BCA Research says the current surge in investment tied to artificial intelligence has progressed to a mature stage, though the firm does not see definitive evidence that the cycle is about to conclude.
In a research note, BCA detailed the specific gauges it will watch to judge whether the AI capex boom is approaching a downturn. Chief Strategist Peter Berezin framed the outlook by noting that while BCA entered the year with an expectation that "2026 could end up being a lot like 2000," the robust demand for computing power driven by AI agents has made "a 1999-type melt-up" appear increasingly plausible.
Reflecting that shift in the investment backdrop, BCA raised its recommended equity allocation for the next 12 months from a slight underweight to neutral.
The firm said that nearly all of the recent upgrades to S&P 500 earnings forecasts have been underpinned by scarcity across several inputs - specifically oil, semiconductors and what BCA described as "other AI paraphernalia." Those shortages, the firm added, together with a relative lack of competition, are supporting the elevated profit margins enjoyed by large technology companies.
Nevertheless, BCA warned that both supply constraints and the present competitive structure are not permanent. The research house expects that the current shortage of computing capacity will ultimately flip into a surplus. Over time, BCA also suggested, AI itself could chip away at the monopoly power of leading technology firms.
Because the timing of such a transition is uncertain, BCA set out four groups of indicators it is monitoring closely: "1) adoption metrics; 2) prices for GPUs and memory chips; 3) analyst capex estimates; and 4) measures of AI financial risk." Taken together, the firm believes these measures indicate the AI investment boom is in an advanced phase, but they do not point to an imminent end to the cycle.
Watchlist context
- Adoption metrics - signals on how rapidly AI products and services are being taken up in the market.
- GPU and memory prices - pricing trends for critical hardware used in AI workloads.
- Analyst capex estimates - consensus forecasts of corporate capital spending that could confirm or contradict the investment cycle.
- Measures of AI financial risk - indicators that would reflect strain or overextension in AI-related finance.
BCA's position is cautious but not alarmist: the indicators show an advanced boom, yet none currently imply that a bust is imminent.