2 AI Stocks to Buy in 2026, and 1 to Avoid

Meta Platforms is accelerating AI infrastructure spending while reporting strong recent revenue and earnings growth driven by AI-powered engagement across its ecosystem (over 3.5 billion daily active users), though its shares pulled back after Q3 amid investor concern over AI investment pacing. Apple is benefiting from iPhone 17–led renewals, posting its best two-quarter revenue growth in three years and guiding to double-digit revenue growth next quarter, leveraging a services attach to 2+ billion active devices. By contrast, Recursion Pharmaceuticals’ AI-driven drug-discovery platform has no marketed products or phase-3 candidates yet and faces competition from large incumbents like Eli Lilly, making it a high-risk biotech investment.

Analysis

Market structure: Big-cap platform owners (META, AAPL) and AI-infrastructure suppliers (NVDA) are the primary beneficiaries — advertising yield and device+services monetization scale with AI features, reinforcing pricing power for high-margin services. Small-cap, asset-light AI drug-discovery plays (RXRX) face adverse selection: their value hinges on binary clinical success and licensing, while incumbents (Lilly) can commoditize the space with deeper pockets and scale.

Risk assessment: Near-term (days–weeks) volatility will track earnings/guidance and data-center order flow; medium-term (quarters) risks include ad spend cyclicality and product refresh cadence; long-term (years) risks are regulatory (privacy/antitrust), AI model failures, or a semiconductor supply shock. Tail risks: a major privacy/regulatory ruling that limits ad targeting (10–30% ad rev hit scenario) or a failed clinical readout at RXRX that vaporizes enterprise value.

Trade implications: Favor overweight in large-cap AI winners and infra — but size allocations should be disciplined: focus 2–4% active positions in META/AAPL/NVDA with disciplined stops and option overlays; keep biotech AI exposure <1% via defined-risk instruments (put spreads) rather than outright longs. Rotate out of small-cap biotech and into semis/services on any >8–12% dispersion moves over the next 3–6 months.

Contrarian angles: Consensus underprices Meta’s optionality beyond ads (AI-driven commerce, creator monetization) and overprices RXRX’s moat relative to pharmas’ internal AI efforts. Historical parallel: AWS-style capex (early negative cashflow → durable moats); if Meta’s AI investments drive 5–10% incremental ARPU over 2–3 years, current pullbacks would be a buying opportunity; conversely, a single negative clinical catalyst could make RXRX binary.

Key Decisions for Investors

• Establish a 2–3% portfolio long position in META over the next 30 days (scale in 50/30/20 on price), target +30–50% over 12–24 months, hedge with a 12% OTM 6–9 month protective put or sell 1–2 month 10% OTM covered calls to fund carry; increase allocation by another 1% only if shares drop >10% from entry.
• Allocate 3–4% to AAPL as a core tech holding to capture iPhone17 cycle and services growth; implement income overlay by selling 1–3 month calls 8–12% OTM (~generate yield) and plan to hold 12–18 months unless guidance misses by >5% on revenue growth.
• Take a defined-risk bearish stance on RXRX: purchase a 6–9 month put spread sized to 0.5–1.0% of portfolio (buy nearer-money puts, sell lower strike to fund) and tighten/close if company announces a Phase 3 entry or extends reported cash runway beyond 12 months.
• Overweight AI infrastructure: deploy 1–2% into NVDA or a focused semi/AI infra ETF via a 3–12 month call spread ahead of memory/GPU cycle confirmation; pair this with the RXRX put spread (long infra / short biotech-AI) to capture divergence between durable infra demand and binary biotech outcomes.