Can Nonprofits Build Stronger Teams While Embracing AI?
Source – Atlassian’s 2026 State of Teams Report
Nonprofits have always worked in environments that demand adaptability. Responding to changing community needs and managing limited resources have pushed the sector to consistently find ways to evolve. But the rapid rise of Artificial Intelligence (AI) is introducing a different kind of shift that is changing how work looks like and how teams collaborate, communicate, and make decisions.
According to Atlassian’s 2026 State of Teams Report, AI is improving efficiency across organisations, but it is not necessarily transforming teamwork in impactful ways. In fact, many teams are experiencing fragmented workflows as AI tools are introduced without dwelling on the foundations of collaboration.
Among the 306 nonprofit respondents included in the survey, one trend that stood was that nonprofits are taking a far more human-focused approach to AI implementation compared to other sectors. Instead of rushing towards automation alone, many nonprofit organisations are prioritising people, participation, and workplace culture while exploring AI adoption. This approach reflects the values at the heart of nonprofit work.
However, the report also highlights an important challenge. While nonprofits are centring humans in conversations around AI, many teams still lack clarity on how AI can practically support their work.
The findings suggest that the future of effective AI implementation can lie in learning how to balance people and technology intentionally.
Key Takeaways
Nonprofits are already evolving how work gets done
The report found that 59% of nonprofits are actively changing how they work by experimenting with new tools, workflows, and routines. Teams are beginning to rethink coordination, communication, and task management in response to changing expectations around productivity and impact.
Human-focused implementation remains a defining strength
One of the report’s strongest findings is that nonprofits are approaching AI through a people-first lens. Compared to tech-focused organisations, nonprofit teams are more likely to involve employees in conversations around implementation and change.
This creates important advantages. Teams that took a human-focused approach reported spending less time on miscellaneous work and felt more included in decisions around AI adoption.
In a sector deeply rooted in collaboration and care, this approach aligns naturally with organisational culture and values.
Good intentions alone are not enough
While nonprofits are prioritising people, many organisations are still struggling with practical AI adoption. Teams remain unclear about how AI should fit into their daily work, which tasks it can genuinely support, and how to build confidence in using it effectively.
The report found that human-focused teams had the lowest levels of AI adoption overall. This suggests that without structured guidance, experimentation, and capability-building, AI can remain only a conceptual conversation. .
The strongest teams balance human and technical priorities
The report identifies a clear “sweet spot” for AI implementation. Organisations can combine human-centred thinking with a tech-informed strategy.
Teams that achieved this balance were more likely to:
- Have clear goals and priorities
- Avoid duplicating work across teams
- Reduce too many competing initiatives
- Create time for coordination and collaboration
- Align goals and objectives more effectively
Most importantly, these teams also invested consistently in the broader foundations of modern teamwork.
The future of nonprofit teamwork will depend on how quickly organisations adopt AI, and how thoughtfully they integrate it into their culture and everyday work. The organisations that succeed may be the ones that treat AI as human collaboration and as a tool that strengthens it.
In that balance between people and technology lies a hopeful opportunity for nonprofits to build teams that are more efficient and also more connected, aligned, and resilient.
You can read the full report here.
