Most companies today use artificial intelligence (AI), but only a small proportion of them are actually seeing major changes. According to an Atlassian survey of 180 Fortune 1000 executives and 12,000 knowledge workers, 96% of organizations have not seen dramatic improvements in efficiency, innovation, or quality of work. By contrast, the remaining 4% are achieving transformative results. These companies do not focus solely on personal productivity, where people report an average improvement of 33% and savings of 1.3 hours per day, but go further. They focus on coordination across the entire company, making them nearly twice as likely to see significant efficiency improvements. Meanwhile, companies that focus only on personal productivity are 16% less likely to achieve organization-wide innovation. And this could cost the Fortune 500 $98 billion annually.
Making Everything Accessible to AI
These successful companies work to create a connected knowledge base for the entire organization. Instead of allowing knowledge to remain in isolated conversations or departments, they make everything accessible to AI. For example, 79% of knowledge workers would use AI more often if it had access to the right data. That is why these companies support brainstorming on digital whiteboards, collaboration on shared pages, and the involvement of AI in meetings to take notes automatically. At Atlassian, for example, projects begin with a clear brief explaining the challenge and the expected impact, which helps AI navigate the work more effectively. They also use tools such as Rovo, which scans goals, projects, and tasks to suggest where to start the day. Another practice is inviting Loom AI to meetings, where it automatically creates notes in Confluence and assigns tasks in Jira. All of this ensures that AI has accurate context, including owners, tags, and statuses such as "draft" or "verified".
Setting Up Systems for AI-Powered Coordination
Another key is setting up the right systems to enable AI-powered coordination. These companies document 3 to 5 goals per team, define success, and link them to departmental and company-wide goals, with quarterly reviews. At Atlassian, for example, all OKRs (objectives and key results) are stored in the Goals app, where they are aligned and linked all the way up to one overarching company goal. This allows AI to quickly identify duplicate work or connect people. They use integrated systems in which AI connects data from different platforms, such as social media and product teams, to suggest adjustments to plans. In addition, they introduce clear AI policies, with guidelines embedded directly in tools such as an AI playground, and support open channels for questions so that people can experiment without fear.
Integrating AI as a Team Member
Finally, these companies make AI part of the team, not just a tool. Half of managers and teams work with it all day, but successful organizations give all teams the freedom to experiment, making them twice as likely to innovate as slow adopters. Instead of formal training, they prioritize hands-on workshops, hackathons, and sharing in channels where managers demonstrate how they use AI. At Atlassian, for example, new hires receive NORA (Newlassian Onboarding Rovo Agent), which answers questions about the company and its goals. At the start of projects, they define AI's role, such as analyzing feedback or drafting a plan, and review it regularly. People who see managers model AI use are four times more likely to experiment and three times more likely to become strategic collaborators with AI.
