AI Panic Hit Tech Stocks—But NVIDIA's Growth Engine Is Intact

AI Panic Hit Tech Stocks—But NVIDIA’s Growth Engine Is Intact Written by Thomas Hughes | Reviewed by Clare Titus September 16, 2026 Add As Preferred Source Share Share Share This Article Link copied to clipboard. Close Key Points Despite calls to slow AI model advancement, infrastructure demand remains strong, with backlogs and capital expenditure plans expanding significantly across hyperscalers in Q2. NVIDIA maintains a nearly 97% Buy-side analyst consensus with no Sell ratings, and its consensus price target implies more than 50% upside from current levels. Inference workloads, led by companies like Advanced Micro Devices, are poised to accelerate data center buildout as AI infrastructure shifts from training toward profitable monetization. MarketBeat previews the top five stocks to own by October 1st . AI leaders shocked the world by calling for a slowdown in AI’s advancement and for regulation. The news triggered a sector-wide drawdown, raising the risk of a deeper correction, but short sellers shouldn’t get their hopes up. As scary as it may seem to AI investors, the slowdown in AI’s advancement isn't likely to affect the infrastructure buildout. For the market, more advanced AI models don't matter, since labs such as OpenAI and Anthropic already have highly capable (and potentially dangerous) versions; what matters is the infrastructure to deploy utilitarian AI across the enterprise landscape. The market gets this wrong: safety and capacity aren’t the same thing. AI demand is not collapsing. Q2 results from NVIDIA NASDAQ: NVDA to Salesforce NYSE: CRM , and nearly every AI-capable company in between, point to accelerating infrastructure demand. In this scenario, September price weakness is a good time to buy these stocks, as catalysts for their price action lie ahead. Get NVIDIA alerts: Sign Up The AI Boom Hasn’t Really Boomed (Yet) Key details for investors to watch include backlogs, utilization rates, persistent pricing power, and the potential for capital expenditure (CapEx) relief. Q2 backlogs expanded at a historic pace, increasing by triple digits at Alphabet NASDAQ: GOOGL , Dell NYSE: DELL , and Super Micro Computer NASDAQ: SMCI . Critical players like Oracle NASDAQ: ORCL , now ubiquitous across cloud instances regardless of hyperscaler, saw backlogs grow to more than $650 billion, while neoclouds like Nebius NASDAQ: NBIS reported far larger increases, with Nebius's backlog up 4x. CapEx plans among the leading hyperscalers total over $700 billion, underscoring the spend. Utilization rates matter because they run near 100%, even for older legacy technology. The takeaway is that technology transitions from model training and advanced computing to inference as it ages out, providing a long runway for cash flow and capitalization. This is the foundational factor in NVIDIA’s ability to securitize its GPUs , enabling institutional investors such as retirement funds to invest in the cash flow. The trigger for stock price gains will be the monetization of existing assets, which, coincidentally, aligns with profitability. Hyperscalers dialing back ultra-expensive frontier modeling will suddenly free up cash flow, removing the primary hurdle for stock prices today. The upfront cost of AI infrastructure is debilitating, impairing cash flow and profitability for most AI-related companies. AI CapEx Fears Haven’t Derailed the Infrastructure Trade Q2 reporting was spectacular , with results outpacing consensus estimates across the board by a significant margin. However, analysts were skeptical of CapEx plans and a rapidly differentiating market, causing stocks to move in different directions. As it stands, AI infrastructure names, including NVIDIA, remain the big winners, as they are the focus of current spending. Wedbush pointed out that the buildout is moving slightly faster than adoption, which is a root cause of concern. The takeaway for investors is that slowing AI model spend not only improves profitability but also frees ...