“I am no longer needed for the actual technical work of my job. I describe what I want built, in plain English, and it just… appears. Not a rough draft I need to fix. The finished thing. I know this is real because it happened to me first.”
– Investor and AI entrepreneur Matt Shumer, writing on X last week.
This is an excerpt from a 5000 word essay about AI that this week broke the internet.
It is emblematic of this moment in markets.
Disruption is everywhere
Almost a year ago the seat-based software business model found itself next in line for the chopping block. A combination of lower headcount growth and LLMs being really good at writing code, as noted by Mr Shumer. Investors rightly questioned the historically high multiples ascribed to software companies. The share prices of many of these companies halved, and in some instances fell -75%. Local tech darlings haven’t been safe, with Xero and WiseTech both down almost -60% from their peaks in 2025.
Elsewhere, the AI grim reaper hasn’t been quite so brutal, but has nonetheless wiped hundreds of billions from the market capitalisation of a number of sectors, as the following illustration suggests. Anthropic’s addition of a legal plugin to its ‘Claude’ chatbot sent public legal companies like Thomson Reuters and RELX (owner of Lexis Nexis) each down -15%. Other ‘knowledge work’ industries like financial services have also been hit.
Source: ChatGPT.
But the perceived impact didn’t stop with services, it also bled into hard asset companies. Commercial real estate companies were smashed when the market realised that if AI reduced headcount then businesses would require less office space. Salt in the wound for an industry still recovering from the disruption that COVID brought to office work…
Perhaps peak panic occurred when a former karaoke company, Algorhythm Holdings, launched its ‘AI freight platform’ that promised 300%-400% volume improvements and sent US trucking and logistics companies like CH Robinson and RXO down -15% and -21%.
At this point, it would be appropriate to ask: why is this happening? And part of the answer can be found later in the Matt Shumer essay. He writes:
“Let me give you an example so you can understand what this actually looks like in practice. I’ll tell the AI: “I want to build this app. Here’s what it should do, here’s roughly what it should look like. Figure out the user flow, the design, all of it.” And it does. It writes tens of thousands of lines of code. Then, and this is the part that would have been unthinkable a year ago, it opens the app itself. It clicks through the buttons. It tests the features. It uses the app the way a person would. If it doesn’t like how something looks or feels, it goes back and changes it, on its own. It iterates, like a developer would, fixing and refining until it’s satisfied. Only once it has decided the app meets its own standards does it come back to me and say: “It’s ready for you to test.” And when I test it, it’s usually perfect.
I’m not exaggerating. That is what my Monday looked like this week.”
This is not the normal stuff of business. Even the birth of the internet, coming as it did from an intent to ensure nuclear retaliation in the event of an unexpected first strike on the USA – may have been just the first course in this digital/mobile/cloud degustation, the most recent dish being AI, which will, of course, serve itself up.
Are there no winners?
The market is in flight to safety mode – i.e. companies in physical industries with physical assets (and therefore moats – for now) like consumer staples, utilities, energy and industrials.
There have also been winners in the private markets – OpenAI boosted its revenue forecasts for 2030 from US$200B to US$300B (fun fact: more revenue than Microsoft generates, today) according to The Information. The updated projections came as part of OpenAI’s latest capital raising, which Bloomberg suggests might be as much as US$100B at a valuation of US$850B. The size, speed and tectonic-plate-moving nature of this capital raising is unprecedented – a word which is thrown around but in this case is wholly apt.
Let that all sink in. The previous largest capital raising was oil giant Saudi Aramco, which sold just over one per cent of the company at a valuation of US$2T. Alibaba was next with a US$22B raise.
Unprecedented capital raisings suggest unprecedented spending
What has been most surprising is that the hundreds of billions of dollars in market capitalisation that has been lost to AI disruption fears has not been made up by the sector that is foundational to it all: semiconductors.
The fine print in OpenAI’s updated financial projections was that in addition to generating more revenue it would also spend significantly more, too. The company now expects to burn double the amount of cash, from $100B to $200B, as a result of spending $600B on computing costs over the period.
Cash Flow Paths for OpenAI and Anthropic
Source: The Information reporting, note figures rounded. OpenAI’s latest 2025 figures are actual.
The processing power (and ancillary hardware/systems) that enables all of this disruption are provided by the likes of Nvidia, AMD, Broadcom, Arista, Samsung and TSMC (all companies in the portfolios we manage). However, the majority of these companies’ share prices have hardly budged this year, despite expected earnings steadily increasing.
Something big is happening
This is the name of Matt Shumer’s piece and we agree.
Whether the share price moves across software, financial & legal services and commercial real estate companies are fair is debatable, but what seems certain is the disruptive potential of AI to every industry across the world.
However, while it’s often easy to draw a straight line from the present to some future – in this case based on a position of AI evangelism or doomerism – the reality is that disruptive change is a journey. And suggesting the magnitude and speed of progress being made in software development can be replicated in every other industry seems far too reductive.
Yes, a new breed of employee-light ‘AI-first’ businesses might emerge, powered entirely by agentic workflows instead of traditional software, but larger enterprises will stick with existing systems, keep a human in the loop and move a little slower (in a similar fashion to the adoption of cloud and mobile). Meanwhile, in the real economy, access to health services is likely to get easier with the advent of AI (this is a good thing), but many will still prefer (and require) in-person appointments with their GP or physiotherapist.
Disruption: redux
We are reminded of the strategy’s inception in 2014. Then, global sharemarkets looked very different.
The ten largest companies by market capitalisation included very few ‘disruptors’, instead being largely old-world incumbents that generated revenues from businesses in Oil & Gas, Consumer Packaged Goods (CPG) or Finance.
Ten most dominant companies from 2014 to 2026
Source: Bloomberg, as at 30 June 2014 and 31 January 2026
But technological change was already rolling through industries and fast-growing disruptors were making their intentions clear. The internet had enabled consumers to surface almost any bit of information at the click of a button (Google) or have any item delivered to your door in as little as two days (Amazon). Smartphone usage was exploding to the benefit of the platforms (Apple) and those with sizable businesses on top of them (Meta). An increasing number of enterprise workloads were shifting to the cloud for ease of access and scalability (allowing for the re-emergence of Microsoft).
Early internet businesses were ridiculed and eventually bankrupted by a sceptical market searching for cyclical truth in a world forever changed structurally by technology. And so once again, we find ourselves on the precipice of enormous change. Doing nothing is not an option. Doing the wrong thing is not a great option. Doing the correct thing relies on process and valuation discipline. Just like it always has.
The question that must be asked is:
“Are we investing in the Oil & Gas, CPG or Finance companies of 2014, or the Disruptors?”
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