Atlassian has launched a sweeping upgrade to its platform, and the message is crystal-clear: AI isn’t just a feature; it’s the foundation. If you’re working in tech, managing teams, or even just part of a business using Jira or Confluence, this isn’t a subtle shift; it’s a tectonic one.

Atlassian dropped a full suite of AI-integrated upgrades on April 9. The centerpiece? Rovo, an AI-powered enterprise assistant that offers deep integration with Atlassian’s ecosystem — Jira, Confluence, Jira Service Management — and external tools such as Google Drive and SharePoint.

Key Moves

  • Rovo goes GA (Generally Available) for all paying users — no extra cost.
  • Over 20 customizable AI agents help automate everything from HR onboarding to DevOps workflows.
  • New Teamwork Collection and Strategy Collection apps roll out as interconnected, AI-native experiences.
  • AI-driven service management with Rovo agents suggests actions and triages issues.

Analysts Charles Betz, Diego Lo Giudice, Julie Mohr, and Will McKeon-White provide their insights on Atlassian’s annual event announcements.

With Rovo, Atlassian Prepares For The AppGen World

At Team ’25, Atlassian announced a pivot toward Forrester’s AppGen platform trend, highlighted by its infusion of AI and generative AI technologies in its suite of tools such as Jira, Confluence, and Align and leveraging its golden source of IT data and metadata organized in a graph, together with the beta announcement of the Rovo Dev suite. This demonstrates a potential move to try to dominate the market by blending low-code/no-code and large language model (LLM) capabilities with Forrester TuringBots (aka AI and GenAI software development tools).

As CEO Mike Cannon-Brookes put it, the strategy is to generate software, not just snippets of code. We agree with that strategy, but Atlassian will need to fill a broader gap by generating not just “software” (assets) but large portions or even entire software applications, since that is what the AppGen trend will bring.

The Rovo Dev Beta Announcement Proves Good Intentions But Is Playing Catchup

The announcement of the Rovo Dev Beta by Atlassian at Team ’25 showcased the company’s forward-thinking approach to offering various vertical use cases to developers to speed up development work for creating code plans, generating code, reviewing pull requests, automating changes in bulk, and simplifying deployments. Although Atlassian does not position it this way, it is automating several steps of the software development lifecycle (SDLC). The thinking needs to shift, however, more toward automating the process of building applications — new ones — and not just maintaining or fixing issues.

The industry is rapidly evolving with AI technologies such as Cursor and Windsurf that integrate LLM coding capabilities to truly reshape the SDLC by offering advanced coding capabilities and challenging traditional methods with the ability to generate significant portions of applications. Rovo Studio’s launch as a free beta version emphasizes automation and productivity enhancements across the SDLC, yet Atlassian’s modest promotion of Rovo’s capabilities suggests this as an area with room for improvement before it can fully leverage its potential to transform software development.

The System Of Work/Teamwork Graph Continues To Gain Traction

According to its leadership, Atlassian has been working toward a graph-based “system of work” for about five years, and its messaging around this vision picked up noticeably in the past couple of years. Customers seem to be resonating with the idea that a unified graph of people, work, and knowledge offers organizational visibility and a critical semantic foundation for generative AI, supplying enterprise context to answers and actions. The Teamwork Graph spans Jira and Confluence and is expanding with Rovo into more general-purpose search, giving Atlassian a flexible architecture for cross-functional knowledge and coordination. As LLMs demand structured context to reduce hallucinations, the graph becomes not just helpful but essential.

A significant question for us at Team ’25 was Atlassian’s replacement strategy for Device42, a discovery and IT asset management partner recently acquired by Freshworks. The answer, confirmed from several directions, is Lansweeper. This sets the stage for Atlassian to deepen its ITAM and CMDB capabilities, a territory where ServiceNow still dominates. But the strategic play is bigger: If Atlassian can extend the Teamwork Graph into asset and infrastructure data, it could start to challenge ServiceNow’s ontological lock-in with its Common Service Data Model. That opens up a deeper discussion about whether Atlassian mirrors some of those ontology structures or defines an alternative aligned with its own modular vision.

The broader architectural issue — surfacing repeatedly in conversations — is control over the graph. This plays out in three ways: physical access (can systems read from each other?), semantic alignment (do different graphs agree on the meaning of entities such as “pull request”?), and commercial control (who can access the data, and under what terms?). These aren’t theoretical concerns — they’re already creating friction. For example, small startups may seek to pull inordinate amounts of data into their systems for analysis. There already is a looming “tragedy of the commons” with public resources such as Wikipedia suffering from excessive AI agent-driven scraping.

Atlassian leadership confirmed that these tensions are front of mind, and rightly so. Any enterprise architect serious about AI enablement and platform convergence will need to grapple with the messy, political, and strategic implications of graph ownership.

Atlassian Is Now A Full-Fledged ESM Player

Forrester has long focused on enterprise service management (ESM) — the expansion of IT service desk practices into broader business domains like HR, facilities, and marketing. Atlassian’s Jira Service Management has always been used this way, but until recently, the company hadn’t offered domain-specific solutions beyond IT. That changed with the announcement of new offerings for HR, customer service, and marketing workflows.

Predictably, this raised questions about whether Atlassian is trying to compete with Workday, prompting leadership to clarify that they’re not replacing systems of record but layering engagement and request routing on top of them. That’s always been the ESM logic: HR analysts live in Workday, but they need a robust system to manage incoming requests, and Workday lacks that. Now that Atlassian has the low-code/no-code back end and workflow engine to support these use cases, we expect them to continue expanding across the enterprise.

Rovo Increases Availability Of Agentic Experimentation

Excitedly announced as a center of Atlassian’s product strategy, Rovo is now included in Premium and Enterprise licenses for Atlassian’s cloud products. This means that any customer is now free to experiment with agent development on the Atlassian platform (via Rovo Studio). Accompanying enhancements to the platform (including a low-code development interface, preset permissions through Teamwork Graph, integrations, and some prebuilt agents) make it worth exploring as an agentic builder option for Atlassian customers in the rapidly evolving market.

During discussions on Rovo, topics such as the rapid adoption of MCP as a standard (and the company’s support of it) and Atlassian’s participation in the newly announced A2A protocol proved animated — and uncertain. Internally, we’re tracking the authentication challenges with MCP, and while Atlassian reinforced that it was managing the current shortcomings, longer-term fixes will have to involve a large ecosystem of players. Next, we anticipate further investments in customer success — specifically, more ready-made agents/use case support, training programs, and premade risk frameworks to support customers experimenting with citizen agent development.

With the initial release, Atlassian’s focus is on iteration and enabling enterprises to interconnect and embed agents throughout its ecosystem — but be prepared to learn alongside them. Before deploying to a vast population or enabling any agent citizen development, ensure that you’ve developed and are enforcing a risk assessment on any desired use cases. Shell’s governance zoning system can provide a strong foundation when modified for genAI/agentic use cases (for example, incorporating the EU’s AI risk definitions as a dimension).

Supercharged Teamwork And Strategy Collections Increase Platform Stickiness

Atlassian’s Strategy and Teamwork Collections are designed to revolutionize organizations’ operations by embedding AI across every layer of collaboration and execution. These collections unify business and technical teams around shared goals through interconnected apps, real-time status updates, and AI-powered context. Tools like Rovo and the Teamwork Graph also bring unprecedented visibility into how work ties back to strategy.

Despite the innovation, these collections may overwhelm teams already facing digital fatigue, particularly if minimal training is provided. Additionally, the proliferation of agents without strong oversight can create a fragmented ecosystem of redundant or counterproductive workflows. Cross-team alignment — while technologically enabled — is still deeply dependent on leadership and culture. Tools can surface misalignment, but they can’t solve it.

The collection may captivate enterprise-level executives but could risk the erosion of Atlassian’s developer base. The challenge is in balancing its new top-down approach without undermining the grassroots developer consensus that fueled its successful rise. Finally, as more work becomes embedded in Atlassian’s platform, organizations may find themselves locked into a single vendor, reducing flexibility and increasing switching costs over time.

Final Take

Atlassian’s vision is clear: The “system of work” is now inseparable from the AI that powers it. Rovo isn’t just an assistant — it’s the connective tissue between teams, tools, and goals. By removing cost barriers and making AI the default, Atlassian is accelerating digital transformation in a way that’s both bold and pragmatic.

This isn’t about robots taking jobs — it’s about making your job suck less. And if you’re not paying attention, you’ll miss the wave.

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