This Wall Street firm’s warnings about the impacts of AI disruption sent ripples through markets this week!

Warnings about the impacts of AI disruption have been made, but there was one warning that appeared to have a greater impact on equity markets than most others (at least recently). A blog post published by Wall Street firm Citrini Research, little known prior to the post, was attributed to an 800 ooint drop in the Dow Jones back on Monday as well as an even bigger impact on software stocks.

We’ve read it ourselves and we think there are two reasons why this stands out from other warnings about AI and why investors should pay attention to it. First, because it warns the disruption could be closer than we think – it is a look back from June 2028 (just over 2 years from now!). Second, it specifically points out the business models that could be under threat…and some of them are businesses investors may not have thought of.

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Citrini’s warnings about the impacts of AI disruption stood out

Citrini’s research was not new in predicting higher white collar unemployment or a potential impact on the stock market. But it arguably raised a point that may may not have thought of. Namely, that they are responsible for such a high proportion of consumer spending, at least in the US. And even if the impact is felt more slowly than blue collar employment, it gradually happens and persists if their income permanently drops.

But as we noted, Citrini said the impact of AI disruption would happen fast – opening the piece with the sentence,’ The unemployment rate printed 10.2% this morning’. Now of course the rate could be worse, but it is far higher than unemployment now, and it is not just about how many would be unemployed, but who. ‘These are the people who buy the houses, the cars, the vacations, the restaurant meals, the private school tuition, the home renovations’. But hey, AI machines spend a lot on discretionary goods just as much, right? … Right? Citadel was not so confident saying,’ Hint: it’s zero’.

There have been doom and gloom warnings about disruptions that did not come to pass in that technology made just as many jobs as it eradicated, like ATMs let bank tellers do other things. But every new job needed a human to perform it, but AI improves the tasks humans would redeploy to. ‘Displaced coders cannot simply move to AI management because AI is already capable of that’.

‘AI has created new jobs…humans are still in the loop…[but] for every new role AI created, though, it rendered dozens obselete. The new roles paid a fraction of what the old ones did’.

The report also predicted business models that would be threatened. In essence, any that act as intermediaries and/or reduce complexity. But think specifically.

The 6 business models under threat

1. SaaS products

In a world where apps can be built from scratch by anyone without knowing how to code personally, how can firms justify paying for them? Citrini said,’ That summer [2026], we spoke with a procurement manager at a Fortune 500. He told us about one of his budget negotiations. The salesperson had expected to run the same playbook as last year: a 5% annual price increase, the standard “your team depends on us” pitch’.

‘The procurement manager told him he’d been in conversations with OpenAI about having their “forward deployed engineers” use AI tools to replace the vendor entirely. They renewed at a 30% discount. That was a good outcome, he said. The “long-tail of SaaS”, like Monday.com, Zapier and Asana, had it much worse’.

Now Citrini still said SaaS was not completely dead and there was value in running a cost-benefit analysis to in-house vs external, but now there is the option of doing it in-house for free. So incumbants would (in this scenario) have to engage in a cut-throat race to the bottom. It is all well and good to say clients that cut 15% of the workforce can boost margins, but that is not just the cost of the people but the licenses for those people.

2. Any company with a subscription and membership model

What a good business model it is. Give a ‘free trial’ with a card, and then people are locked in unless they cancel their credit card. The whole ‘Average Customer Lifetime Value’ was premised around it. As was noted,’ humans don’t really have the time to price-match across five competing platforms before buying a box of protein bars’, but,’ machines do’. One example was insurance renewals – agents that re-shop coverage would dismantle 15-20% of premiums that insurers earned from passive renewals. As nothing is tedious, any subscription helping people navigate what was tedious would be in trouble.

3. Travel booking platforms

This was singled out as an early casualty. ‘By Q4 2026, our agents could assemble a complete itinerary (flights, hotels, ground transport, loyalty optimisation, budget constraints, refunds) faster and cheaper than any platform,’ Citrini asserted. At least our home grown Flight Centre (ASX:FLT) has benefited from Corporate Travel Management (ASX:CTD) customers pivoting across to it for obvious reasons.

4. Realtors or real estate agents

The whole business model is a percentage of the sale on houses. Even in a world where people could theoretically sell and market houses online, it was about getting the best deal. What realtors had was information asymmetry, but it would crumble once AI agents with this data could replicate it. Citrini predicted a huge compression in margins and growth in transactions with no human agent.

5. Food delivery apps…

…and DoorDash was specifically named. What?! Don’t people need food? Isn’t there a whole moat that is,’ You’re hungry, you’re lazy and this is the app on your home screen’!?.

The first two parts of that are true, but as was noted by Citrini,’ AI agents optimising for price and fit do not care about your favourite app or the websites you’ve been habitually opening for the last four years, nor feel the pull of a well-designed checkout experience. They don’t get tired and accept the easiest option or default to “I always just order from here”.

‘It [the agent] checks DoorDash, Uber Eats, the restaurant’s own site, and twenty new vibe-coded alternatives so it can pick the lowest fee and fastest delivery every time. Habitual app loyalty, the entire basis of the business model, simply didn’t exist for a machine’.

‘Multi-app dashboards let gig workers track incoming jobs from twenty or thirty platforms at once, eliminating the lock-in that the incumbents depended on. The market fragmented overnight and margins compressed to nearly nothing’.

6. The credit/debit card model

Cards like Visa and Mastercards charge an interchange rate in machine to machine commerce. With people looking for faster and cheaper options, the report speculated that agents (wanting a bigger part of the transaction given they control it) that they would use stablecoins via Solana or Etherium L2s where settlement would be near-instant and the transaction cost would be measured in fractions of a penny.

The Citrini report did not just warn about Visa and Mastercard, but American Express too given white-collar workforce reductions, but also rewards programs funded by the merchant subsidy.

Conclusion

We’d encourage investors to read the report themselves. There is a lot more there, including predictions of a mortgage crisis that would arise at this point given white-collar unemployment and potentially big tech defaults.

But for now, we saw the most value in extracting the sectors/business models that could  be threatened. Investors should see whether any of these are true in relation to any of their companies, and if not, what they are doing to give themselves the best chance of survival.