New industry analyst reports recognize Atlassian as a leader in service management
AI is changing expectations for service. Employees want help that feels seamless. Customers want answers without long waits or repeated explanations. Operations teams want to get ahead of incidents and prevent disruptions rather than just respond.
Those expectations rest on a critical dependency: context. AI is only useful when it can see the full picture – from people and knowledge to services, assets, and code – and all connections in between.
It’s also the place organizations struggle the most. A recent commissioned survey from Forrester Consulting found that only 18% of organizations say their knowledge is part of a broader context graph or unified data layer1. Inability to provide AI systems with sufficient organizational context was cited as the biggest hurdle for enterprises looking to adopt agentic AI in service workflows AND those who had already deployed it. It’s a problem across the entire maturity curve.
That is why the latest analyst recognition matters: it validates the shift Atlassian has been building toward, where service teams have the connected context they need to make AI useful across support and operations.
Atlassian has been recognized as a Leader in The Forrester Wave™: Conversational AI Platforms for Employee Services, Q3 2026, with Forrester noting that “Atlassian’s goal with Rovo is to unlock better teamwork using AI. To support this vision, the vendor is prioritizing connected user context across tools, proactive employee support, and embedding Rovo into where people work.”
Atlassian has also been recognized as a Leader in the 2026 Gartner® Magic Quadrant™ for IT Service Management Platforms.
The important story is not the recognition alone, though it is certainly appreciated. It is what we believe the research signals: service and operations are moving away from clunky, disconnected experiences toward connected, context-rich ways of working – on and off our platform.
Atlassian customers are already sitting on top of one of the richest context layers in the industry. The Teamwork Graph spans over 150 billion objects and relationships – so teams spend less time piecing together answers, while AI has the data it needs to take action.
Employee support should meet people where work happens
Support teams are often measured on speed, but speed without context creates more friction. Employees don’t want to repeat their request history. Agents don’t want to play detective across a maze of tools. And knowledge – the stuff that makes or breaks good support – is usually scattered across systems, threads, and documents that AI can’t reach.
Atlassian’s Service Collection is changing that equation. Rather than bolting AI onto a traditional ticket queue, Atlassian is embedding AI-powered support directly into the collaborative surfaces where work already happens. The Teamwork Graph surfaces trusted knowledge, past requests, relevant people, and connected work across Atlassian and third-party tools, giving AI the depth of context it needs to answer common questions, triage requests, suggest next steps, and connect support teams across the business.
Forrester’s report stated the following:
Atlassian stands out for its context capabilities (its Teamwork Graph) and ability to embed Rovo into key collaborative surfaces, including multiuser chat channels.”
Employee support does not happen only in a portal. It happens in chat, in search, in Slack channels, and across the teams that own the work. Atlassian’s vision is to proactively bring context to all of those surfaces, improving employee experiences and freeing up service teams to tackle larger, more complex work together.
Ops needs context before, during, and after the chaos
For operations teams, context is just as critical. During an incident, responders need a clear picture of what changed, who and what is affected, and what has worked before. Without that context, teams lose time switching tools and rebuilding the story from scratch while everyone is asking, “Any update?”
We believe Atlassian’s recognition as a Leader in the 2026 Gartner® Magic Quadrant™ for IT Service Management Platforms underscores the strength of Jira Service Management as a connected service and operations platform. It brings critical service and operations work into one place so teams can move from detection to resolution and learning without losing the plot.
AIOps capabilities extend context to help teams spot risks earlier, understand service dependencies, and reduce repeat issues. New integrations bring telemetry, asset intelligence, and log data directly into Jira Service Management, giving teams the diagnostic context they need without constant tool-switching to stop problems in their tracks. The best incident is still the one nobody has to handle at 2 a.m.
And when things do inevitably go down, AI and context are key again – from surfacing similar incidents and dependencies, identifying likely root causes, and suggesting mitigation steps.
Bye-bye, service quo
The future of service is already here, and Atlassian is leading the way. AI-native service management means support and operations teams get the full picture, act with confidence, and stop wasting time piecing together what should have been obvious from the start.
Context is what matters. It’s how teams shatter the service quo – one less-frustrating experience at a time.
- Forrester Consulting: Q2 2026 Enterprise Service Management Survey. Commissioned by Atlassian.
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Gartner, Magic Quadrant for IT Service Management Platforms, By Rich Doheny, Jen Lichucki, 27 July 2026
This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Atlassian.
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