It still shocks me how much difference there is between AI users. I think it explains a lot about the often confusing (to me) coverage in the media about AI and its productivity impact.
I think it's clear there are two types of users to me now, and by extension, the organisations they work for.
First, you have the "power users", who are all in on adopting new AI technology - Claude Code, MCPs, skills, etc. Surprisingly, these people are often not very technical. I've seen far more non-technical people than I'd expect using Claude Code in terminal, using it for dozens of non-SWE tasks. Finance roles seem to be getting enormous value out of it (unsurprisingly, as Excel on the finance side is remarkably limiting when you start getting used to the power of a full programming ecosystem like Python).
Secondly, you have the people who are generally only chatting to ChatGPT or similar. So many people I wouldn't expect are still in this camp.
M365 Copilot has a lot to answer for
One extremely jarring realisation was just how poor Microsoft Copilot is. It has enormous market share in enterprise as it is bundled in with various Office 365 subscriptions, yet feels like a poorly cloned version of the (already not great) ChatGPT interface. The "agent" feature is absolutely laughable compared to what a CLI coding agent (including Microsoft's own GitHub confusingly-named-Copilot CLI).
To really underline this, Microsoft itself is rolling out Claude Code to internal teams , despite (obviously) having access to Copilot at near zero cost, and significant ownership of OpenAI. I think this sums up quite how far behind they are
The problem is that in enterprise Copilot is often the only allowed AI tool, so that's all you can use without either potentially losing your job or spending a lot of effort trying to procure and use another AI tool. It's slow, the code execution tool in it doesn't work properly and fails horribly with large(ish) files, seemingly due to very very aggressive memory and CPU limitations.
This is becoming an existential risk for many enterprises. Senior decision makers are no doubt using these tools with such poor results and are therefore writing off AI, and/or spending a fortune with various large consulting and management consultancy outfits to get not very far.
Why enterprise is so at risk
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