Meta's AI Investment Outlook Sparks Valuation Debate Amid Rising Costs

What happened

In January 2026, a Motley Fool article argued that Meta's stock is undervalued, citing expectations for higher AI investments than predicted, while downplaying bearish interpretations of CEO comments. The DeepValue report reveals that Meta's management has guided for significantly faster expense and capex growth in 2026, with AI infrastructure driving a surge from $39.2B in 2024 to over $70B in 2025. Q3 2025 financials showed robust 26% revenue growth, but costs rose 32%, indicating early margin pressure as spending outpaces gains. Market sentiment has shifted from AI enthusiasm to concern, with recent selloffs reflecting fears that elevated investments may not yield timely returns. The article's bullish stance contrasts with the report's caution, highlighting a divide over whether AI spending justifies current valuations.

Implication

Meta's aggressive AI investments, while aimed at sustaining ad share gains, introduce significant risk of margin erosion if revenue growth fails to keep pace with rising expenses. The stock's high valuation at ~27x EPS already embeds premium growth expectations, leaving little room for error if spending guidance worsens or monetization lags. Entry points near $520 offer better risk-reward, as per the report's attractive level, rather than buying at current levels without clearer evidence of AI payoffs. Monitoring upcoming earnings for updates on 2026 capex and expense trends is critical to assess whether management can balance investment with profitability. Long-term, Meta's moat remains strong, but near-term capital allocation decisions could pressure free cash flow and investor confidence if not executed carefully.

Thesis delta

The bullish article does not alter the core cautious thesis from the DeepValue report, which remains a 'WAIT' rating due to validated risks from accelerating AI spending and margin pressure. It reinforces the need for investors to critically evaluate management's capital allocation against financial outcomes, as optimistic narratives may overlook underlying cost challenges. No fundamental shift is warranted until concrete evidence emerges that AI investments are monetizing efficiently without eroding returns.