Canaccord Genuity

AWS Outperformance Boosts Confidence in Amazon AI

Amazon’s strong second-quarter earnings—led by 37% year-over-year growth at Amazon Web Services (AWS) and revenue beats for both AWS and Amazon’s advertising business—prompted broad analyst upgrades and higher price targets. AWS reported a $496 billion backlog and disclosed $25 billion in AI annual recurring revenue (ARR), while Amazon raised its 2026 capital expenditure outlook to about $220 billion. Analysts cited improving AWS margins, accelerated enterprise AI demand, and a clearer capital-return framework that supports elevated capex. The results drove an ~11% jump in Amazon shares and led many Wall Street firms to maintain or raise buy/overweight ratings and lift price targets across the board.

Analysts Lower Meta Share Ceiling After Q2 Earnings

Meta Platforms reported second-quarter results showing an earnings-per-share miss and softer guidance, prompting a roughly 9% premarket share decline and analyst downward revisions to price targets. Meta earned $6.18 per share versus LSEG consensus of $7.22, reported 3.6 billion active users across its apps, and narrowed 2026 capital expenditure guidance to $130 billion–$145 billion (up from a prior $125 billion low-end expectation). Free cash flow fell to $784 million from $8.55 billion a year earlier. Analysts cited uncertainty about the timing and monetization of Meta’s AI investments (including its foundation model Muse Spark and business-agent initiatives) even as many maintained bullish ratings based on the underlying ad business strength.

Street Divided Over Meta's Cloud Gamble

Meta Platforms confirmed discussions about launching a cloud business after shares initially jumped nearly 9% on the news. Reports say the company is weighing whether to offer access to AI models hosted on its infrastructure or to sell raw compute. The debate intensified because Meta plans large fiscal 2026 capital expenditures — a revised range of $125 billion to $145 billion — prompting questions about whether the company has overbuilt AI capacity. Analysts are split: some (e.g., Needham’s Laura Martin) warn of late entry and lower-margin cloud economics, while others (Canaccord, JPMorgan) highlight potential sizable revenue per gigawatt of compute and argue the move could monetize excess capacity and defend investment in AI infrastructure. The article also notes Meta’s recent AI product release (Muse Image) and places Meta’s valuation and year-to-date stock performance in context versus hyperscaler peers.