Monthly insights into human-AI collaboration – and how to make it work for your teams.
Our ongoing series brings you essential AI news and takeaways every month, helping you stay informed and ready for what’s next in the world of artificial intelligence.
January 2026 edition
Teammate agents are what’s hot in 2026
Companies are figuring out that enhanced collaboration is the ticket to maximizing AI ROI.
The big picture: Enterprise AI tools pivot into teamwork
In the U.S. alone, generative AI has become a part of the average 18- to 64-year-old’s life markedly faster than comparably transformative technologies in the past, such as the PC and commercial internet. But the enthusiastic embrace of AI hasn’t translated into meaningful business outcomes. According to our research only 4% of companies report seeing AI ROI.
Our findings fall in line with other recent studies that drew the same conclusion: Though individual AI users say that these tools are making them more productive, most of their employers aren’t seeing company-wide transformation.
The 4% of companies that are maximizing the benefits of AI are doing something different. They’re shifting their application of AI to facilitate teamwork instead of hoping that individual productivity gains will translate into enterprise-wide outcomes. They’re building workflows that turn individual knowledge into company-wide memory, setting up systems that let AI coordinate work across teams, and using AI as an active collaborator instead of just another tool.
A new report from the Boston Consulting Group supports Atlassian’s findings, identifying semiautonomous collaboration as the “inflection point and the start of real value creation” in companies’ adoption of enterprise AI tools.
The takeaway: To maximize AI impact, treat enterprise AI tools as collaboration facilitators
Companies that focus on AI-enhanced coordination instead of individual productivity are nearly twice as likely to say that AI has significantly transformed their organization’s efficiency. The biggest gains come when AI is integrated into how organizations share knowledge, strategize decisionmaking, and align around common goals. In other words, AI works when it becomes a core member of the team.
Try this
- Put AI where the action is. Tie AI to the systems where work actually happens, such as meeting notes, tickets, roadmaps, stakeholder feedback, and approvals.
- Incentivize knowledge-sharing. Encourage defaulting to public channels over DMs so questions, context, and decisions become reusable inputs rather than dead ends.
- Reinforce coordination. Regularly highlight cases where better documentation, shared context, or cross-team visibility led to smarter decisions or avoided wasted work.
AI slips into the workflow stack
Enterprise AI has entered its infrastructure era.
The big picture: The shift from AI tools to AI systems
In this new AI-as-teammate paradigm, enterprise AI agents are evolving from standalone assistants to integrated systems that plug into the platforms and workflows that teams are already using. This lets AI carry context across teams as work unfolds – rectifying the data siloes and learning vacuums that MIT researchers recently identified as a major culprit for mediocre AI outcomes to date.
Atlassian’s own Rovo has been at the leading edge of this approach, pulling data from project trackers, repositories, and third-party apps while also offering advanced search, chat, and customizable agents that act on behalf of teams within their existing tools. Others are now starting to catch on.
The takeaway: AI delivers the best results when it’s embedded into collaboration platforms within daily workflows
Organizational transformation happens only when AI is incorporated into the processes and pipelines of how teams’ work gets done.
Try this
- Prioritize building AI into key existing systems. Integrate AI into project tracking, team communication, and review workflows so it continuously absorbs context from real work, instead of depending on isolated prompts or manual input.
- Design workflows so context accumulates automatically. Ensure projects, discussions, and decisions are consistently linked, updated, and owned, making it easy for AI to follow what’s happening across teams and carry that context forward instead of starting from scratch each time.
- Use AI to coordinate work, not just speed it up. Deploy AI in moments of alignment, such as status reviews, cross-team handoffs, prioritization, and follow-ups. This helps teams reduce duplication and surface dependencies, while also clarifying shared goals.