At Team '25, Atlassian introduced the Teamwork Collection, bringing together Jira, Confluence, and Loom, significantly enhanced by Atlassian Rovo. This integration is designed to break down information silos and foster more effective human-AI collaboration.
Previously, accessing these powerful tools, including Rovo's capabilities, required separate subscriptions and considerations. Now, with a single offering, enterprises can leverage AI-enhanced workflows without the complexities of intricate setups or individual budget approvals.
While this removes many initial financial and technical barriers, the real opportunity (and challenge) lies in maximizing AI's value within your organization.
This article will guide you in building a roadmap to ensure you not only adopt AI-powered tools, but truly optimize its potential for measurable returns.
Achieving true, measurable ROI from AI goes beyond mere access (as previously discussed in Rovo for Everyone). To integrate these capabilities into your existing workflows and foster a culture of effective utilization requires a thoughtful, strategic approach.
Common challenges preventing effective AI implementation and adoption include:
Think of it as a maturity journey, progressing through levels of sophistication. Drawing inspiration from established industry models, ServiceRocket’s tailored approach to AI adoption maturity includes:
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Many organizations find themselves at the earlier stages of this maturity model. To truly unlock the full potential of the Teamwork collection, a strategic roadmap is needed to progress through these different levels of using AI-powered tools.
Once you have assessed your current AI maturity and identified some opportunities, the next crucial phase is to develop an evolving implementation roadmap that strategically integrates Rovo AI and Teamwork Collection features to advance your organization along the AI maturity spectrum. Your roadmap should be dynamic, prioritizing initiatives that deliver measurable value and aligns with your business objectives. Here is how to approach it:
Begin by establishing your current AI baseline (Step 1) and defining your near-term AI destination. Simultaneously, develop a rigorous understanding of how AI can deliver quantifiable business outcomes within your specific operational context. Knowing this will inform your strategic choices and enable effective AI impact assessment.
Break down work processes into stages and identify where Rovo Agents can contribute or automate. This includes leveraging AI to "shift left". For example, AI can handle initial data gathering, preliminary analysis, and content drafting to empower earlier stages of work. Also, a key part of these initiatives is removing complexity by reducing unnecessary steps within workflows, thereby streamlining operations.
Develop a clear, phased plan that balances quick wins with long-term strategic goals for AI integration. This involves prioritizing initiatives based on potential ROI versus implementation effort, focusing on building momentum and delivering quick wins.
Identify and build necessary knowledge base entries and examples to guide AI agents and ensure grounded, accurate outputs.
Diligently following these steps can lead to enhanced productivity and the development of a future-proof System of Work.
The implementation roadmap created in Step 2 provides the strategic framework. But to truly get the anticipated benefits, the team has to adopt and use the Rovo AI-powered Teamwork Collection effectively. This step will focus on the critical human element: How leadership can foster the genuine adoption and skills needed to transform a new technology investment into real results?
Here’s how to champion this transformation:
Clearly explain the vision and benefits that Rovo AI can bring. Position it as an evolving capability instead of a static solution. Be up front about changes, timelines, and support while encouraging open, two-way dialogue to address concerns. Also, regularly share progress and success stories.
This practical, hands-on training should be tailored to their workflows in Jira, Confluence, and Loom, focusing on real-world Atlassian Rovo use cases. Then, encourage internal AI champions to explore and share novel applications, and maintain a dynamic knowledge base that is regularly updated to reflect the latest AI functionalities and evolving best practices.
Implement robust feedback channels so that users can ask questions and offer suggestions for improvement. Keep an eye on adoption metrics (or how well AI is being used). Regularly re-evaluate AI integration strategies and what skills are needed to adapt to new capabilities. Ensure your operational methods evolve accordingly as well. Finally, recognize and celebrate AI-driven successes and clever, new adaptations. This will reinforce agility and a forward-thinking culture in your organization.
By embracing these strategies, your organization can effectively integrate AI, transforming the Teamwork Collection and Rovo into a true organizational capability that maximizes value and propels future success.
YC Lian is ServiceRocket’s Executive Director of Technology.
Accessing AI-powered tools isn’t enough. To unlock true efficiency, organizations need a strategic partner. ServiceRocket’s deep expertise with AI implementation ensures your organization will leverage Atlassian Rovo to its full potential, driving maximum impact and achieving measurable business results.
