Atlassian’s Avani Prabhakar cautions that imposing AI mandates tied to performance goals can backfire, while emphasizing the powerful influence of AI super users who drive significant gains in team AI usage and effectiveness.
- One AI super user boosts team AI adoption by 56%
- Mandated AI usage linked to performance risks gaming behaviors
- Atlassian uses AI working agreements and AI wallets to manage usage and costs
What happened
Avani Prabhakar, Atlassian’s chief people and AI enablement officer, shared new data and strategies about AI adoption at the company during a conversation at HumanX in Amsterdam. She described the concept of AI super users—team members who use advanced AI features more than 40 times weekly—and revealed that just one super user in a team of five to seven members increases overall team AI adoption by 56%.
Atlassian has introduced AI working agreements to clarify where and how employees can use AI tools in their workflows, while each employee receives an AI wallet that allocates a budget for their AI usage according to role. The company also employs an internal knowledge graph to improve AI accuracy and cut token consumption. Prabhakar warned against enforcing AI mandates tied directly to performance goals, emphasizing that it can lead to undesirable behavior.
Why it matters
Prabhakar’s insights underscore a critical element of AI integration in the workplace: people transformation. The success of AI adoption depends less on technology rollout and more on managing people’s interaction with AI and embedding it into workflows thoughtfully. Atlassian’s approach of balancing governance, budget management, and behavioral insights provides a model for other large enterprises navigating AI implementation.
Additionally, her caution about AI mandates highlights the risk of focusing on superficial metrics rather than meaningful usage, which can undermine AI’s benefits. The company’s investment in behavioral science and partnerships with academic institutions also point to AI adoption as a nuanced challenge that blends technology, psychology, and organizational culture.
What to watch next
Atlassian’s ‘customer zero’ strategy involves piloting AI experiments internally, documenting best practices, and scaling those learnings to external companies. Observers should monitor how Atlassian’s practices influence broader enterprise adoption and whether other firms adopt similar AI wallet budgeting systems or AI usage agreements.
Further research and experimentation around AI’s impact on roles, skills, and workflows remain important. Prabhakar noted no roles have been replaced yet by AI but acknowledged the emergence of new hybrid roles like design technologists. Tracking the evolution of these dynamics, alongside ongoing development of Atlassian’s AI governance framework, will be key to understanding AI’s long-term workplace effects.