It has been a busy week: updating the materials for and delivering a lunch-and-learn session and another full day training course on AI for IPG members, and preparing a keynote presentation on the future of publishing for a conference in Chicago next week. To prepare for those things, I’ve been reading and talking to a lot of interesting people about how they are using AI at the moment. In between, I made a quick dash up to London for my ten year business school reunion—a room full of smart people from different industries who provide a triangulation to the publishing experience. There are three interesting patterns that kept coming up in all of those different contexts.

If you read my piece last year on sizing and plotting the UK publishing industry based on Companies House data, there’s an interesting coda today with the publication of the Office for National Statistics’ updated Standard Industrial Classification (SIC) codes for 2026. If you’re not familiar with what SIC codes are, you’ve probably given up reading by now—but the short version is that SIC codes are short numbers that describe what business activities companies engage in. Firms choose one or more SIC codes when they register with Companies House.

Ian Mulvany has a good piece in the latest issue of InPublishing examining challenges and opportunities for publishers. A couple of his points really stuck with me. Under pressure from investors to signal progress, companies are forcing AI into products and services without a clear sense of value. The result is a proliferation of new features that are individually justifiable but risk being collectively incoherent. And while generative AI can speed up the creation of content, code or even products, it doesn’t create additional time—in other words, opportunity cost still applies. I’ve started thinking of this pattern as strategic debt.

I took part in a webinar on AI and publishing earlier today, hosted by the Crius Group, alongside my friends and colleagues Cameron Drew and Simon Mellins. One of the topics that came up was what mistakes we saw organisations making with AI. The conversation was about publishing, but the more we talked, the clearer it became that these failure modes aren’t industry-specific. They show up everywhere. Here are eight of the most common. If you recognise more than two or three of them in your organisation, you may not have an AI problem—you may have a strategy and operating model problem.

This piece was commissioned by James McConnachie and first published in the Spring 2026 issue of The Author, the journal of the Society of Authors. It is reprinted with their permission.

I gave the opening keynote at the ALPSP University Press Redux conference in Liverpool earlier today, discussing how generative AI is affecting scholarly publishing. My professional background is in trade rather than scholarly publishing, so instead of focusing on the university press business model or specific AI tools, I tried to step back and look at a macro question: what happens when AI changes both how knowledge is produced and how it is discovered.

I’ve just had three very busy days with friends, colleagues and clients at the London Book Fair. I spent time with every company in my portfolio, and had a great discussion with my publisher about my forthcoming book (watch this space for more). While the show is still fresh in the mind, here are a few reflections—less a comprehensive account of the Fair than a set of personal observations, raw signals and conversations that struck me over the last few days.

Everything is now a data business, especially media companies. My friend Alex Boden’s analysis of the Washington Post’s pivot to WP Intelligence is characteristically sharp: editorial expertise converted into structured intelligence products, sold to professional audiences on enterprise contracts. The playbook works for a news publisher. The question for trade book publishers is what version of that pivot is available to them.

Thanks to Luis González, Javier Celaya, Christopher Kenneally and their colleagues for inviting me to give a keynote address on the impact of AI on audiobook publishing this morning at Parix Audio Day 2026 in Madrid. It’s one of the best conferences in the publishing calendar, and hands down the best venue.

I’ve been trying to write something here roughly once a week, largely but not exclusively about my experience working with AI in publishing. I hadn’t planned to post anything else this week, but John Willshire linked to a post from Rachel Andrew on managing publishing operations in the context of generative AI and I wanted to respond to it with some thoughts about how the issues it raises affect book publishing.

Andrew Savikas recently wrote that one of the best ways to see the future of knowledge work is to watch how software developers work. It made me smile because I got to know Andrew nearly twenty years ago through his work at O’Reilly Media and their Tools of Change for Publishing conference—“watching the alpha geeks” was a core philosophical and strategic tenet for O’Reilly.

I’m on my way back from the IPG Spring Conference in London, always one of the highlights of the publishing year. It was a really good mix of the inspirational, the practical, and a uniquely generous, welcoming and supportive community. I particularly enjoyed the presentations from former Shazam chairman and crime writer Ajay Chowdhury, National Literacy Trust CEO Jonathan Douglas, BBC media editor Katie Razzall, Illumicrate CEO Daphne Tonge and Bonnier UK Co-CEOs Sarah Benton and Jonathan Perdoni. I spoke in the morning about the IPG’s forthcoming short training courses (data, content creation, websites/GEO and AI risk/governance) and in the afternoon to give members an update on the policy and licensing landscape for AI.

There’s an interesting new report out from the Minderoo Centre for Technology and Democracy at Cambridge University on the impact of AI on the novel, authored by Dr Clementine Collett. There’s much that I completely agree with and that accords with my experience of working with book trade on AI. But I have some constructive thoughts about the framing/communication.

Recently I’ve been doing some research on the size and scope of the UK book and journal publishing industry, based on data from Companies House. This research is a preparatory step towards building a database of companies, highly relevant for my work as an independent consultant and as policy advisor for the Independent Publishers Guild, which represents over 600 book and journal publishers of all sizes. The other trade body, the Publishers Association lists 168 members at the time of writing, particularly larger, corporate publishers—though there is some overlap between the two organisations’ memberships. The UK publishing sector is world leading, representing over £7 billion of revenue, and it represents the bulk of my client base. So it’s worth understanding.

I don’t use TikTok, but it has been hard to escape its impact on the publishing industry, where I spent the first part of my career. Nielsen research suggests that one in four UK book buyers used TikTok in 2022, accounting for 90 million purchases. As a collective phenomenon, BookTok was awarded the person of the year award at last year’s Futurebook conference. In the meantime, there’s little doubt that the platform has a huge impact on commissioning, marketing and selling books, and that publishers are investing time and money to make the most of that. As a proxy for the level of interest, a search on the Bookseller magazine’s website this morning showed eighty nine search results for ‘TikTok’ for stories published in the first quarter of the year, versus four results for ‘GPT’. (Long term, I know which one I would bet on being most significant and transformative, but that’s another story.)

This piece was commissioned by James McConnachie and first published in the Autumn 2021 issue of The Author, the journal of the Society of Authors. It is reprinted with their permission.