If you’ve been watching SaaS and tech stocks lately and thinking, “Eh… why everything red one ah?”, you’re not imagining things.
This week felt less like a normal market pullback and more like the moment when investors suddenly stood up, looked around, and realised the game has changed. Software stocks sold off. Tech giants wobbled. Even “AI darlings” got whacked.
And no – this is not the market saying AI is over.
It’s something much more unsettling.
The market is starting to realise that AI isn’t just boosting tech.
It’s threatening parts of tech – sooner than expected.
Over the past week, US SaaS and tech stocks have come under heavy pressure.
The Nasdaq slid across multiple sessions, while software and data-focused companies were hit even harder than Big Tech.
At first glance, it looks confusing. AI spending is exploding. Cloud revenues are still growing. So why are investors suddenly dumping software stocks?
A few things happened almost at once.
First, Big Tech shocked markets with the sheer scale of AI spending.
Amazon, Microsoft, Google and Meta collectively signalled plans to pour hundreds of billions of dollars into AI infrastructure – data centres, chips, and compute power – in a single year.
This isn’t incremental spending. It’s a full-blown arms race.
Normally, that would be bullish. But investors are now asking a harder question: how long before all this spending actually turns into profits?
Second, earnings season shifted the focus away from growth and towards costs.
When companies like Amazon and Microsoft reported results, revenue was solid – but what stood out was how fast capital expenditure is rising, and how uncertain the return timeline is.
Third – and this is the real trigger – a new fear entered the market.
AI isn’t just helping software companies anymore. It may be replacing some of them.
The catalyst was Anthropic, which released new enterprise tools that automate tasks in coding, legal work, marketing, finance, and customer support. These aren’t consumer toys.
They go straight after billable white-collar work.
Markets reacted immediately. Data and analytics firms sold off. Legal and publishing-related software companies dropped double digits. Advertising and information services names followed.
The message from investors was clear: if AI can do these jobs directly, what happens to the software companies that used to sell tools to support them?
This sell-off is being misunderstood.
The market is not saying “AI is over”.
The market is saying AI is arriving faster – and more aggressively – than many SaaS business models were built for.
For the last decade, SaaS was priced like a dream:
- Predictable subscriptions
- Sticky customers
- Pricing power
- Great margins
- Long visibility on earnings
AI challenges those assumptions.
If an AI system can replace multiple SaaS tools, or reduce headcount instead of supporting it, companies may start questioning how many subscriptions they really need.
That creates uncertainty around renewals, pricing, and long-term margins – even if revenue today still looks fine.
At the same time, Big Tech is doubling down. The hyperscalers are spending more, not less, because they believe AI usage will explode across every industry. That’s why this isn’t an “AI bubble popping” story.
It’s a value redistribution story.
Some tech companies will capture enormous value. Some will get squeezed. And public markets hate not knowing which is which.
Add in weak US jobs data, rising volatility, and investors already heavily positioned in “quality SaaS”, and you get what we’re seeing now: a fast, brutal repricing.
This is what real technological transitions look like. Not smooth charts up and to the right – but violent moments where assumptions get questioned all at once.
Let me make this very real and very personal.
I started Dollar Bureau about 6 years ago. Back then, running a business meant stacking software on software.
One tool for email. One for CRM. One for landing pages. One for basic legal templates. One for ops. One for analytics.
Plus freelancers. Plus developers. Every new idea meant another subscription, another invoice, another dependency.
Fast forward to after ChatGPT launched – and especially once “vibe coding” became a thing – and my entire operating model changed.
- I cancelled subscriptions.
- I stopped buying new software.
- I stopped engaging developers for small builds.
Today, I automate large parts of my legal workflows, marketing processes, internal tools, and even basic coding myself using AI. Things that used to take weeks and cost thousands now take hours and cost close to nothing.
And I’m not a tech giant. I’m a tiny business owner in Singapore.
Now zoom out.
If I can do this at a small scale, imagine what happens when:
- Mid-sized companies with 200 to 500 staff rethink their workflows
- Large corporates with thousands of employees decide to revamp entire departments
- Finance, legal, HR, marketing, ops and analytics teams start deploying AI agents end-to-end
The implications are uncomfortable:
- Fewer hires
- Fewer software licences
- Fewer “nice-to-have” SaaS tools
- More pressure on pricing and renewals
This is why I agree with the market on one thing: many software and SaaS companies are genuinely in trouble.
Especially:
- Tools that are easily replicated with vibe coding
- Point solutions that don’t integrate well with others
- Software that exists mainly to “assist” humans rather than replace workflows
That doesn’t mean all SaaS is doomed. But it does mean the old assumption – that software subscriptions only ever go up – is no longer safe.
For investors, this creates a dangerous temptation.
When prices fall, everyone wants to “buy the dip”. But in a structural shift like this, buying the wrong dip doesn’t just hurt – it burns a hole in your wallet.
Some companies won’t bounce. Some business models won’t recover. Some revenue streams are quietly being automated away.
This is why, for most investors, the smarter move isn’t trying to outguess which SaaS name survives.
It’s diversification. That means:
- Avoid over-concentrating in US tech or SaaS-heavy themes
- Balance growth exposure with sectors that benefit from productivity gains rather than get disrupted by them
- Use diversified funds that spread risk across regions, sectors, and business models – instead of betting on single winners
AI will create enormous value. But that value won’t be evenly distributed, and public markets are still figuring out who keeps what.
This is exactly why, over the past few months, I’ve been actively helping my clients shift into a more defensive posture – without abandoning growth altogether.
We’re rebalancing across regions and sectors, reducing over-concentration in any single tech or SaaS narrative, and being much more selective about where tech exposure sits in the portfolio.
I still believe AI has a very long runway ahead. But I also believe the journey will be volatile, uneven, and unforgiving to the wrong business models.
So instead of betting everything on a handful of “discounted” tech stocks, we’re taking a more durable approach: diversified core holdings, complemented by tactical exposure to tech and AI themes where the risk-reward makes sense.
If you’re feeling uncertain, overwhelmed, or just want a second pair of eyes on how your investments are positioned in this new AI-driven world, let me help.
You don’t need to invest through an ILP. I work with clients via iFAST, where you get:
- Access to 2,000+ unit trusts, not just what an insurer limits you to
- The ability to start from as low as $100/month
- Full flexibility to increase or decrease your monthly investments anytime
- Lower fees compared to traditional insurance-based solutions
- And most importantly, the freedom to stop or withdraw anytime when times are tough – no lock-ins, no penalties
Fill up this form, quote “FUR” and I’ll help you build a portfolio that’s resilient enough to weather disruption, yet positioned to participate in long-term growth.
The world is changing fast. AI is reshaping everything.
Your investments shouldn’t be stuck in old assumptions.
Stay informed. Stay diversified. And let’s stay invested – wisely, flexibly, and for the long run.