance – and suggested it was feasible to crank out “300 such books a year” this way (Focus: ChatGPT launches boom in AI-written e-books on Amazon | Reuters). Another notable case was a tech worker who used ChatGPT to write a children’s story and Midjourney (an AI image generator) to illustrate it; he self-published the 72-page book in just 72 hours in late 2022 (ChatGPT, Midjourney Helped a Man Write a Children's Book in 72 Hours - Business Insider) (ChatGPT, Midjourney Helped a Man Write a Children's Book in 72 Hours - Business Insider). These cases illustrate the speed and scale advantages of AI: a single individual can produce content in days that would normally take months. Enthusiasts argue this efficiency could enable more stories to be told and empower writers who lack resources (the children’s book above was created with essentially zero upfront cost aside from an AI subscription (ChatGPT, Midjourney Helped a Man Write a Children's Book in 72 Hours - Business Insider)).

Quality and originality issues: However, the rush of AI-generated books has sparked serious concerns about quality and originality. Seasoned editors and agents generally find current AI-written manuscripts subpar. The consensus in the traditional industry is that “content generated by AI is not up to par... lacking the depth and nuance that a human writer brings” (ChatGPT and Publishing: 3 Ways Publishers Are Responding to AI — Alyssa Matesic | Professional Book and Novel Editing). AI text often reads formulaic, and longer pieces may become incoherent or “soulless,” as one editor observed (Write On! Features: Writers & Editors, Do Not Despair! AI And The Future Of Writing, Editing, And Publishing by Dan Cross – Pen To Print). Early experiments confirmed these limitations: the tech news site CNET tried using AI to write financial articles in 2022, but had to issue corrections for numerous errors and even instances of apparent plagiarism, before suspending the attempt (Focus: ChatGPT launches boom in AI-written e-books on Amazon | Reuters). For fiction, AI’s tendency to “hallucinate” or make things up can result in inconsistent plots or nonsensical twists. Writer Dan Cross notes that current LLMs “forget entire plot points and characters, create consistency issues, and...generate...boring and unreadable books” when pushed to novel lengths (Write On! Features: Writers & Editors, Do Not Despair! AI And The Future Of Writing, Editing, And Publishing by Dan Cross – Pen To Print). Thus, while AI can generate text quickly, human authors still need to inject creativity, emotional depth, and careful editing to produce a truly compelling book. As a result, many professional publishers have been rejecting AI-authored submissions. Literary agents and magazine editors now often stipulate they are “not interested in considering any material generated by AI” (ChatGPT and Publishing: 3 Ways Publishers Are Responding to AI — Alyssa Matesic | Professional Book and Novel Editing), due both to ethical stance and the telltale mediocre quality.

AI as a writing assistant: More promising, then, is using LLMs as assistive tools rather than autonomous authors. Many writers are exploring ChatGPT or specialized tools (e.g. Sudowrite, NovelAI) to help with brainstorming, overcoming writer’s block, or drafting specific passages. An author might prompt the AI for “five plot ideas involving time travel” or “suggest some descriptions of a medieval marketplace,” and use those as creative springboards. These models can also mimic various writing styles, which some authors find useful for experimentation. For instance, novelist Jane Friedman reported that ChatGPT can be surprisingly helpful in generating “comparable titles” (comp titles) for book proposals – a task that requires scanning the market for similar books (ChatGPT and Publishing: 3 Ways Publishers Are Responding to AI — Alyssa Matesic | Professional Book and Novel Editing). (She cautions that the AI may hallucinate books that don’t exist, so any suggestions must be vetted (ChatGPT and Publishing: 3 Ways Publishers Are Responding to AI — Alyssa Matesic | Professional Book and Novel Editing).) In nonfiction, authors use AI to summarize research or suggest ways to explain complex concepts in simpler terms. An editor at a major house noted you can “ask ChatGPT to explain a concept like developmental editing... then craft an explanation a 12-year-old could understand”, highlighting how AI can adapt content to different reading levels (How Publishers Can Navigate the AI Revolution). These assistive uses show real productivity gains: AI can augment the writing process by handling routine or repetitive tasks (like rephrasing sentences, checking facts, translating snippets, generating metadata) and even spurring human creativity with its off-the-cuff suggestions. Many in the industry predict that AI “will soon become for writers what Photoshop is for visual artists: an accepted tool of the trade”, integrated into the creative process without replacing the artist (Is AI the Bitter End—or the Lucrative Future—of Book Publishing?).

Despite these assistive benefits, professional authors remain cautious. There is a fine line between help and cheating, and literary culture still prizes originality and human voice. The Authors Guild (a prominent U.S. writers’ organization) advises writers to use AI carefully and advocates for transparency in its use. It’s telling that nearly 90% of writers believe authors should be compensated if their work is used to train AI (per a May 2023 Authors Guild survey) (How Publishers Can Navigate the AI Revolution), reflecting widespread concern about AI “borrowing” from human-written texts. Ethically minded authors worry that over-reliance on AI could lead to homogenized, derivative stories (Write On! Features: Writers & Editors, Do Not Despair! AI And The Future Of Writing, Editing, And Publishing by Dan Cross – Pen To Print). In short, AI text generation is a powerful tool and its use in writing is growing, but the human author’s role as visionary and craftsman remains paramount. No major publisher has yet announced plans to have AI write books outright (Is AI the Bitter End—or the Lucrative Future—of Book Publishing?); instead, the trajectory points toward AI-assisted human writing as the model for the foreseeable future.

AI-Generated Illustration and Cover Art

Text isn’t the only creative output of LLM-based technologies. Generative image models (such as DALL·E 2, Midjourney, and Stable Diffusion) have opened up new possibilities for book illustration and cover design. These tools, introduced around 2021–2022, are trained on vast datasets of images and can create original pictures from text prompts. For authors and publishers, this means cover art or interior illustrations can be produced in minutes by simply describing the desired image.

Rapid adoption by indie authors: Independent authors, in particular, have eagerly adopted AI image generators to create visuals for their books. Commissioning a professional illustrator or photographer can be costly and time-consuming, so AI offers an attractive shortcut. As noted, in the case of “Alice and Sparkle,” Ammaar Reshi’s AI-created children’s book, the author had no illustration experience but was able to produce all the artwork through Midjourney within a weekend (ChatGPT, Midjourney Helped a Man Write a Children's Book in 72 Hours - Business Insider). Illustrated children’s books have become a popular target for AI generation because they require many images; indeed, observers have noted that “illustrated children’s books are a favorite for [AI] first-time authors” on self-publishing platforms (Focus: ChatGPT launches boom in AI-written e-books on Amazon | Reuters). By 2023, social media was rife with examples of self-publishers showing off AI-generated book covers or graphic novel panels. These images often emulate popular art styles – from lush fantasy landscapes to anime characters – giving authors with limited budgets a way to make their books visually appealing. Some niche publishers have also used AI for concept art to pitch projects or to visualize characters for marketing materials.

Controversies and pushback: The use of AI art in publishing has generated significant controversy, especially among professional artists and discerning readers. The core issues are authenticity and intellectual property. AI models have been trained on millions of images (including artwork by real artists, scraped without permission), so when an AI produces a “new” illustration, it is remixing patterns learned from human-created art. Illustrators argue this is a form of plagiarism or theft, and they object to their styles being mimicked by algorithms that they never consented to train (Is AI the Bitter End—or the Lucrative Future—of Book Publishing?) (Is AI the Bitter End—or the Lucrative Future—of Book Publishing?). These concerns came to a head in late 2022 and 2023, when a few high-profile incidents of AI-generated cover art were met with public backlash. For example, in 2023, Tor Books (a major science fiction imprint) was criticized for