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Atlassian is extending its work intelligence and collaboration technologies at a fast rate. The company used its Atlassian Team ‘24 conference in Las Vegas this month to showcase recent platform updates, new developer tool extensions and human-AI workflow advancements designed to make life more productive for software application developers and businesspeople alike.

Already this year we have seen the company update its Jira project management & issue tracking platform by making its Compass application component management tool available within it. As well as new data lake and analytics technologies, the company has also extended its Atlas ‘teamwork directory’ with additional Business Intelligence (BI) functions, the technology is designed to enable teams to communicate directly on project progress and status. Now enveloping all the organization’s toolsets is Atlassian Intelligence, advancements designed to provide AI developed internally and from OpenAI and make use of the company’s ‘teamwork graph’, a tool that pulls in data from Atlassian tools and other SaaS apps to provide a view of an organization’s goals, knowledge, teams and work.

Now looking to promote what it heralds as a new era of AI-empowered human-machine workflows, Atlassian has now put generative AI functions in its editor.

A number of testers and early adopters have been using the AI-enhanced editor in Confluence (a web-based corporate wiki service), Jira and Jira Service Management to get to a first draft faster, find action items and improve their writing. Now, Atlassian Intelligence in Trello (a kanban style teamwork project management tool) and Bitbucket (a Git-based continuous integration tool optimised for Jira) helps users generate pull request summaries, release notes and other key pieces of information.

AI-powered summaries 

“Atlassian Intelligence already offers AI-generated summaries in Confluence and Jira Service Management that help teams get up to speed quickly so they can take immediate action. Soon, issue summaries will be available in the new, combined Jira (formerly Jira Software and Jira Work Management). Further, you can get a summary by hovering over a Confluence, Jira, or Google Docs Smart Link,” said Sherif Mansour, head of AI, at Atlassian. “[Developers can] say goodbye to creating issues one by one and let Atlassian Intelligence do the heavy lifting. [Users] simply choose what issue type they want suggestions for and AI work breakdown makes suggestions for breaking epics into issues, or issues into sub-tasks. After a user customises and approves, all the work items are created and properly nested. AI work breakdown has started rolling out in beta.”

Mansour highlights the problem of trying to reproduce a bug, or how to request time off – and he says that sometimes showing is easier than telling, especially when the software team is distributed, at scale, or both. This is where Atlassian Loom’s AI workflows come in. Acquired in October 2023, Loom is an asynchronous video messaging tool that lets users communicate through instantly shareable videos. Loom’s AI workflows is capable of transforming videos into Jira issues, Confluence pages and step-by-step guides that can be customized for various audiences. 

  • Bug reports: When a bug is documented with a Loom video, Loom AI workflows auto-populate Jira issues and pull request descriptions from a Loom video demo
  • Documentation: Developers can use AI workflows to craft documentation in Confluence and AI workflows follows the steps outlined in an engineer’s video to create standard operating procedures (SOPs), step-by-step guides etc.

Also coming soon is AI in whiteboards notes Mansour. “Kick off a workshop or jam session by brainstorming ideas on a Confluence whiteboard. Atlassian Intelligence will pull from Jira Product Discovery insights, Jira tickets, and Confluence pages to generate ideas and create virtual sticky notes for them. Then, AI helps you organize by grouping similar ideas together on your whiteboard. When you’re ready, you can move the project forward by converting your whiteboard into a Confluence page, or a Confluence page into Jira tickets.”

Other forthcoming functions include a virtual agent in the help centre. Jira Service Management’s AI-powered virtual agent already helps teams who use Slack reduce ticket volume by facilitating support interactions like requests for software licenses and VPN troubleshooting via chat. Virtual agents will soon be available in Microsoft Teams and the help centre inside Jira Service Management as well. Users will type a question in the help centre search box and AI will fetch the answer, along with links to related resources.

“Using natural language to create automation rules makes fast work of a time-consuming task. Simply describe what you’d like to automate and AI will generate the rule for you. Customers who’ve used AI to create rules in Confluence have already automated 5x as many tasks as those who haven’t tried it yet. Imagine all the time they’re saving. [Developers] can use natural language to build automation rules now in Confluence, Jira, and Jira Service Management,” said Mansour.

First, there was DevOps, then came DevSecOps, FinOps, MLOps and even HugOps (literally, a hug for your fellow humans). Atlassian now wants us to get ready for AIOps in Jira Service Management – essential for on-call heroes who need to separate the signal from the noise amidst a flurry of alerts. Atlassian Intelligence will group similar alerts together, detect patterns, and suggest potential root causes. It will also recommend resources such as runbooks and knowledge-base articles for time-saving solutions. Finally, AI will automate post-incident reviews to prevent recurring incidents.

Atlassian Rovo

A key product announcement at Atlassian Team ‘24 was Atlassian Rovo, a new product that helps teams find information scattered across diverse systems, learn through AI-driven insights and take action through AI agents. The company calls it the next step in human-AI collaboration. Underneath it all is the Atlassian platform’s common data model, which connects and organizes data from Atlassian products, Atlassian Marketplace apps and connected third-party SaaS tools. 

“We call it the teamwork graph. With over two decades of experience and a wealth of contextual information to draw upon, Atlassian can enrich AI, collaboration, automation, and analytics like nobody else. We’ll keep enhancing Atlassian Intelligence with features that let teams turn more dreams into reality while keeping your data secure,” added Mansour.

In terms of key trends and takeaways here, we might respectfully suggest that this is Atlassian being more vocal and more connected than at any time in the past. Obviously there are competitors to the company’s platform (ServiceNow & Asana would probably be usual suspects) and GitLab is obviously a central player in the project tools and developer coding management space. With low-code purists also vying for a share of voice in the software automation space, the entire spectrum of software functionalities here has the potential for development and expansion now, specifically of course because of the application of generative AI, as in indeed the case here. Magical analyst house Gartner classifies Atlassian as a player in the ‘enterprise agile planning tools’ space – and if that’s not a category classification that the company uses directly, then it surely doesn’t object to it. 

Atlas may have shrugged, but Atlassian appears to be shrugging off its competitors with a beefed-up toolset.