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AI GOVERNANCE FRAMEWORK FOR HEALTHCARE CONTACT CENTER
Implementing AI Risk Assessment Framework at Healthcare Organization
Context
Served as an Individual Contributor in the Knowledge Management team at Tessera Group Health, a healthcare organization. Led AI governance assessment for Amazon Connect Contact Lens implementation across customer service operations supporting 1300+ representatives (2025).
Challenge
Tessera Group Health was implementing Amazon Connect Contact Lens to analyze customer service calls using AI. The organization had no existing AI governance framework, and leadership was pushing for rapid deployment without considering HIPAA compliance risks, change management issues, and data security concerns.
Initial implementation plans included:
Real-time AI transcription of calls containing Protected Health Information (PHI)
Sentiment analysis of member conversations about medical conditions
No documented data handling procedures for AI-processed healthcare information
Unclear data retention and access controls for AI-generated insights
Restrictive editing capabilities for AI-generated interaction documentation
Without intervention, the organization risked HIPAA violations, regulatory penalties, potential exposure of member health information through inadequately secured AI systems, and potentially erroneous PHI in their permanent record.
Approach
I developed a comprehensive AI governance and risk assessment framework specifically for healthcare AI implementation:
Conducted stakeholder analysis across Information Technology, Quality Assurance, Customer Service Operations, and Leadership to understand implementation plans and identify knowledge gaps about AI-specific risks in healthcare contexts.
Built risk assessment framework documenting:
Data flow mapping (where PHI enters AI systems, how it's processed, where it's stored)
HIPAA compliance requirements for AI transcription and analysis
Access control requirements for AI-generated insights
Data retention and deletion policies for AI-processed information
Created governance documentation including:
AI system usage policies for customer service representatives, including correction of AI-Generated information
Quality assurance procedures for AI transcription accuracy in medical contexts
Incident response procedures for AI-related data exposure
Training requirements for staff using AI tools with PHI
Identified critical implementation gaps and escalated to leadership with specific risk documentation, technical requirements, and recommended security controls before deployment.
Results
Prevented premature deployment by documenting specific HIPAA compliance gaps requiring resolution before launch
Established reusable AI governance framework applicable to future AI implementations across organization
Created documentation standards for AI system evaluation in healthcare contexts
Built cross-functional awareness of AI-specific compliance requirements among IT, operations, and leadership teams
Positioned organization to implement AI tools responsibly with proper security controls and compliance measures
Framework is now being used as template for evaluating additional AI tools and serves as organizational standard for healthcare AI governance.
Skills Demonstrated
AI governance and risk assessment
HIPAA compliance in AI systems
Healthcare data security requirements
Stakeholder management and escalation
Cross-functional collaboration (IT, compliance, operations, leadership)
Amazon Connect and Contact Lens evaluation
Technical documentation for regulated industries
Strategic risk identification and communication
Downloads
This is example documentation, demonstrating documentation structure and risk assessment methodology. These are not final products and do not contain any confidential organizational information.