3 Tech Stocks That Could Be in Trouble if There's an Artificial Intelligence (AI) Slowdown

An Anthropic CEO call to slow AI development highlights downside risk for AI-exposed leaders Nvidia, Micron and Palantir if technology spending or AI infrastructure demand weakens. Nvidia trades at a forward P/E just below 25 versus roughly 20 for the S&P 500, Micron trades at 7x after rising more than 550% over 12 months, and Palantir trades at 85x; all could face sharp multiple compression if AI-driven growth falls short of elevated expectations.

Analysis

The relevant risk is not a voluntary industry-wide pause; it is a lower return-on-invested-capital threshold for AI infrastructure that causes hyperscalers to moderate incremental capex. That would hit the stack unevenly: NVDA can defend gross margin through software/ecosystem lock-in and supply allocation, while MU is exposed to the more reflexive inventory cycle in HBM and conventional DRAM/NAND. AMD is the likely share-gain beneficiary if buyers shift from frontier-training clusters toward cost-sensitive inference, but it remains vulnerable to an absolute reduction in accelerator demand.

PLTR has the greatest multiple-duration exposure rather than the greatest direct capex exposure. Its government revenue provides downside ballast, but commercial AIP bookings must continue converting into durable production revenue; a modest bookings or net-retention miss can trigger disproportionate multiple compression over the next 1-3 months. The less-discussed second-order effect is that a spending slowdown would favor AI software vendors with demonstrable labor-cost savings and short paybacks over model-training and hardware suppliers sold on strategic optionality.

Consensus is likely overstating the importance of AI-safety commentary as a near-term demand catalyst. Enterprise deployment bottlenecks—data readiness, security approval, integration capacity, and unclear ROI—are more investable leading indicators. A broad AI unwind needs confirmation from hyperscaler capex guidance, lead-time normalization, HBM pricing, and cloud AI revenue rather than rhetoric; absent those signals, a headline-driven selloff in NVDA/MU could be a buying opportunity rather than a structural short.

Key Decisions for Investors

• Maintain a 1-3 month defensive pair: long NVDA / short PLTR in matched beta. NVDA has a clearer revenue backlog and lower duration risk; PLTR is more exposed to any deceleration in commercial AI bookings. Exit if PLTR raises full-year commercial-growth guidance materially or NVDA reports a material backlog/lead-time deterioration.
• Do not short MU solely on AI-slowdown headlines. Set an alert to initiate a tactical 3-6 month MU short, or buy downside puts, only if HBM contract pricing rolls over, customer inventory days rise, or management signals weaker bit-demand growth; the risk is that constrained HBM supply sustains pricing despite softer broader AI capex.
• Use any 5-8% headline-driven NVDA decline without a corresponding hyperscaler capex cut as a staged 6-12 month long entry. Falsify the thesis if two or more major cloud customers reduce annual capex plans or NVDA guides to sequential data-center revenue contraction.
• For inference-spend rotation, monitor AMD rather than chase it immediately: initiate a 6-12 month AMD/NVDA relative-value long only after independently verified accelerator design wins translate into data-center revenue guidance. The key risk is persistent CUDA switching costs keeping AMD's share gains below expectations.