Wall Street strategist Adam Parker, founder of Trivariate Research and former chief US equity strategist at Morgan Stanley, warned on the latest episode of Ticker Take that most investors are overexposed to artificial intelligence through the S&P 500. He identified eight stocks—including Walmart, Coca-Cola, and NextEra Energy—with low correlation to AI semiconductor baskets, arguing that genuine diversification requires companies whose earnings do not depend on the AI buildout.

The S&P 500's Hidden AI Concentration: 66% Trades Like a Semiconductor ETF

Parker noted that roughly two-thirds of the S&P 500 now behaves like a semiconductor exchange-traded fund, meaning the index itself carries far more AI exposure than many investors realize , according to the Ticker Take interview. When the AI trade eventually cools, he argued, supposedly diversified portfolios could cool with it. The statistic—66%—drives home how pervasive AI has become in broad market benchmarks, even in sectors not directly related to technology.

This concentration echoes patterns seen during the dot-com era, when a handful of tech giants dominated indices and left passive investors vulnerable to a sector collapse. The source report highlights Parker's view that the hard part today is finding good businesses that don't depend on AI—a challenge that makes his list more than a simple stock tip.

Parker's Eight: Walmart, Coca-Cola, NextEra Energy Among Low-Correlation Picks

Parker's screening process began with stocks up at least 10% over the last six months, then narrowed to names with low correlation to AI semiconductor baskets, upward earnings revisions, and business momentum driven by non-AI factors. The resulting eight include Walmart, which he called a potential AI beneficiary through tighter operations rather than an AI stock; Merck, offering low AI correlation and exposure to aging population trends; Coca-Cola, a defensive consumer-staples play; and NextEra Energy, combining stable utility demand with renewables growth that is not purely tied to data-center AI buildout.

Energy giants Exxon and Chevron add high dividend yields and very little AI correlation, though Parker reportedly prefers the big dividend payers over smaller, higher-flying energy names. Costco rounds out the group as a membership-driven platform with a wealthy customer base, albeit at a high valuation that raises questions about growth outpacing its multiple.

Why Healthcare and Energy Stocks Offer a Different Kind of Momentum

The healthcare and energy sectors provide catalysts unrelated to AI. for Merck, the aging population and steady earnings estimates offer a predictable revenue stream, as noted in the source report. nextEra's appeal lies in its dual exposure to regulated utilities and renewable energy projects—demand drivers that predate the AI boom and will likely persist regardless of chip cycles. Exxon and Chevron, meanwhile, enjoy dividend yields that reward income-focused investors without the volatility tied to AI narratives.

Parker's approach contrasts with the market's current fixation on AI-related plays.. By emphasizing companies with low correlation to AI baskets, he aims to reduce portfolio risk while still capturing upside from sectors like healthcare, consumer staples, and energy—a diversification strategy that the source frames as a hedge against a potential AI correction.

The Missing Detail: Which Diversified Med-Tech Name Made the Cut?

The source report identifies eight stocks but leaves one unnamed: a diversified med-tech name that Parker mentioned in the interview context, possibly Boston Scientific. The vagueness raises an open question about whether investors can replicate the portfolio without a precise list. While the other seven are explicitly confirmed—Walmart, Merck, Coca-Cola, NextEra Energy, Exxon, Chevron, and Costco—the missing eighth stock leaves a gap for those seeking exact replication. The source also does not publish Parker's specific correlation thresholds or the exact AI semiconductor basket used, which could affect how practitioners apply the screening methodology.