Artificial intelligence has been one of the top topics of the past year—some are even going so far as to call 2023 “the year of AI.” Recent research from McKinsey + Co. suggests 40% of organizations are planning to increase their investment in GenAI in 2024, as leaders look to streamline processes in the enterprise.
Atlassian’s new AI offering—Atlassian Intelligence—provides the opportunity to add this powerful technology into existing workstreams. Some teams are already benefiting from the tool under an early access program, available only on the cloud. Because Atlassian Intelligence streamlines the service experience, handles natural language queries, and offers assistance with writing, manual tasks, and advanced analytics, tapping into its capabilities could offer unprecedented speed and automation across the Atlassian toolstack.
| According to Contegix’s Executive Vice President of Professional Services Mike Brown, “Atlassian Intelligence will be transformative for tool usability and efficiency.” In a recent conversation, Mike shared his insights into the future of AI in Atlassian tools and how it will be a critical competitive differentiator in the new year and beyond. |
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Natural language processing and machine learning add immense functionality and efficiency to Atlassian tools for cloud users. For instance, Jira Service Management will offer a virtual agent that uses artificial intelligence to field, create, and even solve minor issues. In Jira Software, AI will be able to automatically generate release notes based on issues and data.
AI will also make it possible to use natural text to generate queries to pull data and build reports in Atlassian Analytics. In the past, in order to build reporting, put together release notes, or even write a Confluence page, you had to be well-versed in the data and able to translate your search to Jira Query Language. Now that translation will be automated, eliminating a learning curve and saving even experienced users’ time.
Now that natural language search is possible, service agents will be able to search for issues quickly. This makes Jira much easier to access and use, makes Confluence more efficient, and builds power behind Atlassian Analytics. These tools aren’t just for business intelligence and crunching data anymore. Now an average user will be able to access Atlassian Analytics and automatically build out dashboards just using natural language. For instance, a user could search, “What is blocking the mobile release?” and receive an instant visualization of issues and dependencies.
Combined with the streamlining of development tasks in Jira Software, these new tools can speed operations across the enterprise. For instance, a large retail organization would benefit greatly from being able to generate reports on the fly using natural language. On the development side, in Jira Software, they’d be able to quickly and easily generate release notes and automate workflows. So there’s lots of efficiency to be gained across the organization.
Atlassian isn’t going to be putting out any new feature capabilities for server after February of 2024, and there also won’t be a lot of new features or capabilities on data center. For companies that aren’t already on cloud, it’s time to make the move. Migrating to the cloud ensures that your team can take advantage of Atlassian Intelligence and other newly-released features available only in the cloud.
The cloud migration movement is not over yet. In fact, a lot of organizations who switched from servers to data centers this year are probably going to be going to the cloud in the next year or two. Now that we've gotten a lot of these small, 25-50 user environments off server, we're going to be seeing larger enterprises moving from datacenter into the cloud because Atlassian keeps releasing these new functionalities in the cloud.
Now is a great time to explore the capabilities of Atlassian Intelligence, and preview what it can do. Because Atlassian Intelligence is still in early access, companies rolling it out need to have governance in place to ensure that anything that they are testing currently is done within a sandbox environment.
Enable a test cloud environment as well as a production cloud environment, and just go through some workflows and some use cases. Figure out how the virtual agent in JSM will fit in over top of your current dataset and your current automations. Or in Confluence, test out how Confluence can automatically clean up messy text using Atlassian Intelligence.
First, it’s important to be diligent about governance. Second, once you’ve played around with Atlassian Intelligence, you’ll have a better sense of how it’s going to help you. But also, this is a great opportunity to take stock of your data. Because you’re running the tool on a copy of your data, take the opportunity to evaluate how well your data has been categorized and reported on. AI is a great tool, but it's only going to be as good as the data we give it. If you're working off of bad or choppy data, or you have misnamed custom fields or workflows that go nowhere, you need to get your ducks in a row so that Atlassian Intelligence can function properly. If you’re struggling to do this, an external partner can establish governance and best practices in your organization so that you can have that clean foundation to work from when you enable Atlassian intelligence.
It’s time for every organization to think about the role that AI can play in their operations. Even if you’re just starting out on your AI journey, you can still catch up. What that comes down to is, once again, cleaning up your data. Once you have defined processes and a strategic idea of where you want to create efficiency, you can get the most from AI tools like Atlassian Intelligence.
To learn more about Atlassian Intelligence’s role in optimizing your Atlassian toolstack, talk to a Contegix expert today.