What are you automating?

Hello,

This is Simon with the latest edition of The Weekly. In these updates, I share key AI related stories from this week's news, list upcoming events, and share any longer form articles posted on the website.

As much as I've been working with AI for the last few years, it still manages to impress me.

At the start of the week, a colleague was showing our team a skill they had built in Claude. This particular skill is designed to produce a handover document from the sales team to the customer department. It's actually a perfect process for AI to assist with — it's crucial, but also time-consuming, and one that can often get overlooked.

By referencing a number of documents used in the sales process and connecting to some internal tools, the skill produces a thorough, 10-page handover document in just 5–10 minutes. It would take a human several hours to produce the same level of detail, making this not only a very useful document, but also a significant time saver. We've already noted that the same skill could be tweaked to produce handover documents for when people go on holiday or take extended periods of leave, such as maternity.

And it's features like Skills in Claude that are really making AI useful in today's workplace. Gone are the days when getting an AI assistant to draft an email felt like a win. Use cases as simple as that don't deliver enough return on investment to provide any real advantage. But connecting AI assistants to tools the business already uses, and automating tasks that would otherwise take hours — that's something every senior leader is far more interested in, and it justifies the ever-increasing costs that businesses are spending on AI.

Have you started building things like Skills yet? And how else do you use AI to automate tasks?

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In this section, I’m going to bring to you a real world example of AI use. This week, we take a look at how General Electric improved performance by 50%

Novo Nordisk, the Danish pharmaceutical company behind Ozempic and Wegovy, announced a strategic partnership with OpenAI this week to deploy AI across every major function of its business, with full rollout planned by end of 2026. The deal, reported by CNBC and Fierce Pharma, is explicitly framed as enterprise-wide integration, not a research pilot. Novo Nordisk, which generates around $65 billion in annual revenue, would be one of the largest pharmaceutical companies to commit to this scale of AI deployment.

Why it matters: Pharma has been among the more cautious regulated industries when it comes to AI at scale, and most announcements have focused narrowly on drug discovery. Novo Nordisk's decision to extend deployment into manufacturing and supply chain is a materially different signal — both for pharma peers and for any organisation in a regulated industry still treating AI as an R&D project rather than an operational one.

The tech industry cut approximately 78,500 jobs in the first quarter of 2026, according to data compiled by Layoffs.fyi and reported by Tom's Hardware, Tweaktown, and Vucense. Of those, companies explicitly attributed 47.9% — around 37,600 positions — to AI automation and workflow changes, the highest proportion of AI-cited cuts ever recorded in a single quarter. The figures include Oracle's 30,000-person restructuring and Snap's 1,000-role reduction, with Snap CEO Evan Spiegel explicitly stating that AI was reducing "repetitive work" that previously required dedicated headcount.

Why it matters: It is reasonable to be sceptical when companies attribute layoffs to AI, but when nearly half an entire quarter's cuts carry explicit AI attribution from the companies themselves, the pattern is harder to dismiss as framing. For business leaders managing teams, Q1 2026 marks a shift from forecast to fact.

A global study by PwC, published this week, found that 74% of the economic value generated by AI is flowing to just 20% of organisations — with the gap driven not primarily by sector, size, or budget, but by strategic focus. The research covered several thousand companies across 65 countries and found that the outperforming firms are using AI to pursue revenue growth, not just cost reduction. They are also nearly twice as likely to have formal AI governance structures in place. The study is available in full on PwC's global website.

Why it matters: Most organisations are still framing their AI programmes around efficiency and productivity. However, the PwC data suggests that the companies capturing disproportionate returns have repositioned AI as a growth lever rather than a cost tool. For any business currently reviewing its AI strategy, these numbers are a prompt to ask which side of that divide it is on.

Thanks for reading, and see you next Thursday.

Simon,

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