Reporting in commercial pharma has always been a team effort. Field Operations, Field Analytics, Commercial Data Management (CDM), and Advanced Analytics each own part of the path from raw data to the number a leader trusts. In recent years,  that path has shifted as AI capabilities  move into the core of leading BI platforms. Natural language query, automated "explain-the-drivers" insights, AI-generated narratives, AI-assisted calculations and report development, and conversational follow-up now sit inside tools commercial teams already use and are becoming  more proactive, surfacing anomalies, and recommending next actions. 

This shift promises  gains such as fewer ad hoc requests, faster answers, and self-service that is more likely to stick. It also introduces new questions that touch every reporting stakeholder. When a business user can ask a dashboard "why did this drop," who owns the accuracy of the answer? Does AI-generated insight improve KPI consistency across teams, brands, and platforms or quietly erode it? Is the semantic layer ready to support natural language querying, or are business rules still scattered across dashboards and offline workarounds? And as work moves closer to the business user, how do the roles of CDM, Analytics, Reporting, and IT need to change? 

Building on the Field Analytics annual reporting landscape—expanded this year into a multi-solution study that includes CDM, and Advanced Analytics—this session will share what the benchmark reveals about how AI-enabled reporting is actually being used. We will cover the platforms and capabilities in use, the maturity of the underlying data and semantic foundations, emerging governance and ownership models  for AI-generated work, and the impact on decision quality, self-service, and analyst workload. We will highlight both where is improving reporting and where it is  creating new consistency, trust, and governance challenges that  reporting teams now need to manage together. 

Join us to see where your organization sits on the AI-in-reporting maturity curve, how your platform choices and governance approach compare to peers, and what leaders are doing to capture the upside of AI while managing the risks.