News

• Disruption fears stay loud, but customer commitments stay real, which is the first sign the model still works.

• Snowflake benefits from the “AI needs data” flywheel, yet guidance tone still drives near-term sentiment.

• Salesforce proves paid AI is moving beyond demos, but investors still watch for seat compression and pricing pressure.

Snowflake and Salesforce just gave investors something rare in an AI-driven market: fresh evidence. The debate is loud, but the questions are simple. Does artificial intelligence (AI) make software easier to replace. Does it shrink pricing power. Or does it increase demand for the platforms that make AI useful.

This review uses the same lenses from our software as a service (SaaS) disruption shortlist.

Our disruption shortlist is not a “winners and losers” list. It is a way to ask better questions. Earnings are useful because they force management to answer those questions with numbers, customer language, and guidance.

Four lenses matter most for long-term investors:

First, pricing mechanics. Seat-based pricing depends on how many people log in. Task-based pricing depends on how much work gets done. AI agents can reduce seats, but they can also create new tasks.

Second, bundling pressure. When a large platform adds “good enough” features, point tools can lose pricing power even if the product is still good.

Third, proof of paid AI. Demos are easy. Paid add-ons and recurring revenue are harder, and more informative.

Fourth, forward demand. Bookings and backlog measures help you see what customers commit to, not just what they used last quarter.

With that in mind, Snowflake and Salesforce tell two different, but connected stories.

Snowflake: the “picks and shovels” case, with one catch

Snowflake sells cloud software that helps companies store, organise, and analyse data. If AI is a new engine, data is still the fuel. That puts Snowflake closer to “enabler” than “victim”.

The headline from the release is that demand looks healthy and customer commitments beat expectations, according to data compiled by Bloomberg. That matters because disruption fears often start with a scary assumption: “customers will pause spending until the dust settles”. Snowflake does not show that kind of freeze.

The softer part is guidance tone. Management guides next quarter product revenue roughly in line with Bloomberg consensus. In a calm market, “in line” is fine. In a nervous market, “in line” can feel like “not enough”, especially when investors want a bold statement that AI demand is accelerating right now.

Snowflake’s strategic message is also clear: it keeps expanding the product set, especially AI tools that sit on top of data already in the platform. AI revenue is still early, with the company previously pointing to about 100 million USD in annual revenue run rate for AI products. That is encouraging, but it also tells you why the stock reaction can be fussy. The promise is big, the proof is still building.

Snowflake’s main risk is not that AI replaces it. The risk is that large platforms bundle more data tooling into broader cloud contracts, turning “best of breed” into “nice to have”. Snowflake must keep earning the right to be the specialised layer.

Salesforce: strong AI traction, but the market wants a cleaner growth story

Salesforce is the leading customer relationship management (CRM) software company. It runs sales and service workflows for many large firms. That scale is an advantage, but the pricing model creates a classic disruption worry: if AI agents do more work, customers may need fewer human users, and therefore fewer seats.

This is why Salesforce sits in a tricky middle ground. It can benefit from AI adoption, yet it also has more to defend. The quarter itself reads well, but guidance lands as lukewarm, and that is what drives the narrative.

The key positive is that Salesforce puts real weight behind Agentforce, its AI agent product. Management says Agentforce annual recurring revenue (ARR) reaches 800 million USD, up 169% year on year, and it highlights a rising count of Agentforce deals. That is the kind of data point our shortlist lens looks for. It signals that AI is moving from “feature” to “paid product”.

The key question is what happens next. Salesforce talks about organic growth re-acceleration later in the year. Investors hear a different subtext: “show me that AI adds revenue, not just buzzwords”. This matters because AI can push pricing in two directions at once. It can expand value if customers pay for outcomes. It can compress value if customers cut seats and negotiate harder.

Salesforce also leans on customer commitments, pointing to remaining performance obligations (RPO), a future revenue indicator. In a market obsessed with disruption, those commitments are a quiet counterpoint: customers still sign multi-year deals when the platform is deeply embedded.

Risks: where the story can still turn

The first risk is budgeting, not technology. If enterprise spending tightens, consumption and new projects slow quickly, even if the product remains strategically important.

The second risk is bundling. AI makes it easier for bigger platforms to ship “good enough” features faster, which can pressure pricing across SaaS.

The third risk is measurement. If companies talk a lot about AI but show little paid adoption, the market’s patience can run out fast. Watch for vague language that replaces clear metrics.

Investor playbook

• Track customer commitments like RPO and renewals. They show real confidence, not only usage.

• Separate “AI trials” from “paid AI”. Look for recurring revenue, not just product announcements.

• Listen for pricing shifts from seats to tasks. It often signals where value is moving.

• Watch bundling signals. When platforms include features for “free”, standalone tools must prove differentiation.

The obituary is early, but the checklist stays

AI has turned software investing into a weekly debate club. These two earnings calls drag it back to something more useful: what customers commit to, and what they actually pay for. Snowflake looks like plumbing for the AI era, but investors still want guidance that feels bolder than “fine”. Salesforce shows that AI can be monetised, yet the market still asks whether agents add revenue faster than they compress seats.

The neat takeaway is not that SaaS is dead, or saved. It is that disruption is a process, not a headline. Earnings are the weather report. The long-term climate still depends on pricing power, product relevance, and execution. This material is marketing content and should not be regarded as investment advice. Trading financial instruments carries risks and historic performance is not a guarantee of future results. The instrument(s) referenced in this content may be issued by a partner, from whom Saxo receives promotional fees, payment or retrocessions. While Saxo may receive compensation from these partnerships, all content is created with the aim of providing clients with valuable information and options.