Morgan Stanley resets MongoDB stock price target after earnings 

There is a specific kind of earnings report that is genuinely hard to read. The one that beats on revenue, raises full-year guidance, shows improving margins, but still leaves investors asking whether the most important growth driver has actually arrived yet.

MongoDB (MDB) just delivered exactly that quarter. And Morgan Stanley’s response captures the tension precisely.

Morgan Stanley raised its price target on MongoDB (MDB) after the company’s first-quarter fiscal 2027 results on May 28. The note’s title said it plainly: 

“Entry to the AI Winner Circle Still Pending, but It’s Just a Matter of Time”

MDB is down 24.65% year-to-date compared to the S&P 500’s 10.78% gain, according to Yahoo Finance.

The stock is being priced for a company whose AI moment has not yet arrived. Morgan Stanley argues that the timeline is getting shorter and that the underlying business is strong enough to own while waiting.

Morgan Stanley raised the MongoDB stock price target to $380 from $335

Morgan Stanley raised its price target on MongoDB (MDB) to $380 from $335 in a note shared with me at TheStreet, maintaining its Overweight rating. This came after its Q1 fiscal 2027 results actually showed solid results.

The first-quarter scorecard from MongoDB’s May 28 earnings release:

Total revenue of $687.6 million, up 25% year over year, beating consensus by $23 millionAtlas cloud revenue up more than 29% year over yearEnterprise Advanced revenue up more than 13% year over yearFull-year fiscal 2027 guidance raised — FY27 revenue midpoint growth lifted to approximately 19.5% from 17% previouQ2 guidance calling for 24% growth, approximately $31 million ahead of consensus
Source: Morgan Stanley Note and MongoDB First Quarter Fiscal 2027 Results

The guidance raise is the headline number Morgan Stanley wants you and other investors to focus on. The full-year outlook was raised by $60 million. In fact, that is more than the Q1 beat and Q2 raise combined, according to the note.

That means management is seeing something in the second half of fiscal 2027 that justified raising beyond what the near-term results alone warranted.

Related: Bank of America resets MongoDB stock price target ahead of earnings

This here is the one soft note from the note. Atlas’ 29% growth came in slightly below elevated investor expectations of 30%-31%, particularly after strong recent results from peers Datadog and Snowflake. 

Management described Atlas as having become more predictable and less sensitive to individual customer movements, characterizing the current trajectory as sustained growth rather than an imminent acceleration.

“We delivered better-than-expected first quarter results, as our go-to-market teams continue to execute well,” said CEO CJ Desai in the earnings release.

At MongoDB Local London, MongoDB announced seven new platform capabilities specifically designed to close the gap between AI experimentation and high-performance production deployment.

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Why Morgan Stanley raised its MongoDB target to $380

The $380 price target reflects a 37x multiple on Morgan Stanley’s calendar year 2029 Base Case free cash flow estimate of approximately $1.27 billion, discounted back to calendar year 2027 at a 10.3% weighted average cost of capital, according to the note shared with me at TheStreet.

The multiple expansion from approximately 33x to 37x reflects the firm’s view that the AI monetization timeline is compressing. Morgan Stanley’s core argument is structural: for MongoDB to see the same AI-fueled inflection that Datadog and Snowflake are experiencing, AI applications must reach a specific maturity threshold. 

Related: MongoDB just got a reality check from Wall Street

Such thresholds include mission-critical to the end customer, significant product-market fit, and material scale relative to the millions of existing applications already running on MongoDB.

That process takes time. But CEO CJ Desai’s commentary on the Q1 call was notably more constructive than in prior quarters. 

He described early AI deployments with enterprise customers and burgeoning momentum with AI-native companies — with MongoDB being deployed for mission-critical use cases and expanding within those customers over time.

My read of that shift in tone is that Morgan Stanley is right to mark it. When a CEO who has been consistently cautious about AI timing language starts sounding more confident, it tends to precede guidance revisions that move stocks.

The product and partnership moves that are building the AI foundation

MongoDB is not waiting passively for the AI tailwind to arrive. The Q1 business highlights show a company actively building the technical and commercial infrastructure to capture it.

The LangChain strategic partnership, announced in the quarter, transforms MongoDB Atlas into a unified backend for production-ready AI agents — integrating vector search, persistent memory, and natural-language querying into a single enterprise-grade platform. That is a direct answer to the enterprise AI deployment use case.

At MongoDB Local London, MongoDB announced seven new platform capabilities specifically designed to close the gap between AI experimentation and high-performance production deployment, according to the earnings release. 

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The acquisition of Clarity Business Solutions strengthens MongoDB’s U.S. Federal vertical. That’s a customer segment with both mission-critical requirements and significant AI investment budgets.

New leadership across product and sales — including a new Chief Revenue Officer, Chief Product Officer for AI and Emerging Products, and a formalized Chief Information Security Officer — positions the company to execute faster on the opportunity CJ Desai described.

For investors, the MongoDB picture is a company where the core business is growing consistently, margins are expanding, the AI opportunity is visible, and management is increasingly concrete about it.

But the stock is priced for a company whose best AI chapter is still being written. Morgan Stanley thinks that chapter starts arriving toward the end of fiscal 2027. At $380, its price target suggests the wait is worth taking.

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