AI adoption is widespread, but its impact varies across businesses, with observability emerging as a key factor in maximizing AI value and mitigating risks. The Dynatrace State of Observability 2025 report highlights a shift from AI experimentation to integration into core operations, noting that observability has transitioned from a reactive IT tool to a central control plane for AI transformation. Executives now prioritize AI observability to reduce risks, lower costs, and align AI initiatives with business objectives, leading to increased budgets for observability platforms, which are now chosen primarily for their AI capabilities. Despite the universal adoption of AI, a trust gap persists, with organizations investing in trust and transparency initiatives to ensure reliability. Observability expands across security, sustainability, and DevSecOps, with AI-powered threat detection and sustainability monitoring becoming crucial for budget allocation. The report identifies a "KPI gap," where only a minority of organizations link observability data to business outcomes, presenting an opportunity for leaders to enhance business agility and financial efficiency by integrating AI-driven insights with technical and business metrics. Observability is now seen as essential for explaining, securing, and auditing AI systems, providing the intelligence necessary for successful AI transformations.