Data security blocking AI adoption? A PM playbook

Atlassian's State of Product 2026 report highlights that 43% of product managers in large companies face data security concerns, hindering their adoption of AI tools, which raises valid legal and compliance issues but can also lead to shadow AI usage and decreased efficiency. Product managers are caught between the need for data security and efficient workflows, with legal teams ultimately deciding on AI tool safety. To gain approval from legal teams, product managers can use a structured approach: mapping data risks, vetting vendors beyond marketing claims, conducting limited AI pilots, running AI usage audits, and building a data governance roadmap. This approach aims to provide legal teams with concrete evidence of AI tools' safety and effectiveness while mitigating risks like data leaks and shadow AI. By presenting a clear roadmap with defined risks and mitigations, product managers can shift the conversation from broad concerns to specific tradeoffs, thereby facilitating a managed experimentation approach to AI adoption.