Does your publishing house really need an AI department

Does Your Publishing House Really Need an AI Department?

by

Table of Contents

Introduction

Artificial intelligence is no longer the future; it is very much the present. AI is popping up everywhere, from quirky startup pitches to boardroom meetings at the world’s biggest publishing companies. It’s impossible to avoid the noise. Everywhere you look, someone is breathlessly announcing that AI will either save publishing or tear it apart at the seams.

At this point, it feels like every industry article you read is shouting, “Invest in AI now, or you’ll be obsolete by next Thursday!” But here’s the uncomfortable question that not many people are asking: Does your publishing house actually need its own AI department? Or are you just caught in the whirlwind of tech-driven FOMO?

This isn’t a simple yes-or-no question. Publishing, like many creative industries, doesn’t continuously operate on rigid formulas. The prospect of an internal AI department might sound futuristic, but it’s worth taking a step back to think carefully before jumping in. After all, starting a whole new department isn’t like installing a new coffee machine. It comes with serious costs, commitments, and long-term consequences.

So, let’s slow down the hype train for a moment and ask the question properly. Does your publishing house really need an AI department, or is there a more effective way to approach this new world?

The AI Boom in Publishing: More Than Just Buzzwords?

AI has already established itself in the publishing ecosystem, even if some professionals still claim otherwise. Many publishing houses, from indie presses to major players, are already using AI-powered tools. These include grammar checkers, plagiarism detectors, manuscript screening software, and marketing automation systems. Even tools like ChatGPT and Jasper are gradually becoming integrated into editorial workflows.

You might not see flashy headlines about it, but AI is humming quietly in the background, fine-tuning book descriptions, auto-generating metadata, and optimizing ad campaigns. Some tools even predict future bestsellers by analyzing sales trends and reader preferences.

Here’s a number that might jolt you: the global market for AI in publishing was valued at approximately $1.02 billion in 2023 and is projected to reach around $7.78 billion by 2033, growing at a compound annual growth rate of 22.7% during the forecast period. That’s not just a slight trend; it’s a seismic shift.

And yet, just because AI is available doesn’t mean every publishing house must scramble to build an in-house AI division. Many of the tools currently driving the biggest changes are off-the-shelf solutions, readily available to anyone with a subscription fee and a bit of curiosity.

Still, the appeal of having a dedicated AI department is understandable. It promises speed, efficiency, and a certain futuristic glow that marketing departments love. But promises and practical results aren’t always the same thing.

Why Some Publishers Are Building AI Departments Anyway

Some publishing houses aren’t just dabbling with AI. They’re diving in headfirst. The logic is simple: owning your AI means controlling your future.

An internal AI department allows a publisher to tailor tools specifically to their needs. For example, instead of relying on third-party platforms, a house could build a custom system to predict which manuscripts have the highest sales potential or automate parts of the editorial review process. These proprietary systems could become competitive advantages that are difficult, if not impossible, for others to replicate.

Another powerful motivator for an AI department is data privacy. Publishing houses handle sensitive information: unpublished manuscripts, author contracts, financial projections, and more. Outsourcing AI projects to external providers may involve risks, including leaks or breaches. With an internal team, publishers keep everything in-house, safeguarding valuable intellectual property.

Then there’s the long-term cost factor. Hiring AI experts isn’t cheap—good data scientists and machine learning engineers often command six-figure salaries—but many publishers are discovering that continually paying for external tools, APIs, and consultants quickly adds up. In the long run, building in-house AI systems may prove more economical, particularly for large-scale publishers that produce hundreds or thousands of books or journals each year.

And let’s not forget prestige. Having an AI department isn’t just about solving practical problems. It’s also a flashy signal to the industry that you’re ahead of the curve. It sends a message to authors, partners, and investors: We’re forward-thinking, technologically savvy, and ready for what comes next.

Why Most Publishing Houses Probably Don’t Need One (At Least Not Yet)

While the allure of an in-house AI department is strong, it’s far from necessary for most publishing operations. In fact, for many, it would be an expensive mistake.

Smaller and medium-sized presses usually don’t have the complex needs that would justify a dedicated AI team. Many common publishing tasks—such as editing, metadata optimization, and plagiarism checks—can be handled effectively with existing SaaS tools like Grammarly, Rank Math, or ProWritingAid. These tools aren’t just cheaper; they’re also remarkably user-friendly, meaning staff can adopt them with minimal training.

And then there’s the matter of costs. Even a modest AI team can quickly become a financial sinkhole. You’re not just hiring one person; you’re hiring engineers, data scientists, and project managers. On top of that, you’ll need expensive computing resources, cloud services, and cybersecurity protocols. It’s the kind of setup that can easily run into hundreds of thousands of dollars annually, if not more.

Perhaps the biggest overlooked hurdle, however, is data readiness. AI requires clean, organized data to function effectively. If your publishing house hasn’t already spent years digitizing archives, standardizing metadata, and tracking sales metrics, your newly minted AI team will be stuck cleaning up digital messes instead of building anything useful.

At that point, the question becomes less about “Do we need an AI department?” and more about “Have we done the basic homework to even make AI feasible?”

Smarter, Less Risky Alternatives to Full AI Departments

Fortunately, there are ways to embrace AI without going all in immediately. In fact, many successful publishing houses are choosing a more pragmatic, hybrid approach.

One of the most effective strategies is to work with AI consultants on specific projects. Maybe you want to develop a tool to streamline your editorial calendar or build a system to analyze reader reviews and identify market trends. By hiring external experts on a project basis, you can get highly customized solutions without committing to a full-time team.

Academic partnerships are another smart route. Universities and research labs are often eager to collaborate on AI initiatives, particularly in fields such as natural language processing and computational linguistics. Such partnerships frequently come with grant funding or government support, making them surprisingly cost-effective.

Then there’s the simplest option: upskilling your current staff. Many publishing professionals are now learning to utilize AI tools independently, leveraging platforms like ChatGPT, Claude, and Midjourney to enhance everything from editing workflows to marketing copy. You’d be surprised how much your current team can accomplish with a bit of training and experimentation.

The point here isn’t to avoid AI, but rather to approach it strategically. You can adopt AI gradually, layering it into your operations where it makes the most sense, without overextending your resources.

The Heart of the Matter: It’s Not About AI Departments

Ultimately, the biggest mistake publishers make when considering AI is focusing too much on structure—departments, job titles, and tech stacks—and not enough on results.

AI isn’t a magic wand that you wave to solve every problem. It’s a tool, no different from a word processor or a sales dashboard. The real power lies not in having an AI department, but in making smart, targeted decisions about how to utilize AI to solve real-world problems.

Struggling to keep up with submissions? AI can help prioritize manuscripts. Losing too much time on repetitive editing tasks? AI can speed up the process. Need better sales forecasting? AI can crunch the numbers. However, all of these solutions can be accessed without hiring a large team of data scientists.

The better question to ask isn’t “Do we need an AI department?” It’s “Where can AI meaningfully improve our work right now?”

If you can answer that honestly, the rest tends to fall into place.

Conclusion

Artificial intelligence is already transforming the publishing world, but it doesn’t mean every publishing house needs to rush into building an internal AI department. For some, particularly larger operations with complex needs and deep pockets, it may make sense. For most others, smarter, more incremental solutions will do just fine.

The key isn’t to obsess over having the shiniest tools or the biggest tech team. It’s about making clear, thoughtful decisions about where AI can provide actual value—and then acting on those opportunities.

After all, the future of publishing isn’t going to belong to whoever has the largest AI department. It’s going to belong to those who are wise enough to use technology without losing sight of what publishing is really about: ideas, stories, and human connection.

Leave a comment