AI best practices for companies and leaders
10 min
By the end of this lesson, you’ll be able to:
- Identify how leadership influences company-wide AI adoption
- Apply company-wide and leadership best practices to enable effective AI use
Drive company-wide AI habits through effective leadership
To build effective AI practices, companies need both strong leadership and consistent company-wide habits. Leaders play a key role in AI adoption by setting clear direction and modeling best practices. At the same time, all team members are responsible for integrating effective AI practices into their daily work. When leadership and individual actions align, companies create a strong foundation for responsible and meaningful AI use.
Company-wide best practices for AI
Company-wide best practices are the shared habits and routines that enable everyone in a company to use AI effectively and responsibly. These practices go beyond individual or team actions—they set the foundation for how information is organized, how context is brought into daily work, and how innovation is accelerated across the company. This collective approach helps break down silos, fosters collaboration, and drives continuous improvement at scale.
👉 For example: Before asking about product knowledge from a colleague, Atlassians commonly use Rovo to search for existing documentation on the subject. This company-wide habit often saves time with less back-and-forth discussion and encourages every Atlassian to keep their own documentation up to date so it can be referenced across all teams and departments.
👇 Explore AI best practices below
1. Make knowledge accessible to AI: Break down silos by ensuring key information is explicit, well-organized, and available to AI apps.
2. Bring context into every workflow: Work with AI agents to turn isolated data into useful insights at every step.
3. Leverage AI to speed up research: AI can synthesize and analyze large datasets, making research faster and more accessible.
Leadership best practices for AI
Leadership best practices are the actions, mindsets, and strategies that drive company-wide standards forward, ensuring every team and individual can succeed. Executives and leaders break down barriers to AI adoption when they foster environments of safety and curiosity.
👉 For example: AI initiatives are explicitly aligned with Atlassian’s core values, such as collaboration and continuous learning. Leadership organizes events like ShipIt Days, Atlassian’s hackathons, where teams experiment with new ideas—including AI—to drive innovation and creative problem-solving. These events foster a culture of open collaboration and continuous improvement.
👇Explore leadership best practices
1. Build trust through transparency: Uncertainty slows experimentation. Transparent tools, clear policies, and open communication help teams learn and experiment with AI safely.
2. Lead by example in experimentation: Champion a culture of experimentation and curiosity.
3. Facilitate community learning: Create opportunities for teams to learn from each other’s AI experiences.
4. Champion building and testing AI teammates: Empower teams to design, build, and improve AI agents that support their workflows.
5. Position AI agents as essential collaborators: Integrate smart tools into daily work as creative and technical partners.