Is GitLab Stock a Smart Play on Generative AI?

There is an iconic scene in the movie Anchorman where the various San Diego news teams converge for a battle royale. Guys in ill-fitting business suits and ugly ties wield chains and swords. A trident flies through the air. An NPR host chops off the arm of a rival with a machete. It’s great fun. In the aftermath, over beers back at the office, anchorman Ron Burgundy remarks, “Boy, that escalated quickly.”

That’s a bit how the current stock market plunge feels. This volatility has hit tech, and especially AI stocks, harder than most because of a basic financial concept called “beta.” Tech stocks are typically high beta. That means they rise more than the stock market in good times and (wait for it) fall more during bad times. And if you can’t handle the high beta heat, stay out of the disruptive tech kitchen.

Click for GitLab company logo

While it’s easy to focus on the blood and tears, these downturns are a great opportunity to buy shares of quality companies, especially fast-growing software firms like GitLab (GTLB) that often trade at a premium based on future expectations. Last year, we finally opened a position after the company’s simple valuation ratio (SVR), which divides market cap by annualized revenue, fell to a 12-month average of 13. That was still twice the average SVR of the stocks in the Nanalyze Disruptive Tech Portfolio, but well below GitLab stock’s rich valuation in years past. The current market jitters have sent the SVR down to 7.7 as of today (6.5 / 0.844 = 7.7 ).

Before we potentially pull the trigger and add shares of GitLab stock, we want to check in with the company. Fortunately, it just released its 2025 year-end results, giving us the first look into how its hard pivot into generative AI has played out since our previous article. Let’s dive in.

Generating Alpha with Generative AI

As you will recall, GitLab’s platform unifies development, security, and operations (DevSecOps) into a single application. The platform serves as a type of digital workspace where developers, designers, and project managers collaborate on software projects. GitLab’s software helps its 30 million users track changes, catch errors early, and automate repetitive tasks so the final product, such as an app or website, works smoothly. Its customers include everyone and everything from solo coders living in their mom’s basement to big companies and organizations like IBM and NASA (for now; more on that later).

GitLab embeds AI in its DevOps platform.
GitLab is going all-in on generative AI. Credit: GitLab

GitLab operates on a freemium model, monetizing mainly through subscriptions for different types of enterprise packages. One big appeal of the platform is that it is available as a regular software-as-aservice (SaaS) offering or on-premise through a customer’s own servers or private cloud, ideal for industries like banking or healthcare with strict data privacy rules. More recently, GitLab intensified its focus on generative AI through GitLab Duo, a suite of AI-assisted tools. This includes GitLab Duo Self-Hosted, which enables enterprises and government agencies in highly regulated sectors to deploy large language models (LLMs) on private infrastructure or cloud services. These AI integrations are expected to buoy revenue growth and net retention rate among enterprise customers. 

More Seats at the Table

And that certainly seems to be the case based on 2025 results (GitLab operates on one of those weird fiscal years, btw). Revenue surged 31% year-over-year (exceeding guidance) to $759 million, driven by enterprise adoption of its top-tier “Ultimate” package and shiny new AI-powered tools. As of Q4-2025, 50% of total annual recurring revenue (ARR) now comes from Ultimate, with advanced security and compliance features favored by customers in highly regulated industries we previously mentioned. Customers spending more than $100,000 per year grew 29% to 1,229 – including 123 clients representing (at least) seven-figure accounts. 

GitLab customer growth
While mid-market and enterprise customer growth is steady, penetration into the world’s biggest companies appears to be lagging. Credit: GitLab

AI-powered Duo accounted for about a third of new ARR in Q4-2025. For example, Barclays dabbled with Duo Pro in Q2-2025 before going all-in with 20,000 GitLab Duo Enterprise seats (at $39 a pop retail) in Q4, in addition to a corresponding number of Ultimate seats. Indeed, 75% of net ARR growth came from seat (i.e., user) expansion by existing customers, implying platform stickiness with a still-respectable net retention rate of 123% (though down from 130% from a year ago). The return on investment (ROI) should be selling itself.

“Customers on our platform are enjoying 15 times faster time to market, four times faster feature delivery, and up to 60% reduction in manual tasks.” – CEO Bill Staples

On the flip side, new base customer ($5,000 ARR) growth was just 10%, implying that maybe GitLab has already caught many of the big fish. However, that does not seem to be the case: Back in Q3-2023, management said GitLab served about 30% of Fortune 100 companies, suggesting there is plenty of runway to add enterprise clients – or steal them away from competitors like GitHub, the DevOps platform owned by Microsoft that had more than 100 million developers at last count. GitLab management did highlight a big win involving one of the “largest cybersecurity companies in a competitive displacement for source code management.”

GitLab 2025 highlights
2025 highlights. Credit: GitLab

In fact, management said its No. 1 focus is to add more new paying customers in 2026 (duh!), but especially in the mid-market and enterprise segments where they feel the opportunity for upselling and cross selling solutions is strongest (duh!). Partnerships with AI cloud providers like AWS Bedrock and Azure OpenAI aim to capture more of these customers, though those stellar 90% gross margins might erode a bit if AI infrastructure costs from these providers go up.

An AI Engineering Buddy

On the innovation front, the focus is front and center on generative AI, especially as competition in this space rapidly heats up. For instance, Microsoft’s GitHub introduced its own AI agent through Copilot. Last year, GitHub’s annual revenue run rate hit $2 billion, with Copilot accounting for more than 40% of the developer tool’s revenue growth. Meanwhile, startups like Cursor AI, an AI-powered code generation platform, reached $100 million in ARR last year at warp speed. Anthropic, a GitLab client, also markets its own coding AI, Claude Code, making it a competitor as well.

Impact of generative AI on various industries.
Software engineering is expected to experience an outsized economic impact from generative AI. Credit: McKinsey & Co.

Naturally, management believes it has the technological edge. Unlike standalone AI code generators like GitHub Copilot, GitLab Duo integrates AI across the entire DevSecOps lifecycle – planning, coding, security, and deployment. GitLab CEO Bill Staples notes this gives Duo an edge because, “AI models need context. GitLab’s platform provides it.” One wonders if Gitlab’s massive code repository provides a competitive moat when it comes to big data they can train their algos on.

More recently, GitLab has launched private beta deployments of Duo Workflow, a next-generation AI tool that autonomously manages code. Workflow is designed for enterprise-scale automation, positioning it as a premium upsell in the next couple of years. Staples likened the AI to having a proactive “engineering buddy” that does things like automatically fix vulnerabilities: While Duo Pro flags a security flaw, Duo Workflow automatically patches it and deploys the update.

“Duo Workflow is our move from AI-assisted to AI-driven software development, leveraging both the power of agentic AI and the comprehensiveness of our DevSecOps platform.” – CEO Bill Staples

Staples makes another pretty obvious statement toward the end of the presentation: “I don’t think a few years from now, developers will be building software without AI.” Probably a better question to ask, “Will AI be building software without developers?” That’s a question for another day.

What to Watch for GitLab in 2026

Let’s wrap it up with a couple of things we’ll be watching from GitLab in 2026:

  • The impact of U.S. government cutbacks. About 12% of ARR comes from the public sector. The company enjoyed its biggest quarter in this sector in Q3-2025, so Staples’ non-comment, “We don’t know what we don’t know,” is a little troubling. Hopefully, they’ll know something by the next quarter.
  • Continued losses at the company’s joint venture in China, JiHu. Tailored specifically for the Chinese market and its unique totalitarian demands, JiHu has not exactly been successful. The company lost $13 million on the venture in 2025 and expects to lose even more, as much as $18 million, this year. Management is actively trying to “deconsolidate” the venture with no firm timeline in place.

GitLab again went with conservative guidance for 2026, projecting total revenue of between $936 million to $942 million, representing about 24% growth at the midpoint. That’s pretty close to last year’s guidance (26%), so we might still see growth close to 2025 if the company can again exceed expectations. Cash flow was very strong in 2025 at nearly $125 million non-GAAP operating income, with expectations of non-GAAP operating income of $109 million to $114 million this year.

GitLab Q1-2026 and full year guidance.
Credit: GitLab

Still, everything points to a slight deceleration in growth, suggesting any big windfall from the AI hype is mid-term at best.

Conclusion

Generative AI is rapidly changing the way many companies do business. Software development will undoubtedly experience some of the biggest seismic changes from automating and deploying code at scale using AI agents. GitLab appears to be positioning itself for that moment. 

However, we have to wonder about its lack of higher penetration into the world’s largest enterprises. Is Microsoft’s GitHub already too well entrenched given the wide-scale adoption of its suite of other software tools? Will startups with cheaper, more powerful AI solutions disrupt the DevSecOps model in ways we can’t predict? Will general artificial intelligence make all of this – including developers themselves – moot? These are the sorts of existential questions that keep us from putting all of our money into tech stocks by allocating most of our funds for dividend growth investing. After all, you can’t digitize a McD’s cheeseburger, right? Right?!