Friends, chip stocks are slammed, semi space is a sea of red. Broadcom couldn't meet market's high expectations for AI chips, making the tech sector seem like it suddenly lost power. One day it's a compute feast, the next day your account gets served a cold plate of reality.
But here's the interesting part: While hardware gets valuation compression, AI software stocks are beginning to recover. ServiceNow shows strength, Snowflake's data platform logic continues to attract funds, Palantir's AIP order narrative is still brewing, and Datadog, CrowdStrike, Zscaler, Cloudflare—key nodes in the AI software chain—are being re-examined by the market.
So in this episode, we won't broadly discuss "Can AI software stocks take over?" That statement is too big and too vague. Instead, we ask a sharper question: After the tech stock plunge, what is capital looking for? My judgment: capital is looking for enterprise AI budget entry points. What does that mean? In the past, capital bought AI as GPU, chips, servers, data centers. But now, the market asks: After enterprises spent heavily on compute, how does AI actually enter real business? Who can embed AI into enterprise workflows? Who can help enterprises mobilize data? Who can get AI into contracts, budgets, revenue, and eventually earnings? That's the core theme today: ServiceNow leads the AI software rebound not because the market suddenly starts buying software stocks again, but because capital is rediscovering the entry points for enterprise AI deployment.
I'm Alan Talks Finance. If you're tracking AI software stocks, first like and save this video. Because the framework ahead not only applies to ServiceNow but will affect Palantir, Snowflake, Datadog, CrowdStrike, Zscaler, Cloudflare and their subsequent rhythms.
First, overall market: AI software stocks have indeed warmed up today, but don't interpret it as all AI software stocks throwing a party again. The market is clearly more discerning than before. Previously, if a company added "AI" to its product description and mentioned "Agent" on earnings calls, investors would automatically imagine "Is this the next ten-bagger?" Not anymore. The market now questions like a budget review: Are customers actually using this AI feature? Did they upgrade their plans? Did it boost renewals? Drive new orders? Improve growth guidance? Make the company more profitable? So today's AI software stock rebound isn't just a dead cat bounce. It's more like capital re-queuing. Whoever stands at the easiest position for enterprise AI budget to land gets looked at first.
Layer one: enterprise workflow, represented by ServiceNow. Layer two: order fulfillment, represented by Palantir. Layer three: data base, represented by Snowflake. Layer four: monitoring and security, represented by Datadog, CrowdStrike, Zscaler. Layer five: network gateway for AI Agents going online, represented by Cloudflare. These lines are the true core of today's AI software stocks.
The most important one to discuss first is ServiceNow. Why? Because ServiceNow represents not just an AI feature but the entry point for enterprise AI budgets. The places where enterprises willingly spend are: faster processes, fewer tickets, higher customer service efficiency, more automated approvals, less manual IT support, smoother internal collaboration. That's ServiceNow's territory. It already sits inside enterprise workflows—IT service, ticketing, approval, customer service, internal automation—these aren't concepts; they happen every day. If AI Agent only lives in a chat window, it's just an advanced Q&A tool. But if it can enter enterprise workflow, understand context, execute actions, and feed results back into the system, it upgrades from "can chat" to "can do tasks." ServiceNow's re-emergence is about competing for the enterprise AI execution layer entry. When enterprises deploy AI Agents, they can't let them run wild. They need to know where tasks come from, who approves, who executes, when human intervention is needed, how to track issues. ServiceNow's advantage is it already has a seat in enterprise workflows. So the market is repricing not whether ServiceNow has an AI story, but whether when enterprises start paying for AI workflows, ServiceNow becomes the default entry. Of course, don't blindly hype. ServiceNow isn't cheap; the market will keep asking: Are Now Assist features actually driving higher payments? Are customers buying more modules? Is AI expanding contracts? Improving growth expectations? So ServiceNow's key observation point: Are enterprises willing to keep paying for AI workflow?
Next, Palantir. For Palantir, the focus is simple: order verification. What AI software stocks fear most is noisy product launches but quiet customer budgets. Every company talks AI, Agent, and wants to brand itself as the next enterprise OS. But capital markets eventually ask: Did customers actually sign contracts? Palantir AIP's value lies here. It's not just an AI assistant for emails, meeting notes, or PPTs. Palantir's real aim is to embed AI into core operations of enterprises and governments, making AI not just answer questions but participate in real decisions and business execution. That's why the market watches AIP orders, commercial customer expansion, US commercial revenue, and management guidance. It answers: Has AI entered core business? Has AI been budgeted by customers? Has AI moved from demo stage to contract terms? If AIP orders continue to grow, commercial customers expand, US commercial revenue grows fast, Palantir will remain an important barometer for AI software commercialization. But risks are clear: valuation is not cheap; market expectations are very high. High-expectation stocks suffer when they need not just to perform well but to prove they are better than market imagination. Contracts big enough, customer expansion fast enough, guidance strong enough, commercial revenue continuously beating. If any of these falters, stocks may see a scenario where fundamentals haven't broken but expectations collapse first. So Palantir isn't uninteresting, but you can't just watch the story. Watch contracts, commercial revenue, customer expansion, guidance. Those numbers determine if it can sustain its high valuation.
Now Snowflake. We won't stretch too long here because the data base story is well known, but it's still important. For enterprise AI to truly land, the first step isn't connecting a large model; it's getting the company's scattered, messy, permission-complex data into a usable state. Sales, finance, customer service, supply chain each have separate systems; historical data may be in different databases. In that case, making AI Agent directly make decisions isn't improving efficiency—it's packaging existing chaos as smarter. Snowflake's logic is clear: the more enterprises want AI in real business, the more they need a reliable data platform. AI Agent needs data from somewhere, needs data quality for analysis, and needs permission control, governance, audit, and security for enterprise use. So Snowflake isn't just a database story; it's the data foundation that must be prepared before AI deployment. The stronger the foundation, the easier AI applications can be built on top.
Next, Datadog, CrowdStrike, Zscaler—fast breakdown. Datadog represents AI monitoring layer. After enterprises deploy AI Agents, systems become more complex: model calls, API chains, inference costs, response latency, abnormal behavior, permission calls all need monitoring. Datadog sells not AI itself but dashboards, alarms, and logs for AI system operations. AI Agent entering production environment—companies can't just plug it in and hope it works. Who detects anomalies? Who tracks costs? Who locates chain problems? Who tells if an Agent starts going off the rails? That's Datadog's opportunity. The more complex the AI system, the more enterprises need observability. CrowdStrike and Zscaler represent the AI security budget line. As AI Agents enter enterprises, security becomes more complex. Previously, companies managed employee accounts, computers, servers, endpoint devices. Future companies must also manage AI identities. Which AI Agent can access customer data? Call internal APIs? Enter code repositories? Touch financial systems? Send emails automatically? All need clear rules. AI entering enterprise isn't just adding a tool; it's adding a new set of digital executors. More digital executors make permission boundaries more critical. So CrowdStrike, Zscaler have strong long-term logic: the deeper AI penetrates, the larger the attack surface; the more automation, the more critical permission management and threat protection. But be calm: strong AI security demand doesn't mean stocks can ignore price. Security budget growth is one thing; how much expectation is pre-loaded in the stock is another. CrowdStrike's recent market reaction shows investors aren't satisfied with just hearing "security is important." They need to see growth accelerating, customers expanding deployment, margins holding, guidance continuing to impress. So security lines aren't uninteresting, but distinguish: demand is long-term logic, price is short-term risk. Good sectors bought at high prices also get punished.
Then Cloudflare. This line becomes more interesting because it represents the traffic gateway for AI Agents online. Previously many saw Cloudflare as CDN, website acceleration, DDoS protection, network security. These matter but didn't sound exciting. Now Cloudflare's narrative is changing. CEO Matthew Prince recently noted that bot traffic has exceeded human traffic (to clarify: this is Web HTTP requests, not all internet traffic). This signal is important. If AI Agents truly become new internet users, they will access websites, call APIs, fetch data, execute tasks, submit requests, even complete full chains of operations for users. Then a new problem arises: who determines if this Agent is normal or malicious? Who manages these automated requests? Who protects websites from being crushed by AI crawlers? Who provides identity verification and access control? Who ensures Agent tasks are stable, low-latency, and traceable? That's the position Cloudflare aims to capture. It doesn't build large models or sell GPUs. It's more like the network gateway, traffic dispatcher, and identity checkpoint for the Agentic Web era. AI Agent not only needs model capabilities but also traffic rules, access permissions, network stability, and security boundaries. Cloudflare bets on this new internet order. If AI Agents go online en masse, Cloudflare's value goes beyond website acceleration—it could become the entry point for AI Agent traffic governance. But don't oversell the story. Cloudflare must prove that these Agent traffic governance needs can truly become revenue. Bot Management, Zero Trust, edge security, API protection, Agent governance all have imagination space, but the market ultimately asks: Are customers paying? Are contracts expanding? Is revenue accelerating? Are margins holding? If only traffic increases and costs rise but customers aren't willing to pay more, the story will be discounted. So Cloudflare's key isn't novelty of concept but whether it can turn AI Agent traffic into a must-pay infrastructure for enterprises.
Finally, Microsoft ecosystem. Microsoft's Copilot, Agent, Azure, GitHub, Office essentially embed AI into default enterprise entry points for office, development, and cloud. Microsoft's significance to the entire AI software sector goes beyond its own size. More importantly, it's changing how enterprises use AI software. Previously, enterprises bought software as standalone features. In the future, they may buy an entire AI-enabled work environment: AI in office (Copilot), AI in development (GitHub), AI in cloud (Azure), database, identity, permissions, enterprise documents and processes all connected by AI. This will continue to fuel market imagination for Agentic AI software ecosystem. Once enterprises accept "AI as work entry," the entire software ecosystem will be revalued. ServiceNow captures workflow; Palantir captures orders and core operations; Snowflake captures data; Datadog captures monitoring; CrowdStrike and Zscaler capture security; Cloudflare captures network entry; Microsoft captures platform ecosystem. That's the layered framework for AI software stocks.
So what is capital looking at? In the past, capital bought AI as compute expansion. Now capital is examining whether AI can actually become a business. Who can sell AI into enterprises? Who can get AI into workflows? Who can get AI to call data? Who can make AI run securely? Who can make AI's operational status monitorable? Who can make AI Agents stably execute tasks on the internet? This is the shift from hardware theme to software application theme. But not all software stocks benefit from this shift. Truly benefiting are companies positioned at key nodes of enterprise AI deployment: workflow entry (ServiceNow), real orders (Palantir), data base (Snowflake), security budget line (CrowdStrike, Zscaler), monitoring capability (Datadog), network gateway (Cloudflare). In short, capital isn't buying "software stocks" generically; it's buying key chokepoints in the AI deployment chain.
But risks must be put on the table. First, valuations are still not cheap. Many AI software stocks have already rebounded a lot; this isn't a stage of bargain hunting. You're buying not panic at lows but expectations of future re-rating. Second, pure concept stocks may continue to diverge. Companies that just shout AI without orders, revenue, customer expansion will likely be pushed back to the bench. Third, earnings verification is critical. The market can rush in on a new narrative, but won't stay in imagination forever. Ultimately, it's about revenue, profit, customer expansion, renewals, and guidance. Fourth, the interest rate environment will still pressure high-valuation software stocks. If Treasury yields continue to rise, high-growth stocks will get marked down. No matter how big the AI story, it must face the yardstick of valuation models.
So ordinary investors should watch five lines: enterprise workflow (ServiceNow), order fulfillment (Palantir), data base (Snowflake), security budget line (CrowdStrike, Zscaler), monitoring and network infrastructure (Datadog, Cloudflare). But remember, not all AI software stocks will take off. The more likely scenario is divergence, not universal rally. Strong names will be continuously researched; weak ones will be gradually ignored.
Key takeaways: Friday's tech stock plunge isn't necessarily the end of AI rally. It's more a reminder that AI trading can't be limited to chips, compute, or hardware. Next stage, capital will care more about how AI lands, how it's charged, how it enters contracts and earnings. ServiceNow for workflow; Palantir for orders; Snowflake for data; Datadog for monitoring; CrowdStrike/Zscaler for security; Cloudflare for Agentic Web traffic gateway; Microsoft for platform ecosystem. That's why Agentic AI is being revalued by capital. But the companies that will survive this cycle aren't the ones that shouted AI the loudest, but those that turned AI into customer budgets, enterprise processes, real revenue, and profit growth. The most practical reality: when markets are hot, they listen to stories; when they cool off, they only care about numbers. Who can produce orders, renewals, margins, and customer expansion gets to stay at the main table.
If you found this episode valuable, remember to like, save, and subscribe to Alan Talks Finance. Also feel free to comment: which AI software line do you like best—workflow, data, orders, security, monitoring, or Cloudflare-type Agentic Web traffic gateway? Next episode, we'll continue breaking down potential underestimated dark horses in AI software stocks. See you next time.
