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Team 24 - seven takeaways on the ongoing evolution of digital teamwork and the role of AI

Phil Wainewright Profile picture for user pwainewright May 17, 2024
A final look back at Team 24, where Atlassian unveiled updates to its flagship products Jira and Confluence plus new additions Loom and Rovo, with some key takeaways about the future of digital teamwork.

Mike Cannon-Brookes and Scott Farquhar, Atlassian co-founders and co-CEOs, laugh together on stage at Team24
Co-CEOs Mike Cannon-Brookes and Scott Farquhar (Atlassian)

Atlassian's Team 24 conference the other week saw several changes in the teamwork vendor's product line-up. Collectively, these changes provide a useful insight into how digital teamwork is evolving in the enterprise, as Atlassian responds to emerging customer needs and a competitive landscape that includes the likes of Microsoft, Google, ServiceNow and Slack owner Salesforce. Therefore there are takeaways for any organization that's looking to advance its own digital teamwork infrastructure — what diginomica calls the Collaborative Canvas, whether they're an Atlassian customer or not. For sure, the advent of AI is having a big impact, but there are equally significant trends gaining momentum at the same time.

1. Work management is core

The increasing automation of the flow of work through an organization's processes has meant that the tools that manage workflow and related resources are growing in importance. Of the four distinct teamwork patterns that make up the Collaborative Canvas, alongside content, messaging and functional applications, workflow is therefore becoming more and more strategic, particularly when connecting processes across different functions.

The new iteration of Atlassian's flagship work management product, Jira, responds to this trend by bringing together three previously separate products. There's some tortuous history here. Jira was Atlassian's first product, originally introduced back in 2002 as a web-based bug tracker for developers, but with project planning capabilities that soon appealed to other software engineering roles. As long ago as 2015, Atlassian decided to widen its appeal to non-technical users with the launch of a general-purpose version called Jira Core, alongside the launch of the more specialized Jira Software, which added functions useful for agile development teams. For the next few years, the company's focus shifted to making its products cloud-first. Then in 2021, Jira Work Management took the place of Jira Core, again targeting non-technical users, and adding general-purpose project management capabilities over time, such as calendar and lists. Meanwhile various initiatives to provide an overview of ongoing projects led to the launch of Atlas in 2022, a product that brought goals, project status and reporting together in one place. After evolving as separate products, the new Jira brings all of these various strands together. Dave Meyer, Head of Product for Jira, sums up:

In some sense, we're combining products that we introduced relatively recently, but in another sense, I think it's a culmination of ideas that have been germinating for a decade.

By the way, this is not the first time Atlassian has introduced and then discontinued products — in 2018, it somewhat controversially discontinued two messaging apps having realized they wouldn't be able to compete with Slack — although in the case of Jira, Atlassian is managing migrations into the new unified product rather than leaving customers stranded. In general, customers have welcomed the move because it simplifies licensing and user management. It also reflects evolution in the customer base, as Meyer explains:

The decision to brand the new integrated product as Jira was driven by a belief, not just in, 'Hey, we can build a product that's valuable to a non-technical team,' but that where we really see our customers going is cross-functional collaboration. That's really the headline story ... We can do a lot of stuff in Jira to bring the product team and the marketing team or the sales team operations closer together, and there's value in the shared platform.

2. Improving the user experience

But in order to reach such a broad cross-section of users, work management products must make it as easy as possible to get started and quickly become productive. It's not just a matter of easily understanding how the product works. Often, people simultaneously have to get used to working effectively as part of a distributed team where much of the communication with colleagues is digital. The user experience (UX) is crucial here, but Jira's history isn't helpful. Because of its roots in software development, Jira earned a reputation over the years for being hard to use — and until now, Atlassian preferred to carve out a separate, simpler product for non-technical users. To help persuade prospects and returning customers that it has changed, the new Jira will roll out with a fresh user experience. Meyer says:

The number one thing we will invest in over the next six to 12 months is, Jira will look different. That's a direct response to, okay, we can run a hundred marketing campaigns that is, 'Hey, take a fresh look at Jira, Jira is not the same software development tool that you have in your head from the on-prem version from seven years ago.' If we can get somebody to take a fresh look at Jira, that actually has to look different.

The recent addition of AI-powered capabilities will go a long way to help, too. One of the Jira features that's popular with developers but forbidding for casual users is Jira Query Language (JQL), a scripting language for power users to build queries and automations. Now, instead of having to build a JQL query to order, filter and sort issues and tasks, a user can simply view the data in a simple list view and ask questions conversationally. The AI then converts that natural language search query into JQL behind the scenes, and responds straightaway with a result. Meyer comments:

Literally the first AI feature to land in Jira was converting natural language search into JQL, where now the user doesn't have to learn JQL or even read the docs and take a training class. They can take advantage of the structure right away.

3. The growing role of metadata

As well as a fresh UX, the new Jira also has a lot going on under the surface. As workflows have become more automated, there's been a growing trend among digital teamwork vendors to define a metadata layer to help them make sense of the data they gather about the work they're managing across the enterprise. This is typically a graph database that maps all the various entities and the relationships between them, and has proven useful in areas such as helping to make search more relevant, identifying potential team members, or analyzing performance. With the advent of generative AI, vendors have found graph mappings particularly useful for building accurate prompts to instruct the AI models. Atlassian is no different. It has defined a teamwork graph that maps the relationships between people, knowledge, actions and goals, and has already extended this to include the semantic index used for AI search and some foundational AI models.

The teamwork graph is part of the underlying platform powering what Atlassian calls its system of work, which encompasses not only Jira but also the other teamwork products in the portfolio, creating a toolbox for every knowledge worker. Jira contributes the essential work management element of this toolbox. Meyer says:

We're breaking the nebulous concept of work down into tasks, attaching metadata to those tasks. Taking those tasks through the workflow is something that, if not every knowledge worker does, the vast majority of knowledge workers do... The Jira product, the ultimate goal is that we're creating something that's valuable for every single knowledge worker in an organization, similar to Microsoft or Google Workspace suite.

In creating a single horizontal product rather than having one work management product for software developers and another for other teams, Atlassian brings Jira into line with its knowledge management platform, Confluence, as well as more recent offerings such as Loom. He goes on:

If we can build a single set of capabilities that are as valuable to a marketing team as they are to a software team, it's not a crazy idea for Atlassian. We've only built one version of Confluence for 20 years, and hopefully Confluence provides equal value to the marketing team as it does to a software team. We look at a product like Loom and it's a similar story — it's everything from executives doing video overviews to filing a bug report.

4. Tying work to goals

As work becomes more connected and tools emerge to help manage it across the enterprise, an emerging trend is for work management vendors to start tying individual tasks and projects to broader goals and outcomes. Previously, goal-setting has tended to be a standalone exercise, and one of the challenges is making sure that goals align across the enterprise. Meyer comments:

In the past, you would have had, the software team has its KPIs, and the marketing team has its KPIs and sales team has its KPIs, and they're all laddering up to maybe a revenue goal that some executive, a general manager has. But the only person that ever sees the thing that's actually going to move the needle for the business is the general manager. And all these teams are kind of isolated in their silo.

There's a twofold argument for aligning goals. Firstly, it's more motivating if individual teams can see how their own goals contribute to the wider organization's mission. Secondly, it can be counter-productive if one team's individual goals conflict with another's — for example, a development team that's trying to control costs might not be able to meet a delivery date that the sales team needs to hit its revenue targets. It's this kind of operational awareness around goals that has led Atlassian to fold the goals functionality from its Atlas product into Jira and the system of work platform, so that each team can see how their own projects and goals impact what other teams are trying to achieve. The Atlas functionality guides teams to set their goals within the broader enterprise context, as Meyer explains:

I do think that what we've built into the Atlas product and is coming to the platform is relatively opinionated. We don't just say type in the goal and put in the number. There's a field for why are you doing it? What does this ladder up to? What is the strategy behind it? Those are fixed fields.

Organization leaders can then track and analyze how projects and resources are coming together to achieve those strategic goals in Jira Align, a separate product that provides an executive-level view of work and projects across the enterprise. The teamwork graph is crucial to making sense of this enterprise-wide view, underlining the importance of the metadata layer. But with the integration of goals still relatively new, even though Atlassian is ahead of most teamwork vendors in thinking about this, Meyer admits it is currently still a work in progress:

I think we still have a lot of work to do. The system of work is a vision and a north star more than something that we have shipped to our customers today. There's certainly work to do to make sure that hierarchy and connections from Jira to Jira Align are clear. Ultimately, it's about rationalizing some of these shared concepts between different products.

5. Connecting content is crucial, too

Teams share and store knowledge as content. The paper-based origins of knowledge work means that content has traditionally been shared in standalone documents. Atlassian's history as a web-based vendor serving developers means that Confluence, its knowledge repository, has a different pedigree that aligns well with current trends in the evolution of content to become more connected. My own view is that Confluence was held back in the early days by its primarily server-based architecture, but following its transition to being fully cloud-first, those web-based, developer-led origins now allow it to shine.

Conceived as a wiki, Confluence documents are actually web pages — or more, accurately, nodes on a directory tree. Rather than locking knowledge away in a closed document, they are inherently designed to be connected, and shared by default. It's well suited therefore to participate in the Atlassian system of work alongside Jira and the other components. As Erika Trautman, Head of Product for Work Management at Atlassian, puts it:

The other thing that I think is unique about Confluence's perspective, in contrast to the other places you can store information as a repository, is that we really think about the free flow of knowledge in connection to the work and in connection to the workflow. We're focusing on breaking down silos, between teams, between products, certainly within the Atlassian platform, but also extending into the third party.

I think a lot of the substitutes or alternatives for Confluence are like, 'Well, what we do is, we're how you create documents and images and stuff.' We're very much thinking about that in service of what you're trying to accomplish as part of the work.

Confluence's wiki architecture also adds structure around the knowledge it contains. That organizing structure can be extended out to content stored elsewhere through the use of 'smart links', either embedded within individual pages or directly as nodes in the Confluence directory tree. The external content in those third-party apps and resources might be a document or folder, or even a Figma design, YouTube video, or other type of content. Confluence therefore becomes a knowledge hub that organizes and connects relevant content into the flow of work and also captures the output. She explains:

When we're thinking about teamwork, generally, there's the ideation and conceptualization of work. Some of that happens in Confluence, some of it happens in Loom, some of it happens in third parties. That then turns into the work itself. We hope that goes into Jira at that point. And then from the work, you want documentation about the work, you want alignment, you want reporting on the work. That then can come back out of Atlassian's platform and you've got documentation that then reinforces that source of truth. So that the full lifecycle of work from ideation through execution becomes the foundation for your knowledge repository.

6. Content is multi-modal

Enterprise content has largely been text-based, but the rising use of audio and video along with AI's ability to add captions and transcripts now allows the digitization of content from other modes of communication. Atlassian's recent acquisition of Loom to become another pillar in its system of work keeps pace with this emerging trend. The integration of Loom not only brings video creation directly into Confluence but will also convert content from Loom videos into other structured formats, as Trautman explains:

A key part of the evolution, how we're thinking about Confluence, which is, communication is obviously not just about text on a page. There are many modes that are important for communication. Obviously, text on a page is a very powerful one. But the free flow of ideas — this is why we're so excited about pulling Loom into Confluence and deepening those integrations...

We're introducing native integrations with Confluence so that you'll be able to create Loom videos right within Confluence. This is the first step for us to really unlock the power of the acquisition and the integration between Loom and what we can do with it from that whole work lifecycle perspective... Or maybe what you want to do is create a Loom where you're talking about the new HR policies, and then you want Loom to turn that into a page for you. Then you'll have both the video and the page. We're seeing standard operating procedures as a huge area of growth for Loom, where people want to record the standard operating procedure, and then turn it into the related document.

Having a choice of modes makes sharing more effective and accessible. A study carried out last year at Atlassian compared the engagement with written content against video when managers sent out weekly status updates. Trautman says:

What we found was, in terms of driving understanding, they were equivalent. But the managers who sent Looms, their teams felt significantly more connected. So that human side, Loom is really outstanding at that.

The steps Loom has taken to make it easier for people to edit and polish videos helps make it less intimidating to create them, and simpler to adopt for those who find this mode of communication easier than the written word.

7. Multiple roles for AI

Easier video creation is just one example of how AI is removing many of the previous barriers that have held back effectvie teamwork and collaboration in the enterprise. The impact of generative AI in particular is being felt in four main ways:

  • Facilitate — instead of having to learn how to use a complex application, a user can describe what they want in natural language, and after a conversation with the AI to clarify their intent, the AI then takes care of figuring out how to make it happen. This shortcuts the time it takes to get something done, making it simpler to try out different options or to achieve complex outcomes in applications like Jira, which have in the past proved challenging for new users because of the learning curve required to get started. Meyer comments:

The two sides of the Jira coin is, it's extremely flexible and extremely configurable. That creates a ton of value for organizations that successfully adopt Jira, but also becomes a big hurdle for getting to that level of adoption rates. I see different types of workflows and fields and screens, and how do I set all of this up to map to my company's process? That's where I get really excited about what we can do with AI, where instead of having to navigate through all those screens ... you can just describe the kind of configuration you want, and we can create it for you and I can actually replace 20 different screens buried in the settings of Jira, to configure all of that.

  • Find/retrieve — similarly, users can frame search queries using natural language instead of needing to know the precise keywords and phrasing that will produce the answers they're looking for. In Atlassian's case, the new Rovo intelligent agent interacts with the underlying teamwork graph to interpret queries and find relevant answers.
  • Summarize/draft — summarization is one of the most common tasks performed by generative AI, saving time by providing a digest of comments made in a thread or a précis of a document. Atlassian has added these capabilities to Confluence, while Rovo can also produce short 'knowledge cards', which provide in-context snapshots of specific information about projects, goals, people and so on.
  • Transform/analyze — here, AI converts content from one format to another, or provides insights and suggestions based on analysis of data. Examples from Atlassian include Loom's ability to convert video bug reports into Jira issues, or turn a video description of a process into a standard operating procedure document, while Confluence is able to transform a completed whiteboard into a to-do list or other format.

My take

This tour through several of the announcements from Team 24 underlines how much is changing in the world of digital teamwork and work management. The impact of AI is significant, but there's a lot going on beyond that — accommodating new modes of communication, building out work management graphs, aligning work more closely with broader business goals, and getting more oversight of workflows and resources as automation accelerates.

And that's just the technology. There's a big change management challenge ahead as people adjust to the more open and accountable landscape of digitally connected patterns of work. People are not used to this level of visibility across an organization, but it's only going to increase as digital tools proliferate. In the past, the focus was very much limited to individual projects, teams and functions, because the technology simply didn't allow for a wider perspective. Now that it becomes possible to match up individual team objectives with overall enterprise goals and customer outcomes, a whole new world opens up that requires a different mindset and organizational culture.

Atlassian has always thought deeply about the nature of enterprise teamwork and how best to support it. It recently published findings about the evolution of digital teamwork in an age of increasingly distributed teams. That thinking has informed these latest product changes. Acquiring Loom and betting on a reformed Jira are bold moves, but they're in line with important trends in the wider market and help Atlassian stand out against its more document-centric rivals such as Microsoft and Google. 

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