In today's technology landscape, merely using AI is no longer enough. Recent research from Atlassian's Teamwork Lab reveals a critical insight: when it comes to maximising the value of AI in the workplace, mindset trumps adoption rates. The difference between organisations seeing moderate benefits and those experiencing transformative results isn't how frequently they use AI—it's how they approach collaboration with it.
Atlassian's comprehensive survey of nearly 5,000 knowledge workers across Australia, the US, India, Germany, and France identified two distinct approaches to AI integration in the workplace:
The difference in results between these two mindsets is striking. While both groups benefit from AI, the strategic collaborators consistently achieve superior outcomes across multiple dimensions.
The research establishes a clear maturity model for AI engagement, with meaningful differences at each stage:
Stage 1: Basic Task Automation At this entry point, workers use AI for simple, repetitive tasks. They might ask for basic content generation or data organisation but typically treat AI as a replacement for routine work.
Stage 2: Specific Problem-Solving As users become more comfortable, they begin directing AI toward specific challenges. However, interaction remains largely transactional and one-directional.
Stage 3: Interactive Collaboration At this stage, users begin engaging in two-way exchanges with AI. They solicit feedback, refine their approaches based on AI suggestions, and integrate AI more deeply into their workflows.
Stage 4: Strategic Partnership The most advanced collaborators establish a genuine partnership with AI. They leverage AI's capabilities for complex analysis, strategic decision-making, and creative innovation—approaching AI as they would a trusted colleague with specialised expertise.
Anu Bharadwaj, President of Atlassian, exemplifies this advanced approach by collaborating with AI to quickly pull customer data and then actively "sparring" with the system to surface insights that might otherwise remain hidden.
The productivity benefits of advancing through these stages are substantial and quantifiable:
However, the true difference lies not just in how much time is saved, but in how that time is reinvested. Stage 1 users typically redirect their saved time toward additional administrative tasks, whereas Stage 4 collaborators invest in higher-value activities like skill development and innovation.
The research translates these productivity differences into concrete financial outcomes. Enterprise organisations that partner with AI strategically can achieve an estimated annual ROI of £129.4 million, compared to just £65.1 million when AI is used merely for task-specific purposes—representing an opportunity cost of £64.3 million.
This dramatic difference stems from several factors:
Perhaps the most compelling finding is that strategic collaboration doesn't just accelerate work—it fundamentally transforms work quality. While Stage 1 users complete tasks faster, the quality of their output remains largely unchanged. In contrast, Stage 3 and 4 collaborators experience dramatic quality improvements alongside speed gains.
This quality difference emerges from distinct approaches to working with AI:
The result? Strategic AI collaborators are 1.8 times more likely than basic users to be recognised as innovative teammates, driving not just individual performance but team-wide creativity and problem-solving.
The research highlights a defining factor in an organisation's AI maturity: leadership approach. Employees who agree with the statement "Leadership encourages me to experiment with AI" save 55% more time daily than those who don't (84 minutes versus 55 minutes) and are 2.5 times more likely to become strategic AI collaborators.
In environments where leadership views AI with scepticism or anxiety, workers typically:
Conversely, when leaders actively promote AI experimentation:
Annie Dean, Global Head of Team Anywhere at Atlassian, demonstrates this leadership approach by leveraging AI for real-time idea generation: "If you're stuck on an idea and your favourite sparring partner is tied up in a meeting, you can open a conversation with AI to bounce ideas back and forth, get feedback in real time, and treat the exchange like a true conversation. For the first time, technology speaks our language—and that's a huge unlock."
The research reveals significant variation in how different business functions leverage AI collaboration, with some notable missed opportunities:
These differences highlight the value of cross-functional knowledge sharing. While specific AI applications may vary between disciplines, exposure to how other functions leverage AI can spark new experimentation and innovation.
Transforming an organisation from basic AI usage to strategic collaboration requires deliberate cultural change. Practical steps include:
Looking ahead, the research points to several important trends:
The message from Atlassian's research is clear: we need to fundamentally reset how we conceptualise AI in the workplace. Rather than viewing it as merely a productivity tool that automates unwanted tasks, forward-thinking organisations must embrace it as a collaborative teammate that amplifies human capabilities.
The most successful teams won't be those who use AI most frequently, but those who collaborate with it most strategically. By fostering cultures that encourage experimentation, sharing best practices, and continually evolving collaborative approaches, organisations can unlock the full transformative potential of human-AI partnership.
The future of work isn't about humans being replaced by AI or merely directing it as a tool—it's about creating genuine collaborative relationships that combine human creativity, judgement and intuition with AI's analytical power, knowledge base and processing capacity. Those who master this collaborative approach will define the next era of organisational excellence.
Source: https://www.atlassian.com/blog/productivity/ai-collaboration-report
