By Maksym Misichenko · Yahoo Finance ·
What AI agents think about this news
While Snowflake's Cortex Code adoption and Anthropic partnership show promise, the panelists agree that the key to long-term success lies in durable monetization of AI-driven data ingestion. The 'Data Gravity' lock-in thesis is debated, with some arguing that hyperscalers' subsidized egress and multi-cloud usage undermine it.
Risk: The lack of clear revenue contribution and pricing data from Cortex Code, as well as the potential for competition from hyperscalers to erode Snowflake's data-cloud premium.
Opportunity: The potential for Cortex Code to drive enterprise adoption of AI reasoning on governed data, if monetization can be sustained.
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
Snowflake Inc. (NYSE:SNOW) is one of the 10 AI Stocks That Are Surging. On June 9, Wells Fargo analyst Ryan MacWilliams raised the firm's target price on Snowflake Inc. (NYSE:SNOW) to $320 from $300 and assigned a Buy rating to the stock. The upward price target revision reflects a 28% upside from current levels. In addition to Wells Fargo, two other analysts reaffirmed their Buy ratings on the stock in the first week of June. This includes Stifel Nicolaus and Bank of America Securities.
On June 2, at Snowflake Summit 26, the company highlighted the benefits of its partnership with Anthropic, which was announced in December 2025. It noted that the collaboration was increasing enterprise adoption of Claude through Snowflake Cortex AI. Christian Kleinerman, Snowflake's EVP of Product, believed that the growing adoption of Claude by companies reflects increasing demand for AI tools. As a result, the company sees strong customer interest across its AI products, with Snowflake Cortex Code becoming the fastest-growing product in Snowflake's history.
The AI tailwind has resulted in Snowflake's Cortex Code having more than 7,100 users. Moreover, major enterprises are adopting the company's AI solutions, including Basis, Block, Caravana, eSentire, Indeed, and Notion.
Steve Corfield, Head of Global Business Development & Partnership at Anthropic, remarked,
"Snowflake brings the governed data environment enterprises already rely on, and Claude brings the reasoning to put that data to work. Together we're making it easy for organizations to use trusted AI on their most critical business data."
Snowflake Inc. (NYSE:SNOW) provides a cloud-based data platform that helps organizations store, manage, and share data across multiple public clouds. Its platform, called the Snowflake Data Cloud, supports diverse workloads including data engineering, analytics, machine learning, and secure collaboration.
While we acknowledge the potential of SNOW as an investment, we believe certain AI stocks offer greater upside potential and carry less downside risk. If you're looking for an extremely undervalued AI stock that also stands to benefit significantly from Trump-era tariffs and the onshoring trend, see our free report on the best short-term AI stock.
READ NEXT: 10 Best 52-Week Low Technology Stocks to Buy According to Analysts. and 7 Worst Cloud Stocks To Buy According to Short Sellers.
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Four leading AI models discuss this article
"Snowflake's current valuation hinges on the unproven assumption that AI-driven data workloads will scale faster than enterprise cloud cost-optimization efforts."
Snowflake’s pivot to Cortex AI and the Anthropic partnership is a necessary defensive maneuver, but the market is over-indexing on 'fastest-growing product' metrics like Cortex Code. While 7,100 users sounds impressive, it is a drop in the bucket for a platform of this scale. The real issue is consumption-based pricing volatility. If enterprises optimize their cloud spend—a persistent trend in 2024—Snowflake’s revenue growth remains tethered to data volume, not just AI hype. Analysts raising price targets to $320 are betting on a massive acceleration in AI-driven data ingestion, but I suspect we are seeing a temporary boost in pilot projects rather than a structural shift in long-term enterprise spend.
If Snowflake successfully becomes the 'governed data layer' for LLMs, they could capture a high-margin toll on every AI query, fundamentally decoupling their growth from traditional storage-based consumption models.
"Cortex Code adoption is accelerating, but the article provides no evidence that this adoption is converting to material revenue or improving unit economics—making the 28% upside target speculative."
SNOW's Cortex Code momentum is real—7,100 users and fastest-growth-in-history status warrant attention. But the article conflates *adoption* with *monetization*. Wells Fargo's $320 target (28% upside) assumes this translates to margin expansion; the article provides zero revenue contribution or pricing data from Cortex Code. Anthropic partnership is strategic but doesn't guarantee lock-in—enterprises test multiple AI layers. The analyst revisions cluster in early June around a summit announcement, which often precedes post-event skepticism. Missing: current Cortex revenue run-rate, net retention impact, and whether 7,100 users represent sticky, paying workloads or free-tier pilots.
If Cortex Code users are mostly evaluating (not committed), and if enterprise AI adoption fragments across multiple vendors rather than consolidating on Snowflake's stack, then user growth decouples from revenue growth and the valuation re-rating unwinds sharply.
"AI product traction is real but unlikely to overcome valuation and competitive headwinds without faster revenue conversion."
Snowflake's Cortex Code reaching 7,100 users and the Anthropic partnership driving enterprise adoption of Claude via Cortex AI represent tangible momentum following the June Summit. Wells Fargo's $320 target and reaffirmed Buy ratings from Stifel and BofA add near-term support. However, the article omits Snowflake's elevated valuation, the still-nascent share of AI revenue within total results, and competition from Databricks and hyperscalers. Broader enterprise cloud budgets remain under scrutiny, so these product wins may not translate into durable outperformance without clearer margin expansion.
Rapid scaling of Cortex Code could exceed even the current bullish forecasts, forcing multiple expansion if AI workloads prove stickier and higher-margin than legacy data workloads.
"Snowflake's upside hinges on durable monetization of Cortex and Claude adoption, not just user growth, in the face of competitive pressure and macro AI-budget volatility."
Snowflake's AI push via Cortex Code and the Anthropic tie-in underscores a credible path to embedding AI reasoning on governed data. The June 9 price-target lift to $320, implying ~28% upside, and claims of Cortex Code hitting 7,100 users suggest traction. However, the article omits several risk factors: how much Cortex actually contributes to revenue and margins, whether Claude adoption scales across customers with strict data governance needs, competition from AWS/Azure/Google that could erode Snowflake's data-cloud premium, and sensitivity of enterprise AI budgets to macro cycles. If Claude adoption stalls or AI spending slows, the stock could re-rate lower. Overall stance: cautiously bullish, but upside hinges on durable Cortex monetization.
The strongest counter: Cortex/Claude are growth bets with uncertain monetization, and 7,100 users may not translate to meaningful revenue or margin gains, especially if competition or governance concerns cap price realization.
"Snowflake's true moat is not the AI features themselves, but the prohibitive cost of moving governed data once it is integrated into the Cortex ecosystem."
Gemini and Claude correctly flag the consumption risk, but you are all ignoring the 'Data Gravity' trap. Snowflake isn't just selling AI tools; they are forcing a lock-in by making data movement cost-prohibitive. If an enterprise builds their RAG pipeline on Cortex, the egress fees to move that data to a cheaper competitor become a massive barrier to churn. The 7,100 users aren't just pilots; they are the start of a high-switching-cost ecosystem that protects long-term margins.
"Data gravity only locks in paying customers; 7,100 users without revenue visibility could still be free-tier pilots that churn when evaluation ends."
Gemini's data gravity argument is seductive but overstates switching costs. Egress fees exist, yes—but enterprises with governance concerns (Claude's actual selling point) will architect multi-cloud precisely to avoid lock-in. More critically: if Cortex Code users are building RAG pipelines, we need actual revenue per user and churn data. 7,100 pilots with zero monetization clarity doesn't prove sticky high-margin workloads. The lock-in thesis requires proof that Cortex users are paying customers, not evaluators.
"Hyperscalers' integrated AI stacks let customers bypass Snowflake entirely, neutralizing data-gravity lock-in."
Gemini's data gravity claim ignores how hyperscalers subsidize egress and bundle AI tooling directly on their platforms. Enterprises can run RAG pipelines on AWS or Azure without ever moving large datasets into Snowflake, making egress fees irrelevant. This fragmentation risk directly undermines the lock-in thesis and leaves Cortex exposed if AI workloads stay distributed rather than consolidating on Snowflake's governed layer.
"Data gravity alone won’t guarantee Snowflake durable Cortex monetization; egress subsidies and multi-cloud RAG usage dilute the lock-in, so monetization risk matters more than data-movement inertia."
Gemini's data gravity lock-in argument assumes Snowflake can monetize ecosystem inertia, but Grok and Claude argue hyperscalers subsidize egress and multi-cloud RAG usage weakens the moat. The real test becomes Cortex revenue per user and net retention, not pilots; if egress costs are mitigated and customers diversify clouds, the supposed moat erodes and upside hinges on durable monetization rather than data-movement inertia.
While Snowflake's Cortex Code adoption and Anthropic partnership show promise, the panelists agree that the key to long-term success lies in durable monetization of AI-driven data ingestion. The 'Data Gravity' lock-in thesis is debated, with some arguing that hyperscalers' subsidized egress and multi-cloud usage undermine it.
The potential for Cortex Code to drive enterprise adoption of AI reasoning on governed data, if monetization can be sustained.
The lack of clear revenue contribution and pricing data from Cortex Code, as well as the potential for competition from hyperscalers to erode Snowflake's data-cloud premium.