Outrageous Predictions
Die Grüne Revolution der Schweiz: 30 Milliarden Franken-Initiative bis 2050
Katrin Wagner
Head of Investment Content Switzerland
Investment Strategist
SaaS weakness reflects tighter expectations, not a collapse in fundamentals.
AI is shifting value from software pricing to hardware capacity and supply.
Markets are rewarding scarcity in chips while questioning growth in software.
Software stocks were meant to be the cleanest story in markets. Predictable revenue, steady growth, and high margins. It felt simple. Right now, it does not feel simple at all. Recent earnings from names like ServiceNow and Adobe have triggered sharp share price reactions. Not because the numbers were disastrous, but because they were not strong enough.
At the same time, parts of the semiconductor world are holding up better. Companies like Intel and Texas Instruments are benefiting from a different kind of question. Not “will customers pay more?” but “who can actually supply what is needed?”
That contrast tells a bigger story. The artificial intelligence trade is not disappearing. It is shifting.
SaaS, or software as a service, has long been valued on future potential. Investors paid for growth that was expected to continue almost automatically. That expectation is now being tested. Companies are still growing, but at a slower pace. Customers are more careful. Deals take longer. Expansion within existing clients is not as strong as before.
One key measure is net revenue retention. This shows how much existing customers increase their spending over time. For many SaaS firms, this number is drifting lower. The reason is simple. Businesses are reviewing costs. Software budgets are no longer treated as untouchable.
There is also a quiet shift in competition. Large platforms such as Microsoft and Alphabet are bundling more features into their ecosystems. Tools that once justified separate subscriptions are increasingly included as part of a broader offering.
This puts pressure on pricing power. Still, it is important to stay grounded. Many SaaS companies continue to grow at healthy rates. Their margins remain strong. Recurring revenue is still more stable than most business models.
The issue is not that SaaS is breaking. It is that expectations are tightening faster than the businesses are changing.
While software faces questions about pricing and demand, hardware tells a different story. Semiconductors are physical. They require factories, supply chains, and years of investment. They cannot be copied overnight.
That creates scarcity. Artificial intelligence is not just a software story. It is also about data centres, power systems, and the chips that make everything run. This is where companies like Intel and Texas Instruments come in.
Intel is working to rebuild its position in advanced chips and manufacturing. It sits closer to the large-scale infrastructure needed to train and run AI systems.
Texas Instruments operates in a quieter part of the market. It produces analogue and embedded chips, the components that help machines sense, control, and manage power. These chips are found in cars, factories, and industrial systems. Not exciting, but essential.
This difference matters. Software can often be replicated or bundled into larger platforms. Hardware cannot. If demand rises, supply takes time to catch up. That gives chipmakers a different kind of pricing power.
In simple terms, software is facing substitution risk. Hardware is facing capacity constraints. Markets are responding accordingly.
The recent split between SaaS and semiconductors reflects a deeper change. Investors are moving away from broad narratives and towards practical economics. In software, the key question is whether companies can maintain pricing power and steady expansion.
In hardware, the question is whether supply can meet demand, and at what cost. Both sectors are tied to artificial intelligence, but they sit at different points in the value chain. One is closer to the user. The other is closer to the infrastructure.
Right now, infrastructure looks more tangible. That does not mean hardware is safer. Semiconductor businesses are cyclical. Demand can rise quickly, but it can also fall. Overinvestment is always a risk. It simply means the current phase of the AI cycle is rewarding what is hardest to replicate.
There are risks on both sides of this divide.
For SaaS, the main concern is that slower growth becomes structural. If customers continue to reduce spending or switch to bundled solutions, pricing power could weaken more than expected. For hardware, the risk is the opposite. If companies build too much capacity, the industry could face oversupply. That would pressure margins and returns.
There is also a broader risk. If economic conditions deteriorate, both software spending and hardware demand could slow at the same time. Early signals often appear in guidance, order trends, and how companies talk about demand. Tone matters as much as numbers.
At first glance, the recent moves look like a simple rotation. Software down, hardware up. It is more interesting than that. The market is not rejecting artificial intelligence. It is refining how it values it. The focus is shifting from what AI can do to what it requires. Software shows the promise. Hardware carries the cost.
That brings us back to the starting point. Software once felt like the easiest story in markets. Today, it requires more explanation. Hardware, often overlooked, is gaining attention because it is harder to ignore.
For long-term investors, this is not about choosing one over the other. It is about understanding where value is building in each phase of the cycle. The glow around SaaS may have dimmed, but the broader AI story has not. It has simply moved deeper into the system, where scarcity, not just innovation, decides who gets paid.
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