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3 Top Artificial Intelligence Stocks to Buy in December

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3 Top Artificial Intelligence Stocks to Buy in December

Alphabet is reportedly commercializing its custom Tensor Processing Units (TPUs) in partnership with Broadcom and may sell TPUs to Meta, while reporting recent revenue growth of 16% and diluted EPS growth of 35%. Nvidia generated $52.1 billion in data-center hardware sales in its fiscal third quarter, underlining the sizable market opportunity that Broadcom (which has clients including OpenAI and a reported $10 billion mystery order) and Taiwan Semiconductor (the dominant neutral fabricator) stand to benefit from as hyperscalers guide for increased 2026 AI spending and Nvidia projects $3–4 trillion annual data-center capex by 2030; the piece recommends buying GOOGL, AVGO and TSM into 2026.

Analysis

Market structure: Broadcom (AVGO) and TSMC (TSM) are the primary beneficiaries — AVGO by selling lower-cost, high-volume custom AI accelerators and TSM by owning wafer capacity — while Nvidia (NVDA) faces targeted share loss in fixed-workload data‑center segments but retains pricing power in flexible/GPU workloads. If hyperscalers shift even 10–20% of inference traffic to custom ASICs over 12–36 months, ASP pressure on mainstream GPUs could be 5–15% and margins for hyperscalers improve. Cross-asset: sustained AI capex growth (Nvidia’s $3–4T by 2030 thesis) should lift semicap equipment, copper/silicon demand and push real yields modestly higher; expect elevated equity vols for NVDA/AVGO around earnings and directional TWD/USD moves on Taiwan geopolitics. Risk assessment: Key tail risks are regulatory (US export controls widening), a Taiwan military incident disrupting TSMC, or Broadcom/Alphabet deals collapsing — each could wipe 15–30% off consensus incremental revenue for suppliers in 6–24 months. Immediate market moves (days) are sentiment-driven; short-term (weeks–months) depends on Q4/2025 earnings and 2026 guidance; long-term (1–5 years) hinges on software lock‑in (CUDA/TPU ecosystems) and fab capacity allocation. Hidden dependencies include software stack adoption and hyperscaler procurement cycles which can delay revenue recognition by 6–12 months. Trade implications: Favor AVGO and TSM as mid-term longs (6–18 months) and selective GOOGL exposure to capture TPU monetization optionality; size positions 1.5–3% NAV each. Hedge NVDA exposure — prefer small short or protective put spreads (0.5–1% NAV) rather than outright large shorts given NVDA’s ecosystem moat. Use options: buy 6–12 month AVGO call spreads (10–20% OTM) and 3–6 month NVDA put spreads (8–12% OTM) to express asymmetric risk/reward around earnings and 2026 guidance. Contrarian angles: The market may overstate immediate Nvidia displacement — historical parallels (GPU vs ASIC in crypto mining) show ASICs win niche scale workloads but don’t fully replace flexible platforms. Broadcom’s custom chips could take share quickly in inference but risk being niche if software migration costs exceed 12–24 months. TSMC’s geopolitical concentration is underpriced; a 2–4 week fabrication disruption would materially re-rate all suppliers. Monitor for supply-side bottlenecks that could flip winners into temporary losers.