Morgan Stanley issues sharp take on the stock market

Morgan Stanley thinks that Mr. Market just made a mistake.

Strategist Katie Huberty, speaking with Bloomberg, laid out the case that the recent stock market sell-off hasn’t been selective. In fact, she argues that it has been “indiscriminate,” where investors continue dumping stocks linked with the AI trade without separating the wheat from the chaff.

Huberty’s broader point is that we’re still in the early innings of what could become a whopping $10 trillion capital-spending cycle, driven by major productivity gains.

However, the markets don’t usually move in straight lines, which is why it’s easy to lose out on the nuance when positions shift so quickly.

The software and services space, in particular, has been under considerable duress of late. For context, here are five of the biggest enterprise-software names that have taken major hits over the past month.

Simultaneously, we argue that the leadership is broadening and AI adoption isn’t just about the flashy chipmakers and the big hyperscalers.

I covered Bank of America analyst Michael Hartnett, who had a similar take, warning that the stock market’s “easy” leadership era is fading away quickly.

Given that development, he argued that investors should turn their attention toward “unloved” pockets of the market, including small caps, REITs, and emerging markets, as these segments are the first to reflect a rotation.

If Huberty is right, this may not be the end of the AI trade, but the beginning of a major rotation.

• Morgan Stanley:7,800 (year-end 2026 target)

• J.P. Morgan:7,500 (year-end 2026 target, with upside case over 8,000 if the Fed cuts more)

• Bank of America Global Research:7,100 (year-end 2026 target, a more cautious “priced for perfection” setup)

• Barclays:7,400 (year-end 2026 target after bumping its forecast)

• UBS Global Research:7,500 (year-end 2026 target linked to AI momentum along with earnings strength)
  Source: Reuters

We aren’t seeing selective selling in the stock market, where a bunch of fundamentally strong businesses are being trimmed without much nuance, Huberty argues. She believes the major shift is from AI builders to AI adopters.

According to Morgan Stanley’s data, businesses that have been actively embedding AI into their operations are experiencing margin expansion at nearly half the pace of major benchmarks such as the S&P 500 and MSCI World.

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However, despite the impressive margin expansion, the big enterprise software names weren’t rewarded for their performances.

In identifying that disconnect, the firm effectively mapped 3,600 stocks 5 times while tracking changes in AI exposure, earnings quality, pricing power, and data advantage.

The common thread from the analysis was data moats.

Businesses sitting on heaps of proprietary credit and market data, along with financial systems of record or customer datasets, are in the best position to efficiently monetize AI.

Huberty also suggested that the “rate of change” in AI exposure is perhaps much larger outside tech at present, specifically in areas such as consumer, apparel, durable goods, autos, and energy/utilities.

Moreover, the recent price action backs up that thesis, with leadership effectively broadening beyond Big Tech.

Recent sector performance backs the rotation thesis
Using common ETF proxies for the buckets she pointed to, here’s what’s been happening recently.

• Benchmarks for context
  S&P 500 (SPY): -1.04% (1-month) and +3.30% (3-month) Tech (XLK): -3.72% (1-month) and -0.20% (3-month) Source: Barchart

• ETF proxies for various buckets
  Autos (proxy: CARZ): +2.28% (1-month) and +17.44% (3-month) Durable goods/housing-linked cyclicals (proxy: XHB): +3.36% (1-month) and +18.62% (3-month) Durable goods/home construction (proxy: ITB): +2.87% (1-month) and +18.33% (3-month) Apparel/retail-adjacent (proxy: XRT): -2.65% (1-month) but +12.37% (3-month) Consumer (broad discretionary proxy: XLY): -4.96% (1-month) and +3.55% (3-month). Source: Barchart

Hence, over the past three months, autos, homebuilders, and retail names have outperformed both the S&P 500 and tech, backing up Huberty’s claims that leadership is broadening beyond mega-cap AI stocks.

However, if we look at things from a one-month perspective, it suggests that the rotation is still underway but not in a straight line.

Interestingly, Morgan Stanley’s Mike Wilson made a similar point about stock market breadth in a separate Bloomberg interview.

Related: Cathie Wood buys $14 million of sliding AI stocks

This story was originally published by TheStreet on Feb 20, 2026, where it first appeared in the Investing section. Add TheStreet as a Preferred Source by clicking here.