AI’s rapid expansion is no longer just about soaring technology stocks. The scale of spending required to build the AI economy is reshaping equity valuations, credit markets and even traditionally slow-growth sectors such as utilities.
According to Janus Henderson portfolio managers Denny Fish, John Lloyd and John Kerschner, market volatility tied to AI stocks has intensified debate around whether the technology’s promise is already priced in. They say that investors should focus less on short-term swings and more on the breadth of disruption unfolding across industries.
The report aligns with the rising fear among investors that AI may be disruptive across industries while the tech sector itself grapples with generating returns on eyewatering investment.
“Recent volatility in AI-related equities only sharpens this line of enquiry,” the report noted, adding that understanding the scale of transformation is essential because it will ultimately affect revenue growth, productivity and business models across nearly every sector.
The firm points out that today’s valuations look less extreme when compared with past technology bubbles. The largest companies in the S&P 500 currently trade at price-to-earnings multiples well below dot-com era highs, while generating significant cash flows from deployed AI infrastructure.
Importantly, the managers argue the investment cycle remains in its early stages. Advances that enabled modern AI developed over decades, suggesting that the commercial buildout — and earnings growth tied to it — could extend for years.
Unlike previous tech booms, the AI buildout is increasingly reliant on debt financing. Hyperscale technology firms are tapping investment-grade credit markets aggressively to fund unprecedented capital expenditure programs tied to data centers and computing infrastructure.
That borrowing surge could pressure tight credit spreads as new supply enters the market, the report warns. Yet it also creates opportunities across fixed income sectors, particularly as spending ripples through supply chains supporting AI infrastructure.
Commercial mortgage-backed securities are emerging as a key financing channel for new data centers. Location matters, the managers said, because projects must be positioned within established development hubs capable of supporting enormous electricity demands.
Power consumption is becoming a defining constraint. Some estimates suggest AI infrastructure could require the equivalent electricity usage of three New York Cities by 2030, a dynamic already prompting utilities to issue debt to expand capacity.
For bond investors, that shift may transform utilities from historically stable but slow-growing businesses into higher-growth issuers benefiting directly from AI adoption.
While enthusiasm remains high, the report cautions against assuming every company linked to AI will succeed.
“Technological shifts of this magnitude are a fertile environment for active management,” the managers wrote, emphasizing that careful selection will be critical as disruption accelerates.
Infrastructure providers enabling AI development continue to stand out, while certain software companies face mounting pressure following a broader sell-off in software-as-a-service stocks. Future leaders, the authors argue, will be those that build operations around AI rather than simply adding it as a feature.
Meanwhile, some companies trading at steep revenue multiples appear supported largely by what the report describes as an “AI halo,” despite limited commercialization timelines.
As AI moves from infrastructure buildout to widespread enterprise adoption, investors may find the biggest gains not in today’s obvious winners, but in the next generation of companies positioned to harness the technology’s productivity gains across the broader economy.
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