Markets are acting on a strange contradiction. AI is still the biggest long-term theme, yet one wave of fear about “business disruption” can push some sectors down as if they are about to lose their entire market. Morgan Stanley strategists argue that these oversized selloffs can create opportunities for investors who choose specific companies, not just buy the whole index.
Their main point is that the market often assumes established firms are the ones that will be harmed by AI. Morgan Stanley takes the opposite view. In the next few years, the bigger effect should be practical adoption of AI inside real businesses. That can lift productivity, expand markets, and support pricing power for companies that already have customers, data, and strong sales channels.
"The 'AI panic' as a misplaced market bet
Morgan Stanley $MS describes the current jitters as typical of the course of a great investment cycle: alternating between phases of enthusiasm and phases where the market begins to question whether the giant capital outlay will pay off and who will be "rolled over." During such periods, price volatility widens and pockets of selling emerge where the sell-off becomes detached from the reality of corporate performance.
This is why the bank recommends looking for three types of titles: established "core" players in the AI ecosystem, strong growth companies, and quality companies with a high ability to translate value into prices. In their vocabulary, this means companies that can deploy AI quickly into products while having the customer impact to maintain margins even in times of pricing pressure.
Why Morgan Stanley is returning to software even though it has been under pressure
Software is one of the segments that has been hit hardest by AI fears, with some investors interpreting the new tools as having the potential to "cheapen" development, thereby destroying the pricing power of traditional vendors. But Morgan Stanley says the market overly assumes the inability of established firms to use AI innovation to their advantage. Rather, their thesis is that AI will expand what can be automated in enterprise systems, thereby increasing the scope for further growth.
The argument from the second Morgan Stanley note taken up by financial sites fits in with this: after sell-offs, multiples in software are significantly lower than at times of peak uncertainty, creating "attractive entries" in big names. Specifically, the average firm value-to-revenue multiple has fallen by about a third since October 2025, returning to levels familiar from the earlier wave of uncertainty around firms moving to the cloud.
That's why Morgan Stanley names the likes of Microsoft $MSFT, Intuit $INTU and Atlassian $TEAM as interesting entry points - firms that have a strong position with enterprises, a broad ecosystem and the ability to "build AI" into products in a way that customers will actually pay for. In that logic, AI is a new feature that adds value to products and extends contracts, rather than a "killer" of existing players.
Banks as the net beneficiary of AI profits
Interestingly, Morgan Stanley counts banks among the net winners. The reason is pragmatic: the banking business is full of repetitive processes (client servicing, risk control, document processing, compliance) where AI can incrementally increase productivity and reduce costs. This translates into profitability over time, even if it is not "seen overnight".
At the same time, the bank names specific "most resilient" choices: Citigroup $C, Bank of America $BAC, State Street $STT and Truist $TFC. The common denominator is supposed to be a combination of size, a stable business and the fact that it is difficult for them to be quickly displaced by pure technology change. In other words: AI in banks is likely to first lift the efficiency of those already sitting on the infrastructure and customer base.
Payments, consumer finance and insurance: less revolution, more efficiency
For payments and fintech, Morgan Stanley mentions Mastercard $MA and Visa $V as beneficiaries. The basic reasoning is simple: AI increases automation, speeds up decision-making, improves fraud detection and can support new ways of shopping where software does some of the decision-making for the user. Thus, short-term concerns about "disruption" can become a long-term story of efficiency and higher transaction volume over time.
Consumer finance is viewed similarly: the market fears that AI will bring new competitors, but Morgan Stanley argues that the benefits in terms of productivity and better processes will outweigh this. For insurance, they see a gradual improvement in the way intermediaries work, while contract complexity, regulation and mandatory processes reduce the risk of AI "overhauling" the entire industry anytime soon.
What to take away from this as an investor
Morgan Stanley's entire thesis can be summed up as follows: the market today is "selling some sectors" as if AI is a purely disruptive force. In contrast, the bank says the next few years will be dominated by a wave of AI adoption - and this will favour firms that already have customers, distribution and the ability to translate new value into pricing.
To this they add a longer-term framework: generative AI is set to expand the addressable market for enterprise software solutions into the hundreds of billions of dollars by 2028. This is important because if the 'pie' gets bigger, established firms may not just struggle for share - they may grow in absolute numbers too.