Reimagining data platforms in the agentic AI era

Agentic AI goes beyond traditional AI models by acting autonomously. Unlike rule-based or predictive models that require human intervention, agentic AI systems can interpret data, make decisions, and take action while learning from feedback. In pharma, this means agents can manage workflows like personalized HCP outreach, real-time market analysis, and medical content creation—dramatically reducing latency and manual oversight.

Most pharma data ecosystems were designed for human interpretation, focusing on dashboards and reports. Agentic AI, however, requires machine-readable semantics, real-time processing, and autonomous reasoning capabilities. Without upgrading to semantic knowledge layers, standardized data formats, and streaming architectures, organizations cannot safely deploy agents at scale.

The paper identifies six major challenges:

• Lack of semantic context and knowledge graphs
• Inconsistent data quality and standards
• Latency in data availability and limited use of unstructured data
• Governance and auditability gaps in regulated environments
• Cultural resistance and fear of automation
• Siloed organizational structures and fragmented data ownership

The white paper outlines a phased roadmap:

• Immediate (6–12 months): Identify 2–3 agent-ready use cases, launch governance councils, and establish initial semantic layers.
• Mid-term (2 years): Expand real-time processing, integrate unstructured data, and align with industry standards.
• Long-term (3–5 years): Deploy orchestration frameworks and fully autonomous agent systems across commercial functions.

Clear KPIs are essential to ensure trust and ROI. Recommended metrics include:

• Data Quality: Error reduction, accuracy of third-party data, anomaly detection time.
• Business Impact: Campaign ROI, HCP engagement, sales productivity.
• Governance: % of actions with audit trails, number of overrides, compliance scores.
• Platform Maturity: Real-time data volume, semantic coverage, interoperability rates.