Jennison's Raj Shant, PGIM's Guillermo Felices and PGIM's Morgan Laughlin argue the tech sell-off reflects a healthier, more selective AI build-out rather than a demand collapse. They see power, permitting and political constraints slowing capex without derailing underlying compute demand or the broader economy.
6 NOVEMBER 2026
The piece argues that a sharp selloff in AI-linked semiconductor and tech stocks reflects a necessary reset of crowded positioning and high capital spending, not the end of the broader AI investment theme. It contends long-term compute demand remains intact, while market leadership broadens beyond mega-cap tech.
Janus Henderson Investors argues China equities merit a strategic allocation, citing an innovation-led growth shift, attractive valuations, diversification benefits and shareholder-value reforms. It contends widening performance dispersion between winners and losers strengthens the case for active stock selection.
A research team argues that Democratic gains in state governorships, driven by anti-data-center rhetoric, raise regulatory risk for AI infrastructure, triggering a tech sell-off. It contends the AI buildout will continue but favour diversified hyperscalers over single-product and smaller neocloud providers.
Schroders attributes the sharp tech-led equity sell-off to fears that a Democratic midterm win could slow AI infrastructure spending, but argues the structural AI case remains intact despite near-term volatility. It favours resilient equity exposure, higher-quality US stocks, and diversification via government bonds and alternatives.
Schroders' Simon Webber argues the AI sell-off reflects financing risk rather than weakening demand, as capital markets face strain funding the infrastructure build-out. He favours active selection of companies with strong balance sheets and earnings visibility amid valuation compression.
Capital Group strategists including Matt Miller, Diana Wagner, Tom Hollenberg and Cheryl Frank argue Democrats' midterm sweep will constrain Trump's tariff and tax agenda but won't curb deficits, healthcare debates or AI-driven economic resilience.
J.P. Morgan's Stephanie Aliaga argues political backlash against AI data centers, evident in midterm election results, raises costs and delays but is unlikely to derail the buildout given strong economic incentives. Post-2028 projects face the greatest uncertainty, while a shakeout of speculative developments may benefit well-capitalized hyperscalers.
JPMorgan Asset Management estimates the five major US hyperscalers face a combined $1.1 trillion external financing gap for AI infrastructure, creating expanding credit opportunities but requiring careful security selection as leverage and structural complexity rise.
