2 AI Stocks Worth a Look in December
AI stocks sold off after Oracle and Broadcom reported. Sentiment soured on cloud demand and margins, and quality names got pulled down with the group. For finance pros, that's a window: buy durable cash flows and clear catalysts while the market is distracted.
Two names stand out for different reasons: IREN for asymmetric growth if it executes, and Alphabet for steady compounding backed by cash generation.
IREN: A direct play on AI data center power constraints
Iren (NASDAQ: IREN) is building data centers positioned as 100% renewable, targeting the core bottleneck in AI: power and land with grid access. The company recently signed a five-year, roughly $9.7 billion agreement with Microsoft, validating demand from hyperscalers.
Management issued $2.3 billion in convertible notes. Yes, that dilutes in the short term, but part of the raise refinanced more expensive obligations-improving long-term flexibility. Shares are still down close to 50% from the early-November peak despite a strong year-to-date move.
- Thesis in one line: If IREN can reliably deliver powered sites at scale, hyperscaler demand can fill capacity fast.
- Key numbers to track: Targeting $3.4 billion in annual recurring revenue by fiscal 2026 versus $16.4 million from AI cloud services in fiscal 2025. One more hyperscaler deal of Microsoft's size could get them most of the way there.
- Catalysts: Nvidia is gathering partners this month to tackle AI data center power issues. If power availability is the gating factor, operators with greenfield sites and PPAs win.
- Execution risks: Permitting, interconnect timelines, delivered cost per MW, and the capital intensity of buildouts. Watch share count, capex per MW, contract length/price, gross margin on AI cloud services, and contracted MW backlog.
- Positioning: Treat as a high-beta satellite position sized for volatility. Re-rate potential is significant if the second hyperscaler lands; the flip side is drawdowns if timelines slip.
Context: AI compute demand is growing faster than available power, and grid constraints are real. For background on data center electricity trends, see the International Energy Agency's overview of data center and network electricity use.
Alphabet: Cash machine funding both digital and physical AI
Alphabet (NASDAQ: GOOGL) (NASDAQ: GOOG) has the balance sheet and cash flows to invest through cycles. Online ads and Google Cloud throw off the cash that funds AI chips, models (Gemini), and infrastructure-without stressing the business.
Recent numbers support the momentum: total Q3 revenue grew 18% year over year, while Google Cloud grew 34%. Interest from large customers in Alphabet's AI chips could translate into multi-billion-dollar orders over time, adding another earnings lever beyond ads.
- Thesis in one line: Own the compounding: ads and Cloud pay for AI optionality (chips + models) with upside to share gains if competitors slow spending.
- Valuation: Around a 31x P/E with accelerating EPS has room if Cloud margin expands and AI monetization compounds.
- What to watch: Google Cloud operating margin and backlog, Gemini adoption across Workspace and Cloud, AI chip orders/commitments, and capex cadence.
- Risks: Antitrust actions, ad cyclicality, AI model competitiveness, and continued heavy capex.
For primary data and disclosures, monitor Alphabet's investor relations.
Portfolio approach for finance teams
- Entry timing: Use staged buys during sector-wide drawdowns tied to macro or peer earnings. The Oracle/Broadcom selloff is a good example.
- Sizing: Core position in Alphabet; satellite in IREN given execution and financing sensitivity.
- KPIs to review quarterly: For IREN: contracted MW, ARR, capex/MW, dilution. For Alphabet: Cloud growth and margin, AI chip commitments, EPS revisions, capex.
- Risk controls: Set downside triggers tied to fundamentals (missed build timelines for IREN; Cloud margin deterioration for Alphabet) rather than price alone.
- Time horizon: 24-36 months. AI capacity and monetization cycles don't resolve in a quarter.
If you're building internal AI capabilities on the finance side, this curated list of AI tools for finance can help with evaluation and vendor shortlisting.
This article is for informational purposes only and is not investment advice. Do your own research and consider your mandate, risk budget, and constraints before allocating capital.
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