AI Strategies for Book Publishing Companies

January 26th, 2025

First revision, February 3, 2025

I’ve realized that amidst all of my excitement around what AI can do for authors and publishers (in the midst of a great many AI threats, challenges and concerns), I’ve neglected to be explicit about what publishers can do, from a strategic perspective. Here’s my first revised draft conjuring a program. (It can also be downloaded as a PDF.)

When my friend Bob M. read this post he commented “it sure seems like you want publishing companies to turn themselves inside out to bring AI into every aspect of how they do business.” No, it’s not that. This is intended for companies who have independently decided that they want to move forward aggressively in AI adoption, and have been looking for a roadmap. They need to decide to decide.

  1. 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.

The first decision to make is whether you want to engage actively with AI or not. Some organizations pursue a deliberate strategy of not adopting external AI tools—and that is a valid choice. But, 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. The only useful approach is to go all in.

  1. 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 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 sufficiently robust TMS and/or CMS (title management system or content management system)? And more…

  1. Staffing for AI:
    Perhaps the most important set of decisions to make early in the process concern an AI strategy for your staff.

Management can’t tackle AI on their own, and they can’t tackle it just with outside vendors and consultants. The largest determinant of your success in executing your overall AI strategy will be having buy-in from a knowledgeable and experienced team.

Some of your staff have already made progress on their own, probably 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 programs.

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 train or hire an “AI Leader” for the organization, responsible for working with management to support staff development and advising on strategic direction?

  1. 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 ongoing 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.

  1. Pilot Project:
    Plan for a pilot project to be implemented by the early enthusiasts. 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).

  1. Financial planning:
    You will need to budget for AI training and implementation. Software costs are modest; nearly all of the cost is 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?
  1. AI & Publishing Value Chain:
    Analyze how AI could disrupt various aspects of the publishing value chain, such as author 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. 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 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), or driving new revenue. Regardless of the anticipated dollars that might be saved, or the revenue that might be gained, assume that both types of initiatives have equal value. Nonetheless, set targets, and timelines. Given the speed of change for AI, include quarterly review/adjustment cycles.

  1. AI Quality Control:
    Establish metrics for evaluating AI output quality across different departments. Define acceptable error rates and correction procedures. Create workflows for human review and oversight.
  1. 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.
  1. 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.
  1. 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?
  1. AI Policy Development:
    Develop an official organizational policy on AI (or possibly, a set of policies). Define the “ethical use of AI” within your company. Ideally your internal policy will be consistent with your public (author-facing) policy, though the nuance will vary.

Establish clear policies around AI usage rights in author contracts. Develop guidelines for AI-assisted content creation and editing. Create protocols for detecting and handling AI-generated submissions (see #17).

  1. 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.
  1. AI Risk Management:
    Create contingency plans for AI program failures. Develop protocols for AI-related PR issues. Plan for potential AI regulatory changes.
  1. 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.
  1. AI Use Detection, Fact-checking and Plagiarism Detection:
    Invest in understanding which AI tools can detect AI use, plagiarism or inappropriate content. Explore AI use for fact-checking.
  1. Accessibility and AI:
    AI tools are proving to be fast and largely accurate for creating accessible content, including both alt-text and audiobooks. How can you take advantage of these tools?
  1. AI for Marketing:
    AI tools for marketing have tremendous potential, and are being widely used across multiple industries. Your staff need to prioritize AI adoption across marketing and sales functions.
  1. 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.
  1. AI & Translation:
    AI translations using large language models greatly increase translation efficiencies. 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?
  1. 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. 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.