Snowflake Inc. Positions Itself for a Robust Fiscal 2026 Third‑Quarter Report

Snowflake Inc. (NYSE: SNOW) is once again the focal point of equity research as the company prepares to disclose its third‑quarter results for fiscal 2026 on December 3. Analysts across the spectrum have tightened their forecasts, raising price targets and earnings expectations in the wake of the company’s continued dominance in the AI‑enabled data cloud market and its expanding customer base among Fortune 500 enterprises.

Analyst Consensus and Upgrades

  • Price Targets: A majority of research houses have increased their 12‑month price objectives by an average of 8 %, bringing the consensus target to $112.50 per share from a recent baseline of $104.30. The most aggressive upgrade came from Morgan Stanley, which raised its target to $120.00, citing Snowflake’s superior net‑new pipeline in the AI sector.
  • Earnings Per Share (EPS): Forecasts for the fourth quarter EPS have risen by 12‑15 % year‑over‑year, with analysts projecting a diluted EPS of $1.15 versus the consensus of $1.00. This adjustment reflects the company’s high‑margin data‑as‑a‑service (DaaS) model and its recent focus on high‑value AI workloads.
  • Revenue Growth: Revenue guidance for the fourth quarter is expected to climb to $2.45 billion, up 15.8 % from $2.08 billion in the same period last year. This growth trajectory aligns with Snowflake’s historical ability to deliver revenue expansion in the mid‑teens of percentage points, often outpacing broader market averages.

Market Context: AI‑Driven Data Cloud Momentum

Snowflake’s valuation rally has been largely propelled by the broader artificial‑intelligence boom. The company’s data cloud platform, which aggregates data from disparate sources and enables AI‑ready analytics, has become a critical infrastructure layer for organizations deploying generative AI, machine learning pipelines, and advanced analytics.

  • Adoption Curve: According to a Gartner survey, 57 % of surveyed enterprises now consider data‑cloud services “critical” or “highly critical” for their AI initiatives, up from 42 % a year ago. Snowflake accounts for approximately 28 % of the cloud‑data market share, positioning it as the most widely adopted platform among AI‑centric workloads.
  • Competitive Landscape: While Microsoft Azure, Amazon Web Services, and Google Cloud continue to offer integrated AI services, Snowflake’s unique separation of storage, compute, and services layers affords customers fine‑tuned cost control and elastic scaling—a feature cited by analysts as a decisive competitive advantage.

Expert Perspectives

  • Industry Analyst – Dr. Elena Ruiz (Forbes Technology Council): “Snowflake’s growth is no longer a function of volume alone. The company’s recent investment in AI‑specific extensions and partnerships with leading machine‑learning frameworks has created a virtuous cycle: more AI workloads drive higher storage and compute usage, which in turn fuels recurring revenue.”
  • Technology Strategist – Jonathan Lee, VP of Cloud Infrastructure at Bloomberg Intelligence: “The company’s pricing model remains highly elastic. With the current inflationary environment, Snowflake’s ability to shift customers between compute and storage buckets allows it to preserve margins even as usage peaks during AI model training.”
  • Financial Researcher – Maya Patel, Equity Analyst at Citadel Securities: “Given the firm’s consistent record of exceeding revenue forecasts, the consensus EPS upside appears justified. However, investors should remain vigilant about potential macro‑economic headwinds that could compress enterprise IT budgets.”

Actionable Takeaways for IT Decision‑Makers

  1. Leverage Snowflake’s AI Optimizations
  • Snowflake’s recent “AI‑optimized” compute kernels reduce latency for transformer‑based models by up to 30 %. Enterprises focused on large‑language‑model deployments should benchmark performance gains against their current data‑platform stack.
  1. Cost‑Control via Separate Billing
  • The platform’s separation of storage and compute costs allows for granular budgeting. IT finance teams can isolate AI workloads to specific projects, aiding in chargeback and cost‑allocation models.
  1. Strategic Partnerships
  • Snowflake’s alliances with major AI vendors (e.g., NVIDIA for GPU‑accelerated workloads, Hugging Face for open‑source model hosting) expand the ecosystem, offering lower total cost of ownership for AI initiatives.
  1. Monitoring Market Sentiment
  • With analyst upgrades, the stock may experience heightened volatility around earnings release. IT leaders should monitor capital‑market reactions, particularly in relation to AI‑specific revenue segments, as they may influence funding for new AI projects.

Outlook

Snowflake’s impending third‑quarter fiscal 2026 report will likely reinforce the narrative of sustained growth in the AI‑driven data cloud sector. Analysts’ upward revisions, coupled with a strong market rally, underscore investor confidence in Snowflake’s product differentiation and recurring‑revenue model. For enterprise IT professionals and software developers, the company’s trajectory offers a compelling case for continued investment in AI‑ready data infrastructure.