Atlassian Teamwork Lab has announced the results of a large-scale survey of 12,035 knowledge workers and 172 Fortune 1,000 executives across six countries.
The study reveals that while AI boosts individual work speed, it creates new burdens on team alignment, decision-making, and priority consensus. It suggests that the true competitive advantage in the AI era is not just execution speed, but a team's collaborative strength.
Key Challenges Identified by the Survey
1. **Leaders are falling into AI's speed trap** While 89% of executives reported that AI increased their work speed, only 48% said it improved collaboration. This highlights the reality that while AI dramatically enhances individual productivity, it fails to produce the same effect on overall team collaboration.
2. **Executives are unable to prove ROI** Only 6% of executives are confident they can clearly demonstrate the ROI of their AI investments, and 58% admit they don't even know how to measure it. The main reason is that 67% of corporate AI strategies are focused on the individual or specific domains, with only 24% focusing on team-level application.
3. **The widening AI proficiency gap** 55% of executives reported that AI has widened the performance gap between teams. Although 85% of knowledge workers use AI, only 29% have actually integrated it into their daily workflows, and a mere 15% are able to use AI as a "teammate."
4. **Data debt is causing a crisis of trust** Only 22% of knowledge workers fully trust the accuracy of AI tools. 69% report that their company's data and knowledge infrastructure is not optimized for AI, indicating that data quality issues are a barrier to AI adoption.
5. **The $161 billion annual "Cost of Disconnection"** Duplicated work, misaligned priorities, and collaborative chaos resulting from a lack of strategic AI implementation are estimated to cause $161 billion in annual losses for Fortune 500 companies.
The "Three Pillars" Practiced by Top Teams
The survey found that top teams achieving sustained results with AI practice the following three pillars: - **1. Context:** Share clear goals across teams and build a trusted knowledge base accessible to both humans and AI agents. (Effect: Reduces the incidence of goal misalignment by a factor of 12.) - **2. Workflow:** Clearly define the roles of humans and AI agents and design cross-team workflows. (Effect: Improves AI utilization alignment by 13 times.) - **3. Culture:** Foster an organizational culture that encourages continuous learning and experimentation, promoting collaboration between humans and AI. (Effect: Increases the likelihood of using AI as a teammate by 2.3 times.)
Shifting to a Team-Centric AI Strategy
Based on these findings, Atlassian Teamwork Lab offers the following recommendations for businesses: - **Shift from individual optimization to "team optimization":** The focus of AI strategy should shift from individual productivity to the quality of overall team collaboration. - **Establish a shared context:** A centralized knowledge base and clear goal-setting, accessible to both humans and agents, are prerequisites for effective AI utilization. - **Redesign the entire workflow:** Instead of partially adding AI to existing processes, workflows should be rebuilt on the premise of human-agent collaboration. - **Close the AI proficiency gap:** Without continuous investment in AI training for personnel, the skills gap will only continue to widen.
The contents of this survey will also be presented at the Atlassian Team on Tour event on Tuesday, June 16, 2026.
FACT BOX
- Source: PR TIMES
- Category: Survey
- Organizations: Atlassian
- Products / services: Atlassian Teamwork Lab