As AI tools flood the healthcare and life sciences ecosystem, hub and access leaders are facing a new challenge: not whether to use AI but how to use it responsibly and effectively. Many organizations are experimenting with multiple tools at once without a clear strategy for aligning technology to real patient and operational needs. This lack of clarity is leading to fragmented adoption, internal resistance and missed opportunities for impact.
At the same time, regulatory scrutiny, data privacy concerns and ethical considerations are increasing, making it critical that AI adoption is intentional, governed and transparent. This session responds directly to the growing industry need for a decision-making framework that helps leaders “prescribe” AI in the same way they would a therapy: with purpose, oversight, and measurable outcomes. For attendees, this workshop offers a practical starting point to move from experimentation to confident implementation ensuring AI investments improve access and patient experience without compromising trust or compliance.
This interactive session reframes AI as something that must be prescribed, not blindly implemented. Attendees will break down:
The differences between generative AI, machine learning and predictive analytics, and where each is best suited across the patient journey
How to identify high-impact use cases in areas such as enrolment, adherence, patient communications, and prior authorizations
Methods to assess your organization’s AI readiness and maturity, including infrastructure, data quality and cultural alignment
Governance and compliance considerations to ensure AI is deployed ethically, transparently and safely
How to balance automation with human oversight, ensuring AI enhances, not replaces, patient-facing team
Why this matters:
Rather than promoting AI for AI’s sake, this workshop empowers leaders to make intentional, patient-first technology decisions. You’ll leave with practical tools to evaluate AI opportunities, avoid costly missteps and deploy solutions that deliver measurable value all while protecting the human element at the heart of care.
Decoding the AI Ecosystem – Your Playbook for Patient Support Innovation
Differentiate generative AI, machine learning, and predictive analytics
Apply AI to patient journey pain points, from enrollment to adherence
Assess organizational AI maturity and readiness in patient support
Navigating the Regulatory Maze – Building Compliant AI Patient Solutions
Understand FDA guidance and industry standards for AI in patient support
Implement ethical frameworks to protect patient data and enable personalization
Establish governance structures that ensure human oversight of AI
Unleashing AI's Potential – Strategic Implementation Blueprints
Analyze case studies improving prior authorization and adherence
Evaluate AI integration with existing hub services and workflows
Identify warning signs of problematic AI applications
Challenging Assumptions – The AI Believer vs. Skeptic Showdown
Explore AI implementation debates from advocates and critics
Develop strategies to address adoption resistance and concerns
Build a balanced view of AI’s potential and limitations
