The traditional risk-on, risk-off framework that governed stock market investing for decades has given way to an AI-on, AI-off model, according to a Barron's analysis published July 24.
The traditional risk-on, risk-off framework that governed stock market investing for decades has given way to an AI-on, AI-off model, according to a Barron's analysis published July 24.

The traditional risk-on, risk-off framework that governed stock market investing for decades has given way to an AI-on, AI-off model, according to a Barron's analysis published July 24.
The stock market's traditional risk-on, risk-off framework has been replaced by an AI-on, AI-off model, with capital reallocating toward AI-linked equities, according to a July 24 Barron's analysis.
"The old playbook of rotating between cyclical and defensive sectors based on macro signals no longer works the way it used to," said Viraj Gandhi, chief executive officer at SAMCO MF. "Largecaps offer better safety as valuations are below historical averages."
The shift is visible in corporate spending patterns. Alphabet and Tesla's recent capital expenditure plans, which exceeded analyst expectations, have reinforced the new regime, with investment directed primarily toward AI infrastructure, according to the analysis. Companies committing spending to AI have been rewarded by investors, while those perceived as underinvesting have been penalized — a departure from the traditional framework where macro factors such as interest rates drove sector-wide moves.
The implications for portfolio construction are significant. Under the old framework, investors rotated between growth and value based on rate expectations and economic data. The new AI-on, AI-off model means a company's exposure to artificial intelligence increasingly determines its stock performance, potentially triggering broad-based re-pricing as fund managers reassess which holdings qualify as AI beneficiaries. The shift also has cross-asset implications, as bond yields and currency markets adjust to the changing composition of capital spending.
Alphabet and Tesla's capital expenditure announcements have crystallized the new regime. Both companies unveiled spending plans that exceeded analyst expectations, with investment directed primarily toward AI infrastructure. The market response — rewarding AI spenders while penalizing laggards — represents a structural change from the traditional risk framework, where sector-wide moves were driven by macro data such as GDP growth and interest rate decisions.
The shift extends beyond US mega-cap stocks. In India, Hiren Ved, director at Alchemy Capital Management, said the country's indirect AI play could create wealth in power, data centers and capital goods. "India's AI boom offers indirect opportunities in infrastructure and power sectors," Ved said, pointing to the physical infrastructure build-out needed to support AI computing. Rajesh Palviya, head of technical and derivative research at Axis Direct, said the midcap and smallcap rally has eroded the margin of safety, recommending a rotation toward largecaps where valuations offer better risk-reward.
The AI-on, AI-off framework is forcing investors to rethink how they classify stocks. A utility company building data centers may trade more like a tech stock. An industrial firm supplying cooling equipment for AI servers may command a higher multiple than a traditional manufacturing peer. This blurring of sector lines challenges the passive investing model, where sector-based exchange-traded funds have been a staple of portfolio construction.
Pramod Gubbi, director at Marcellus Investment Managers, said AI poses a bigger risk to IT workers than to the companies themselves. "Artificial intelligence may reduce Indian IT sector employment before impacting companies," Gubbi said, suggesting the disruption will reshape labor markets before it reshapes corporate profitability. The valuation premium for quality stocks has corrected to attractive levels, Gubbi added, making selective stock picking more important than broad sector allocation.
The new regime also affects how investors evaluate risk. Under the old risk-on, risk-off framework, the VIX and credit spreads served as primary gauges of market stress. In the AI-on, AI-off world, the dispersion between AI-linked and non-AI stocks has become a more relevant measure of market health, with the gap between the two groups widening to levels that would have signaled extreme sector concentration in prior cycles.
This article is for informational purposes only and does not constitute investment advice.