As many authors and literary professionals know, the book publishing industry is notoriously slow to change. For example, industry standard platforms such as QueryTracker and Publisher’s Marketplace lag behind in
Not only that, but query submissions still lead to saturated agent inboxes to this day, which takes time away from their busy schedules. Additionally, while buzz around miscellaneous books has been abundant in recent years, pinning down acquisition and distribution due to lack of data is a challenge. Finally, without a surgical approach to attribution and omnichannel operations, traditional publishing digital marketing efforts can often feel like the most fractured silos of technology.
As a science fiction writer and tech enthusiast working with many of the same tools as publishers, I wonder if there’s a better way to handle this whole book business.
What if intentional AI tools could provide a better path for the publishing industry?
For literary agents, AI might just be the ticket to inbox zero. An AI-powered layer could quickly sort submissions based on genre, word count, and sentiment analysis. It would be a dream come true for overworked literary agents. Of course, diversity must be a priority to avoid repeating
Artificial intelligence can even help demystify much of the questioning process for authors. For example, submission tags could be cross-referenced with an agent’s customer acquisitions using QueryTracker data, if they had an API (they don’t). This would not only save time, but could also increase the chances of finding perfectly suited agents. This is especially important for marginalized authors so that our unique work finds the right talent to support it.
Not only that, but if the AI was trained on successful requests, it might be able to give tooltips to authors, much like Gmail’s response suggestions. With so many sample query letters and submission headings, it can be difficult for writers to know if their query is up to snuff. Less guesswork means more time saved and happier inboxes for everyone.
In terms of book discoverability, AI could help bring out various books that fight for space. For example, Amazon uses machine learning to power its recommendation engine. However, Amazon’s algorithms are often biased and lack accountability, which is a big flaw for the e-commerce giant. A better tool can and should be built. We have the technology.
What about book acquisition data? Using a polished AI tool can lead to the automation of easily searchable databases that everyone can use to make invaluable decisions. Decisions such as marketing next steps, agents to interview, work to acquire, work that has been acquired, etc. Everyone benefits from data accessibility, especially marginalized authors. When you can see the landscape at a glance and filter in no time, it’s easy to know what inclusion work remains to be done.
Let’s talk marketing. If you’ve ever had to track metrics from traditional to digital, on omnichannel, above influencers, through editorials, and on social media, you know the real agony of marketing. AI can help publishers, bookstores, and authors overcome this hurdle by centralizing the process and layering it on a user-friendly dashboard. It is the chimera of booksellers all over the world. If you crack, consider yourself my personal hero.
Finally, being able to gain an edge on operations is paramount for any industry, including publishing. It’s a sad situation when platforms like Ingram, an industry standard for bookstores, libraries, authors, and publishers, lack APIs. When it comes to small presses, freelancers, and anyone using Amazon, operations don’t provide the necessary benchmark data.
There are many more examples of poor information visibility than these. Indeed, everywhere you turn in the digital sea of publishing, you notice how far behind it all is. This is the critical challenge: overcoming legacy tools.
What are the downsides of an AI push in the publishing industry?
Unfortunately, many authors worry
According to publishing professionals, there seems to be little reason not to pursue streamlined processes. Clearer inbox, better marketing data, higher quality queries, industry overview? It all sounds obviously positive.
What are the disadvantages of AI technology?
This is where the hope for an editorial revolution fades.
As far as AI ails, it always comes down to GIGO. Much like with Amazon’s scrapped recruiting tool, using historical publishing data without considering bias and retooling for inclusion is a critical failure. Quite simply, any AI tool operated without data cleansing calcifies and replicates systemic issues. For this reason aloneAI can’t fix posting issues at the moment, although I would like to.
Is it possible for AI and publishing to join hands and walk together towards a bright literary future? Not at the moment, but it would be a really new concept, indeed. I hope one day I can see this happen. At the very least, it would be nice if older tools made post data more accessible to everyone so that better tools box to be built.
K. Leigh is a former freelancer, full-time author, and weirdo artist. Check out their lgbt+ sci-fi books, log on to Twitter, or email them if you’d like to work together. 🌈 🏳️⚧️
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