JFrog (NASDAQ:FROG) executives said the company’s cloud business is benefiting from rising software usage tied in part to artificial intelligence experimentation, but management emphasized that it is maintaining a conservative forecasting approach because customer usage patterns remain uncertain.
Speaking at a JPMorgan investor event hosted by software analyst Brian Essex, JFrog Chief Financial Officer Ed Grabscheid and Vice President of Investor Relations Jeff Schreiner discussed the company’s recent results, cloud growth, AI-related demand, security products and capital allocation.
Cloud Growth Driven by Usage, but Visibility Remains Limited
Grabscheid said investors have focused heavily on JFrog’s reported 50% cloud growth and the fact that cloud now represents 51% of total revenue. He said that mix shift is aligned with JFrog’s strategy of moving more customer decisions from self-hosted deployments to the cloud or landing new customers directly in cloud environments.
Asked whether the growth is sustainable, Grabscheid said the company does not have certainty.
“We don’t know. We really, truly don’t know,” Grabscheid said. “We’re happy with the way things are going. We’re built for scale.”
He said JFrog guides based on minimum customer commitments rather than assuming continued usage above those commitments. The company raised the floor of its cloud guidance from 30% to 32% growth to 33% to 35%, according to Grabscheid. If current usage trends continue, he said, the benefit would be reflected in revenue and guidance could rise as commitments are captured.
Grabscheid said customers are currently willing to pay overage rates rather than immediately commit to higher annual levels, largely because AI-related usage remains difficult to forecast. He said JFrog is working with customers to move them to higher commitments, which would benefit both JFrog and customers through better unit economics, but the timing remains uncertain.
AI Adoption Still in Experimental Phase
Grabscheid said many enterprises remain in an experimental stage with AI, beginning with code-assist tools that increase the amount of code being produced. He said companies have not yet reached a stage where autonomous systems are consistently producing production-quality binaries without human involvement.
“We’re still very much at that experimental phase,” Grabscheid said. “We’re certainly not at this autonomous building code, moving into a binary, into a production-level quality binary.”
JFrog executives said increased binary creation and software package activity are broad-based across customers, industries and geographies. Grabscheid said JFrog has three of the five foundational AI companies as customers, but noted that those customers are currently self-hosted rather than cloud customers. As a result, he said, the cloud overusage JFrog is seeing is not concentrated among those AI lab customers.
Schreiner said JFrog sees itself as a “governor” or system of record in an AI-driven software development environment, rather than as the creator of code. He said investors may have misunderstood the impact of AI models on JFrog’s security opportunity, arguing that enterprises will still need systems to manage, record and govern what enters production.
Grabscheid added that JFrog functions as a control plane with visibility into open-source repositories entering an organization, while AI models provide only one aspect of the broader software development process.
Security Demand Supported by Supply Chain Threats
Executives said recent software supply chain attacks have increased awareness around JFrog’s curation capabilities, which Grabscheid described as a firewall around the organization. He said JFrog is seeing a strong pipeline for curation and that decisions around the product are being made more quickly than for some advanced security products, where customers may be replacing existing point solutions.
“The awareness is there at the enterprise,” Grabscheid said. “We’re actively working to convert those pipeline opportunities into actual durable revenue growth for JFrog.”
Schreiner said JFrog’s technical team views “skills” used by agents as a potential future vulnerability injection point for enterprises. He also discussed Model Context Protocol, or MCP, connections as potential exposures that may need to be registered and managed within Artifactory. He said such features could become part of a broader AI governance bundle, potentially alongside AI Catalog, Skills Registry and MCP Registry capabilities.
Grabscheid said JFrog currently monetizes cloud based on data consumption and usage, while security is monetized based on the number of contributing developers. He said that could eventually include machines, but the company does not want to be a pioneer in pricing changes and is watching how larger infrastructure companies evolve pricing models.
Emerging Products and Governance Opportunity
Grabscheid said AppTrust and AI Catalog, released at JFrog’s swampUP conference, are still in the early stages. He said the company is seeing pipeline traction and may provide an update in the second quarter, but those products are not currently considered growth drivers for 2026.
Schreiner said governance is becoming more important as software development moves toward greater autonomy and more agent-based activity. He said JFrog’s internal team views curation not only as a security product, but also as a core part of governance.
On scalability, Schreiner said JFrog’s ability to support many package types and languages is a key differentiator as AI increases exposure across more programming languages. He contrasted source code, where developers create instructions, with binaries, which are compiled machine-readable packages that are deployed into production.
Asked about the possibility of models writing directly to binaries, Grabscheid said JFrog has not modeled any financial benefit from that scenario. However, he said production-ready binaries would be favorable for JFrog if they increase the number of production assets that need to be managed, secured and tracked.
Financial Discipline, Buyback and Customer Growth
Grabscheid said JFrog has maintained discipline around expenses while balancing growth and profitability. He said the company’s first-quarter revenue beat flowed entirely to the bottom line, but added that it is uncertain whether that same level of flow-through will continue throughout the year.
In response to an audience question, Grabscheid said JFrog did not quantify the amount of upside tied to usage over minimum commitments. However, he said that with a $7 million beat and more than $4.5 million carried into full-year guidance, “you can assume that the difference is gonna be your usage over minimum commit, at least in the first quarter.”
Grabscheid also said JFrog’s sales organization is compensated on customer commitments, not on usage above minimum commitments, which aligns incentives with moving customers to higher annual commitments.
On capital allocation, Grabscheid said JFrog’s board authorized a $300 million share repurchase program within six days of the market reaction following Feb. 20. He said the company is operating on a grid and will report its buyback activity in the second quarter.
JFrog also discussed customer growth, including 57 net new customers in the $100,000-plus category. Grabscheid said much of that growth was driven by customers adding security, which can move enterprise customers above the $100,000 threshold. Schreiner added that new cloud lands are occurring at higher average selling prices than several years ago as customers increasingly land on the broader platform and add security earlier.
About JFrog (NASDAQ:FROG)
JFrog is a software company specializing in DevOps solutions designed to streamline the management, distribution and security of software binaries. Its core offering, JFrog Artifactory, serves as a universal artifact repository manager compatible with all major package formats, enabling development teams to store, version and share build artifacts across the software delivery pipeline. The company's platform also includes tools for continuous integration and delivery (CI/CD), security scanning and release automation.
Among JFrog's flagship products are JFrog Xray, a security and compliance scanning service that analyzes artifacts and dependencies for vulnerabilities; JFrog Pipelines, a CI/CD orchestration engine that automates build and release workflows; and JFrog Distribution, which accelerates the secure distribution of software releases to edge nodes and end users.
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