Pre-Conference Workshops: Monday, March 16th, 2026 - ET (Eastern Time, GMT-05:00)
Distinguish between generative AI, machine learning and predictive analytics models and evaluate the unique benefits and challenges of each
Map specific AI technologies to common patient journey pain points, from enrollment to adherence support
Build a framework for assessing AI maturity and readiness within your organization's patient support infrastructure
Master the current FDA guidance and industry standards governing AI applications in patient support programs
Implement ethical frameworks that protect patient data while enabling personalized support experiences
Create governance structures that maintain human oversight while leveraging AI capabilities
Analyze case studies of AI implementations that significantly improved prior authorization success rates and adherence metrics
Evaluate integration approaches that connect AI capabilities with existing hub service platforms and workflows
Recognize warning signs of AI applications that create more problems than they solve
Witness compelling arguments from both AI advocates and critics on key implementation controversies
Develop strategies for addressing resistance to AI adoption while also legitimatizing concerns
Create a balanced perspective that acknowledges both AI's transformative potential and its practical limitations