It’s been a heavy week with travel, an IPG Lunch and Learn update and interesting discussions at the BISG AI Working Group. But before publishing breaks for the weekend and packs for Frankfurt, some interesting AI developments across audio, author apps and retail… ​ AI audio platform ElevenLabs has introduced a new managed production service combining AI voice reading and human editing and post-production. Audiobook production is one of the launch use cases, and pricing starts at $2 per minute. It’s an interesting middle ground: cheaper than human voice audio, arguably better than out-of-the-box AI voice but still not quite convincing, to my ear at least. I also wonder if offering a managed service around it is also a tacit acknowledgement that tweaking outputs for quality isn’t easy. ​ A couple of weeks ago, I commented on a piece about AI use in education and speculated about which self-help author would be the first to create their own AI coaching app. Thanks to subscriber Nikki Howard from Gill Books for pointing out that Tony Robbins was way ahead of my speculation: for $99 a month you could have access to 24/7 advice from his chatbot. Similarly, this week, hedge fund manager and bestselling author Ray Dalio launched a beta version of an AI advice app using a voice interface. For publishers working with brand authors, there’s an interesting question of whether this kind of AI product becomes a core part of the format mix, or if it’s the equivalent of the iPad apps that were launched with great fanfare in the early 2010s, few of which survive. ​ With the holiday season in sight, Adobe Analytics published new research on how shopper behaviour is being influenced by AI: 53% of respondents had used generative AI for research, 40% for product recommendations and 36% for finding deals. This growing usage explains why ChatGPT is integrating buy links into LLM outputs, and Google recently introduced a payment protocol for AI agents. ​ For publishers, this introduces a trade-off between restricting AI crawlers from their websites to prevent training, and allowing them to encourage visibility of products in outputs. OpenAI and Anthropic use different crawlers for training and servicing user queries, so it’s possible to take a granular approach. But Google and others do not, and most publisher websites that I’ve reviewed take an all-or-nothing approach. ​ Web content being scraped doesn’t just affect publishers and retailers, but also universities. For academic readers, the Authors Alliance has a good piece here looking at AI scraping of institutional repositories (which often contain versions of publisher content) and tensions between restricting AI training and Open Access publishing. ​ Ultimately, across both domains, this will be a judgement call for publishers, but I’m reminded of Tim O’Reilly’s aphorism that obscurity is a greater threat than piracy. ​ At OpenAI’s Dev Day, Sam Altman claimed that ChatGPT now has 800 million weekly active users—a staggering figure that, if accurate, would make it one of the largest digital platforms in the world. For context, Microsoft 365 has around 400 million paid seats. In less than two years, generative AI has gone from experiment to near-universal tool, a shift no other technology has achieved at such speed or scale. ​ For a more independent take on usage statistics, there’s a great new report from the Reuters Institute at Oxford University: 90% brand awareness of leading AI tools, all-time AI use increasing from 40% to 61%, and weekly use of AI tools nearly doubling. For publishers, it’s striking that information seeking is the number one use case, ahead of content creation. ​ There are some interesting points in a recent Econsultancy study on marketing and AI: in particular, 47% of marketers described their knowledge of generative AI as advanced or expert: only 4% then passed a test on their knowledge. ​ Finally, Dan Shipper has an interesting essay here commenting on sharp progress in AI performance but putting it in the context of human intelligence. It’s a timely reminder that the good results that are possible with AI depend on enormous amounts of human framing—not least designing tasks, prompts, and evaluation criteria.

Another week, another flood of AI product announcements from Microsoft, Amazon, OpenAI and Anthropic. But some of this week’s news feels particularly consequential: if you publish books to Kindle or have a direct-to-consumer sales strategy, read on…

The approval of the settlement in the Bartz v. Anthropic litigation overshadows most other developments for publishers this week. But elsewhere the week has seen new research, strong opinions on LLMs and web traffic, and a new creative AI tool that could get traction with creative teams in publishing. Have a good weekend. ​ Big news overnight: Judge Alsup has given preliminary approval to the copyright infringement settlement in Bartz v. Anthropic. There will be more information on the operation of the settlement in coming days, and I’ll be covering this in detail in my next policy update for IPG members. As a reminder, it’s not enough for works to be within LibGen: eligibility for the settlement depends on copyright having been registered within five years of publication and before August 2022 (the date of Anthropic’s infringement). It’s also worth reiterating that the settlement is about copyright infringement, not the subsequent training, which Judge Alsup found to be Fair Use. In considering the sufficiency of the roughly $3,000 per author, the Judge asserted that Anthropic could have paid as little as $1 for a (presumably used) copy of a book and trained from that. ​ I was talking to a client this week about how publishing breaks down into individual and group tasks. Most of the successful AI use cases I’ve seen have been about making individuals more productive—fewer have addressed collaborative working. So I was interested to see the latest experiment from Google Labs: Mixboard, an AI-powered mood board tool. It’s currently only available in the US, so American friends, have at it, while the rest of us wait or VPN. But this looks like a really interesting way for design, marketing and other creative teams to collaborate on visual tasks, and it’s the first AI tool I can imagine seeing on meeting room screens. ​ Useful snapshot data in Google Cloud’s 2025 DORA report on the state of software development: 90% of software developers are using AI, 80% reported increased efficiency, and 59% claimed increases in code quality from using AI tools. ​ Research from the Tony Blair Institute tends to divide opinion. But its latest report on AI usage and attitudes, based on polling by Ipsos, also gives a useful contextual snapshot. Some highlights: more than half of UK adults have used Generative AI tools in the last year, and just under a quarter use Gen AI weekly; two thirds of people who feel confident in their AI skills expect it to help them at work while leaving core responsibilities intact, but only 45% of people with lower confidence are optimistic; and looking at secondary education, 37% of respondents were comfortable with the idea of AI tutors compared to 32% against, with 33% in favour of AI taking on some routine teaching tasks versus 38% against. Lots of undecideds on both, but even small moves in this direction would have far-reaching implications for the sector and for educational publishing. ​ On the education theme, HBR has an interesting report on an experiment using Generative AI for professional training which found significantly better outcomes from personalised AI coaching. It’s interesting but all a bit vague: I’d love to know more about the model they used, as opposed to generic references to a Gen AI Tutor. But it’s an interesting direction. I’m curious to see who is the first self-help author to release an AI coaching tool alongside their books and courses. ​ Continuing the theme of discovery and web traffic from LLMs from last week, my friend Ani Attamian has a great piece in The Bookseller on AI optimisation, including recommendations for tools to monitor performance and visibility. I’ve known Ani since she was working with publishers at Google, and if you’re looking for help in this area, she’d be a great person to talk to. ​ Cloudflare’s annual letter outlines a future where AI agents, not humans, are the main readers of the open web, and traffic-based business models continue to erode. Their proposed fix is to facilitate AI companies paying creators. But as Paul Ford points out in his newsletter, that vision turns writers into prompt-chasing content suppliers. The real lesson for publishers? Paywalls work. In a world of aggressive scraping and vanishing referral traffic, subscription models—not scale—are becoming the most reliable path to sustainability, leverage, and autonomy. ​ Nieman Lab has a piece comparing the AI strategies of the New York Times and Washington Post, which provides some helpful advice on AI deployment for publishers: I was particularly taken by the Post’s policy that while generic information can be processed through enterprise AI tools like ChatGPT, sensitive data can only be used with internally hosted language models. Few publishers will need that level of security, but I suspect if you’re writing about All the President’s Men, sensitive data really is quite sensitive (RIP Robert Redford). ​ Finally, since we’ve established that a non-trivial proportion of you are classics nerds, you might enjoy this tongue-in-cheek suggestion from Ethan Mollick for properly acknowledging the role of AI in work: tagging it with the Latin phrase, Fieri iussit.

A slightly shorter email than usual today, as it’s been a very busy week of travel. I had conversations about AI in some interesting places: a publishing conference, an Oxford college and the House of Lords. The latter two particularly felt a long way from Silicon Valley, but the discussions underlined how much the technology is permeating every aspect of our lives. ​ International readers may have missed President Trump’s state visit to the UK this week, but domestically it’s been hard to ignore. There was a slew of major AI investments being announced, but for publishers the most consequential aspect of the week was confirmation from new Technology Secretary Liz Kendall that no commitments had been made to AI companies on UK copyright and AI training. ​ A couple of major updates on AI and ecommerce. Amazon announced an upgrade to its Seller Assistant, which now includes AI agents for tasks like inventory management. Publishers or retailers using FBA can use the AI to review stock levels, minimise charges, identify product opportunities and plan marketing campaigns. This goes beyond basic automation into generating proactive insights. This is interesting in its own right, but also speaks to Amazon’s bullish strategy on AI: this tooling is for FBA today, but it shows the direction of travel for Vendor Central and other systems. ​ Secondly, on the customer side of the transaction, Google launched Agents Payment Protocol (AP2), a standard way for AI agents to be authorised to make purchases on behalf of consumers. More than a third of UK consumers (more than half in the US) are already using generative AI for research and product discovery. Whether purchasers will be happy with the idea of an AI personal shopper is a big question. ​ I was at the Independent Publishers Guild Autumn Conference on Tuesday, and had the pleasure of chairing a panel with Isaac Jones of the BMJ and Lauren Ingram of Next Big Thing, discussing the impact of AI on websites, and how to optimise website content for AI models. Publishers need to strike a balance between controlling how the content on their website is used by AI models, preserving traffic, and being visible and hyperlinked in AI outputs—or, as I thought about it afterwards, having your click and feeding it. This is a fundamental question given that point above on the importance of AI for product discovery. This is a complex and nuanced topic, but as a start on a checklist for publishers, my takeaways from the session were: there will be a range of perspectives even within a publisher—editorial, marketing and technical stakeholders look at this through their own lens, so coordination is essential; quality of content (including specificity, uniqueness and credibility) is fundamental, which should play into publishers’ strengths; and experimentation is key, including putting yourself in your audience’s shoes and using the platforms they do. Do get in touch if you’d like to discuss what this means for your business. ​ Some highlights from OpenAI’s new research paper on how people are actually using ChatGPT: around 10% of the world’s adult population has used ChatGPT; 18 billion prompts are being sent each week; and non-work use cases (advice, shopping) account for 70% of usage, up from about half a year ago. ​ There’s a sobering report here on librarians’ experience of AI: patrons showing reduced critical thinking, and requesting hallucinated books. ​ Thanks to Thad McIlroy for highlighting an essay on AI in the workplace that argues most organisations are essentially in the business of converting work from one format to another. As it points out, there’s a natural role for AI in this, and the implications it identifies for organisations echo the HBR piece I shared last week on consulting firms. Broadly it rings true. But two nuances strike me. First, AI is very good at summarising—many of the examples in the essay are essentially reductive—but often less capable when the task is to expand short form into long form. Second, what AI produces often loses individuality. In Oxford this week, I spoke with a Mandarin translator about how AI translation can be powerful but flattens linguistic nuance. For some tasks in business and publishing, the output may be good enough. But publishing is a business of meaning-making as well as information—and that’s where the human voice remains indispensable.

This week’s stories point to deeper layers of the AI stack: standards, infrastructure and how organisations are evolving. From licensing to litigation to content production, there are clear signs of where publishing may be heading.

This week’s practical insight focuses on two linked topics: onboarding and oversight of AI models. But there are also more philosophical questions from news publishing and Seth Godin, and details of the most open LLM to date. Have a great weekend. ​ Sometimes it’s the simplest insights that stick. In a recent webinar with Rich Ziade and Paul Ford of AI developer Aboard, Rich said something that stopped me in my tracks: “AI is a new hire.” When you onboard a new team member, you think carefully about their role—who they’ll work with, what systems they’ll need access to, how they’ll get up to speed. In a hybrid workplace, we’ve learned that structure and documentation matter more than ever. But with AI, I’ve seen people open up a general LLM with no context or preparation, and then feel disappointed by the results. It’s the equivalent of throwing a new hire in at the deep end and hoping for the best. ​ Here’s my start on a checklist to avoid that. Have you done each of these things for your AI projects? And let me know if there’s anything you’d add to the list.

The AI and content ecosystem is maturing fast. The big news this week is a settlement in Bartz v. Anthropic with implications for other litigation. But besides the big picture, the newsletter highlights new tools and practical things you can try. Have a good weekend.

AI is changing how people produce, discover and evaluate content. This week’s stories show how fast those shifts are happening. From Amazon’s AI shopping assistant to Grammarly’s reimagining of student writer, publishers face questions about visibility, value and voice.