In the first part of this series, we explored how AI is reshaping textbook publishing from within as it transforms structure, authorship and personalization. But this story does not end with creation. As AI is inserted into more stages of the publishing process, it is also reshaping how textbooks are governed, monetized and sustained. Beyond the technology, let’s look at questions that touch on ownership, ethics and the evolving nature of the textbook itself.
Rights, ethics and the battle over data
The insertion of AI into content production introduces new layers of legal and ethical complexity. The publishers have built their value on intellectual property: the authority and protection attached to curated, peer-reviewed material. But AI blurs the line between source and synthesis. If an algorithm generates a passage of text based on thousands of pre-existing works, who owns the output? The publisher who commissioned it, the developer of the model or the authors whose material informed the algorithm’s training?
Textbook publishers face these questions directly. Some have tightened contractual language to protect their archives from unauthorized AI training, as others are negotiating controlled licensing deals to allow selective use. The outcome of these conversations will determine how future textbooks will be priced, updated and distributed.
Along with ownership there is another concern: that of privacy. AI systems often depend on data drawn from how students use digital materials by noting what they struggle with, how long they spend or which concepts prompt review. When used responsibly, that data can make learning profoundly adaptive and effective, but it must be handled with care and transparency. In answer to this, many publishers are adopting internal audit mechanisms to monitor how this data is stored and applied with an emphasis on earning and maintaining the trust of their users.
From editions to ecosystems
The traditional publisher’s model relied on distinct editions updated and released every few years. AI sidesteps that rhythm by making continuous updates efficient and affordable. When errors can be corrected instantly and examples refreshed with new data, waiting for a new edition seems rather out of step with current capabilities. These capabilities enable “ecosystem publishing:” dynamic collections of content modules, assessments, and interactive elements connected through shared databases. AI flags inconsistencies, updates terminology and suggests revisions and the textbook becomes a connected platform –a system– rather than a single object.
Economically, this new system supports subscription and institutional access models. Schools pay for continuous access to up-to-date materials, as students benefit from content that evolves with them as they learn. Smaller publishers can also participate, using scalable cloud-based AI tools to automate editing, tagging and version control without increasing headcount.
Challenges and cautions
But a note of caution: as has been well documented, AI-generated content can introduce factual inaccuracies or stylistic inconsistencies if unchecked. And bias within training data may skew examples toward certain perspectives while omitting others. Publishers will need to sustain active editorial oversight to preserve educational accuracy.
Widespread use of AI also poses cultural challenges within academia. Instructors accustomed to traditional methods may hesitate to embrace automation in pedagogy. Framing AI as a tool for support or enhancement rather than a substitute may help shift the perception from threat to helpful resource rather than a replacement human judgment.
Onward toward an intelligent curriculum
With changing perceptions around how it is used, AI can turn textbooks from static repositories into living frameworks that will interpret, adapt, and respond. While we’re not there yet, in the near future textbooks may update themselves as new research emerges or as analytics reveal the areas in which learners struggle. Exercises could adjust difficulty dynamically; examples might localize automatically. These innovations lead to an intelligent curriculum that will be a continuously improving ecosystem shaped by the interaction between educators, students and AI.
The publisher’s mission remains the same: to deliver trusted, accurate, relevant high-quality learning materials. But the means by which this is accomplished is changing to favor agility, feedback and continuous growth. The textbook, once bound by paper and time, now begins its second life, growing from a static, finished product iterated by the edition, to an intelligent process producing living, evolving content. Sounds pretty cool.
Sources
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[https://publishingmeta.com/2025/06/25/ai-in-educational-publishing-opportunities-and-risks]
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[https://integranxt.com/blog/content-technology-change-top-higher-education-publishing-and-edtech-trends-shaping-2025]
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[https://www.thetimes.co.uk/article/pearsons-ai-push-fuels-profit-rise-and-350m-buyback-67lq82vhf]
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[https://www.techlearning.com/news/edtech-show-and-tell-october-2025]
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[https://www.theverge.com/2024/10/18/24273895/penguin-random-house-books-copyright-ai]
7. Publishers Weekly. *“An AI Licensing Primer for Book Publishers.”* (2024).
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9. Extanto. *“The Practical Value of QueryTek in Higher Education Publishing.”* (2024).
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