Agentforce in Life Sciences: A Framework for Deploying Autonomous AI Agents in Pharmaceutical CRM and Patient Engagement

Author(s)	Maneesh Gupta
Country	United States
Abstract	Artificial intelligence in the pharmaceutical industry is undergoing a significant transition, from assistive tools that support human decision-making to autonomous systems capable of independently executing complex tasks. Historically, AI adoption in life sciences focused on analytics, forecasting, and workflow automation. Recent advances in generative AI and agent-based architectures now introduce the possibility of autonomous digital agents that can reason, act, and operate within enterprise systems with limited human intervention. This evolution reflects broader industry momentum. McKinsey estimates that generative AI could generate between $60 billion and $110 billion annually in economic value for pharmaceutical and medical-product industries, particularly across commercial, medical affairs, and research functions 1.
Keywords	Linear Regression, Forecasting, Prediction, Analytics, Storage, Repository, Nexus, Capacity, Utilization, Modeling, Machine Learning, DevOps, Artifacts, Trend Analysis, Regression, Optimization, Infrastructure, Automation, NXRM.
Field	Engineering
Published In	Volume 7, Issue 6, June 2026
Published On	2026-06-29
DOI	https://doi.org/10.70528/IJLRP.v7.i6.2280

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