August 18th, 2025
(First published January 26, 2025. 1st revision, February 3, 2025; 2nd revision, April 14, 2025)
Third revision, August 18, 2025
Also available as a 
This short document is intended for companies who have independently decided that they want to move forward in AI adoption, and have been looking for a roadmap. They have decided to decide. Deciding not to adopt AI technologies is an appropriate choice, for reasons I’ve described elsewhere; this post is for those interested in moving forward with AI technology, despite the controversy.
- AI Adoption Decision:
Decision-makers need to understand the fundamentals of AI as it impacts publishing. And to be willing to make a series of decisions about AI within their organization.
If you decide to move forward with AI, there’s no point in moving tepidly. You’ll learn little from gingerly poking AI around the edges — that will only give you the impression that it in fact offers little value. The only useful approach is to go all in.
- Digital Readiness Audit:
Before you move forward with specific AI initiatives, you need to get your “digital house” in order.
Any existing workflow problems that a publishing company is still facing should be addressed NOW, because the company needs to approach AI from a position of digital operational strength.
Is your metadata complete, accurate and up to date? Are all of your backlist books digitized, with the content consistently tagged? Are you efficiently using a robust TMS and/or CMS (title management system or content management system)? Are your publishing contracts digitized? Are your author email contacts verified and up to date?
- Staffing for AI:
The most important decisions to make early in the process concern the AI strategy for your staff.
Management can’t tackle AI on its own, and they can’t tackle it just with outside vendors and consultants. Your success in executing your AI strategy will be determined by whether you can get buy-in from your knowledgeable and experienced publishing team.
Some of your staff have already made progress on their own, possibly without your support or explicit endorsement. Try to identify the enthusiasts on your staff.
But few in the company can claim conversancy. It will be necessary for all staff to be trained on the fundamentals of AI as it impacts publishing, so that they can assist management in moving the organization forward with AI planning.
Determine specific AI competency requirements for different roles. Department managers will themselves be responsible for strategic decisions moving forward, and will require a higher level of AI experience and knowledge.
Do you have the budget to hire or train an “AI Leader” for the organization, responsible for working with management to support staff development and advising on strategic direction?
If you’re a smaller publisher, where will the leadership and knowledge reside?
- AI Training:
As of yet there are insufficient resources for AI training for book publishers.
My book, The AI Revolution in Book Publishing, has been well-received, but is just a brief summation of the knowledge required. My AI webinar series, co-produced with the Book Industry Study Group (BISG), features some compelling topic-based content on a range of AI & Publishing issues and opportunities.
Erin Servais’ AI for Editors Course is very good. The Independent Publishers Guild in the UK offers a one-day training program with the excellent George Walkley, available also to publishers in the U.S.
You will need someone in your organization, sufficiently enthusiastic about AI, to try to keep up with the latest.
- Pilot Project:
Plan for a pilot project to be implemented by the early enthusiast(s). Don’t make it too easy, but make sure it’s a win.
Create a framework for evaluating the project; determine success metrics (e.g., improved efficiency, cost reduction, or enhanced user experience).
- Financial planning:
You will need to budget for AI training and implementation. Software costs are modest; nearly all of the costs are in training and recruitment. Larger initiatives will require the skills of consultants and outside vendors. Where will the funding come from for your AI initiatives? Can you project a ROI?
- AI & Publishing Value Chain:
Analyze how AI could disrupt various aspects of the publishing value chain, such as manuscript discovery, editorial processes, book production, marketing, and distribution. How will these disruptions impact your organization? What actions do you need to take to minimize the effects of the disruption?
- 1-2 Year AI Strategy: Create an internal task force to build out a 1-year and 2-year AI strategy for your organization. Anything past 2 years is wild speculation — arguably true even with a 1-year and 2-year AI strategy. But in times of uncertainty, planning is an essential discipline.
With each perceived opportunity, decide whether you are creating organizational efficiencies with AI (cost savings), driving new revenue, or improving quality. Given the speed of change for AI, include quarterly review/adjustment cycles.
- AI Quality Control:
Establish metrics for evaluating AI output quality across different departments. Hallucinations are fast-declining, but define acceptable error rates and procedures to spot hallucinations and other errors in AI-generated text/responses. Create workflows that include human review and oversight.
- Industry Allies:
Figure out who your allies are, whether at other publishing companies or at trade associations, or just enthusiastic individuals/analysts/consultants. Reach out and confer. Hire outside talent to analyze, to advise, and to assist. Attend industry conferences and online webinars.
- Vendor Assessment:
Make a first assessment on which vendors or other service partners might be able to provide software or systems-based approaches to move the organization forward with AI technology.
- Competitor AI Analysis:
Assess what your competitors are doing with AI. What outcomes do you expect them to achieve from their efforts? How should this impact your strategy?
- AI Policy Development:
Develop an official organizational policy on AI (or set of policies). Define the ethical use of AI within your company. Ideally your internal policies will be consistent with your public (author-facing) policies, though the nuance will vary.
Establish clear policies around AI usage in the author contracts you sign. Some authors will try to bind their publishers to an AI prohibition. That seems fine for one author or one book, but the restrictions will soon permeate your list. Develop guidelines for AI-assisted content creation and editing. Establish protocols for detecting and handling AI-generated submissions (see #17).
- Data security and privacy:
Implement safeguards for the use of AI tools for manuscripts and associated data. Ensure GDPR and CCPA compliance when using AI. Evaluate other regulations within the U.S. federal and state governments.
- AI Risk Management:
Create contingency plans for AI program failures. Develop protocols for AI-related PR issues. Try to plan around potential AI regulatory changes.
- Author Relations:
Create support systems for authors using AI tools. Develop AI collaboration guidelines. Plan a communication strategy around AI initiatives. Consider programs to educate your authors on the pluses and minuses of engaging with AI.
- AI Use Detection, Plagiarism Detection and Fact-checking:
Invest in understanding which AI tools can detect AI use, plagiarism, inappropriate content, or sensitivity analyses. Recognize the risks associated with the use of these tools. Explore AI use for fact-checking.
- Accessibility and AI:
AI tools are proving to be fast and largely accurate for developing and labelling accessible content, including both alt-text and audiobooks. How can you take advantage of these tools?
- AI for Sales and Marketing:
AI tools for sales and marketing are being widely used across multiple industries. Your staff need to prioritize AI adoption across these functions — this is where AI-related revenue accrues.
- AI & Audiobooks:
The technology for synthetic voices works today, and is essentially undetectable. Determine your strategy on the use of AI for audiobooks, particularly for backlist.
- AI & Translation:
AI translations using large language models greatly increase translation efficiency. What does this mean to your strategy of selling and buying foreign-language rights? Which of your books could you translate to Spanish, just for the U.S. market?
- The Long-Term Vision:
While acknowledging the limitations of long-term predictions, brainstorm some visionary thinking about the future of AI in publishing, including potential scenarios and their implications for the industry and specifically, for your company. Encourage an internal team of enthusiasts to explore speculative AI innovations, including AGI (artificial general intelligence).
I want to acknowledge the encouragement of Venu Prasad Menon, managing director at Amnet ContentSource, in preparing this document. Venu invited me to participate in a webinar “AI and Publishing: Building a Successful Strategy” on January 22, 2025, and that’s what spurred me on. I prepared an early draft for Amnet. Thanks, Venu.