Conclusion

So where does this leave us?

I felt it necessary to catalog the challenges that publishing faces. Chat AI is arriving at a time when trade publishing is troubled. It’s not arriving at a time when the industry is robust, and able to say: “we don’t need some newfangled technology; we’re doing just fine.”

I talked above about the most pressing challenges publishing faces: rising costs and shrinking margins.

The wolves will never be sated in their demands for ever steeper discounts; margins will not improve. Retail prices are near a ceiling. The future of the current trade publishing model lies in cost reduction.

Salaries cannot go any lower, so we’ll need to cut costs within the production cycle.

But publishers have been trying to cut production costs for decades. There have been some notable successes, but we’ve exhausted the current options.

I’ve shown that AI can bring efficiencies to publishing, across the workflow. They’re not instant and they’re not easy: you need to work at AI. But the opportunity is there.

Publishers are not looking to reduce staffing, so the objective has to be more books coming more quickly to market based on current staff resources. AI tools can further that objective.

And, of course, there’s always a goal of selling more copies of the books being published. AI can help there as well.

My simple recommendation to publishers is to employ AI tools with the objective of driving 15% out of fixed costs, while seeking a 15% increase in backlist sales, in any format.

I describe above how AI can be transformative to the longer-term future of publishing as well.

Don’t worry about that. Get your house in order, and we’ll talk further.