Atlassian: Research shows organizations should approach AI at the team level, not the individual level, to achieve true ROI

2026-07-21 · Source: VentureBeat · Field: Business & Management — Corporate Strategy & Leadership, Operations & Process Management · Depth: Intermediate, quick

Summary

Atlassian's Teamwork Lab, led by Dr. Molly Sands, reveals that organizations often mismanage AI adoption by focusing on individual efficiency rather than team-level collaboration. The annual State of Teams Report, based on surveys of 12,000 global knowledge workers and 200 Fortune 1000 executives, found 89% of executives observed individual speed improvements, yet only 6% could pinpoint clear AI ROI. In contrast, 14% of teams successfully translated AI usage into tangible value. These high-performing teams excelled in three areas: establishing shared context through "context graphs" in tools like Jira and Confluence, redesigning entire end-to-end workflows, and fostering a culture of learning and experimentation. Dr. Sands emphasized that imposing deliberate constraints and implementing "AI working agreements" significantly accelerated team learning and improved decision-making, ultimately exposing and addressing pre-existing collaboration challenges.

Key takeaway

For Directors of AI/ML evaluating enterprise AI strategies, shift your focus from individual AI tools to team-level integration. You should prioritize establishing shared context via "context graphs" and redesigning end-to-end workflows. This prevents individual speed-ups from creating team friction. Implement "AI working agreements" to standardize AI usage. Foster a culture of experimentation to ensure your teams translate AI activity into measurable ROI.

Key insights

True AI ROI stems from team-level adoption and collaboration, not individual optimization.

Principles

• AI ROI requires team-level focus.
• Shared context drives AI value.
• Redesign end-to-end workflows.

Method

Implement "AI working agreements" at project start to define AI usage, shared agents, and common skills across teams.

In practice

• Build context graphs in collaboration tools.
• Redesign workflows for AI integration.
• Implement AI working agreements for projects.

Topics

• AI Adoption Strategy
• Team Collaboration
• Organizational ROI
• Workflow Redesign
• Context Graphs
• AI Working Agreements

Best for: CTO, Executive, Director of AI/ML, VP of Engineering/Data, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by VentureBeat.