Purpose of the Workshop
This Healthcare AI Workshop is designed to help organizations move from general interest in AI to clearly defined, client-specific AI use cases.
The focus is on:
- Cut denials and rewoUnderstanding the client’s current landscaperk with predictive claim validation
- Identifying operational pain points
- Exploring realistic AI opportunities
- Prioritizing use cases that align with impact, feasibility, and ROI
The outcome is not theory, but a tangible set of prioritized AI use cases and next steps.
Pre-Workshop Preparation & Data Gathering
Before the workshop begins, preparation is done to ensure discussions are relevant and grounded. This phase includes:
- Client Needs Assessment: Discovery sessions are conducted to understand the client’s challenges, goals, existing infrastructure, data availability, and pain points. Input is gathered from multiple stakeholders to capture different perspectives.
- Data Readiness Assessment: The client’s data landscape is evaluated to understand whether data is available, relevant, and usable for AI applications. This includes reviewing sources such as patient records or operational data, while keeping data privacy, security, and HIPAA requirements in focus.
- Targeted AI Research: Initial research is carried out on AI applications relevant to the client’s context. This helps frame discussions and supports informed brainstorming during the workshop.
- Stakeholder Identification: Key participants from different departments and levels of the organization are identified to ensure balanced input and a holistic understanding of needs.
Workshop Structure & Activities
Session 1: Understanding the Client’s Landscape
The workshop begins by establishing shared context.
This session includes:
- Clear introduction of workshop objectives
- Client overview covering mission, initiatives, challenges, and aspirations
- Interactive discussions where participants share perspectives on AI and its role within the organization
roup activities focus on identifying pain points, inefficiencies, and areas where AI could add value. Simple prioritization techniques are used to highlight problems based on impact and feasibility. Data and workflow mapping helps visualize existing processes and integration points.
Session 2: Exploring AI Possibilities
Once challenges are clearly defined, the workshop shifts to exploring AI opportunities.
This session includes:
- Examples and case studies of AI applications in similar healthcare settings
- Group brainstorming to generate AI use cases tied to identified pain points
- Guided discussion on how AI could:
- Improve efficiency and reduce administrative burden
- Enhance clinical decision-making and diagnostic accuracy
- Support patient engagement and personalization
- Optimize operational workflows and resource use
Relevant AI technologies are introduced to explain capabilities and limitations, helping ideas stay realistic.
Post-Workshop Deliverables
After the workshop, clients receive clear, usable outputs:
- A comprehensive report summarizing identified pain points, prioritized AI use cases, and key discussions
- An actionable roadmap for developing and implementing selected AI solutions
- Supporting documentation, including relevant case studies, insights, and best practices
hese deliverables ensure the workshop results in direction and momentum, not just discussion.
Outcome
By following this structured approach, the Healthcare AI Workshop helps organizations:
- Clearly understand where AI fits within their operations
- Identify AI use cases grounded in real needs and data
- Prioritize initiatives with measurable value
- Leave with a roadmap that supports practical execution
Explore AI Opportunities That Make Sense for Your Organization
If your team wants to identify meaningful AI use cases and move forward with clarity, this workshop provides a structured starting point.