Driving AI Transformation Through Strategic Learning: HealthEdge’s Multi-Channel Approach 

At HealthEdge, we know that deploying AI tools is just one piece of the puzzle. True transformation happens when people across the organization not only understand what AI can do but also begin to apply it in ways that elevate their day-to-day work. That belief has guided our approach to learning and development as we scale AI adoption.

Our teams span a wide range of roles from claims analysts and care managers to product leads and engineers. That diversity requires a learning strategy that can meet people where they are, whether they’re just beginning their AI journey or already building solutions. To help make that happen, we’ve built a multi-channel learning ecosystem that combines centralized resources, live expert-led sessions, self-paced development, community interaction, and continuous feedback.

Multi-Channel Learning Modalities

The AI Hub: Centralizing Knowledge Resources: We established a centralized AI Hub on the HealthEdge intranet platform, serving as the single source of truth for AI learning resources. This hub houses curated content, including top AI podcasts, recommended books, instructional videos, and manager-specific resources. The platform also features structured AI learning paths and houses recordings from various AI sessions, ensuring that learning resources remain accessible beyond live events.

The centralization strategy addressed a critical challenge identified in employee feedback: the proliferation of scattered resources across different platforms. By consolidating everything in the AI Hub, we eliminated the friction that often prevents employees from engaging with learning content.

AI Power Hours: Sharing The Learning: The monthly AI Power Hour sessions became a cornerstone of the HealthEdge learning strategy, featuring both internal experts and external speakers. These hour-long sessions cover topics ranging from fundamental AI concepts to specific tool demonstrations, with notable speakers including company leaders and external technology partners.

The program has demonstrated strong engagement across the organization. So far in 2025, 36% of people managers and 30% of all employees have attended at least one AI-specific Power Hour session. Attendance peaked at 380 participants in January 2025 for “AI Innovation in Action,” a session on practical AI applications led by CTO Rob Duffy, indicating high organizational interest.

Recognizing diverse learning needs, we plan to implement a dual-track approach: technical sessions focused on specific tools and implementation for engineering teams, and enterprise-wide sessions covering topics like prompt engineering that apply across all roles.

LinkedIn Learning: Self-Paced Professional Development

We leveraged our existing LinkedIn Learning platform investment to provide comprehensive, self-paced AI education. This modality has been growing in popularity: by mid-2025, we had already approached 2024’s full-year AI learning consumption levels. Employees are not just consuming content broadly through individual courses (903 started in 2025) but also focusing on deeper programs through structured learning paths (122 started in 2025).

Business unit analysis shows particularly strong engagement from technical teams, with our Tech organization leading in both learning path and individual course consumption. However, significant adoption across the HealthRules® Payer (58 learning paths started) and Global Professional Services (15 learning paths started) business units demonstrates that AI learning extends well beyond traditional technology roles.

Community Engagement: More Ways To Get Involved

We expanded our learning ecosystem with several supporting initiatives. The “AI @ HealthEdge” Teams channel provides a platform for peer-to-peer learning, questions, and sharing of AI innovations. Monthly “Ask Me Anything” sessions with leadership create opportunities for real-time problem-solving and guidance.

The global nature of our workforce is reflected in specialized programming, including monthly AI Talk sessions hosted by our team in India, ensuring that learning resources serve all geographic regions and time zones.

Pulse Surveys: Measuring Transformation Progress

To measure success, HealthEdge implements quarterly pulse surveys tracking AI transformation progress across six key dimensions. These surveys provide crucial feedback on the effectiveness of learning initiatives and identify areas requiring additional focus.

Our comprehensive learning approach has yielded significant measurable improvements across all tracked dimensions. Between Fall 2024 and Summer 2025, we saw improvements in every survey category:

• AI familiarity and role application: Increased from 71% to 81%
• Adequate information/training: Rose from 59% to 66%
• Easy access to AI resources: Improved from 61% to 68%
• Leadership support: Strengthened from 82% to 88%
• Empowerment to recommend AI solutions: Grew from 66% to 76%
• Belief in AI’s positive company impact: Increased from 76% to 81%

While these improvements are encouraging, we recognize that scores in the low-to-mid 60s for training adequacy and resource access indicate continued opportunity for enhancement. The partnership between these two teams specifically targets these areas through more hands-on enablement and practical application training.

Looking Forward: Sustainable AI Transformation

Our multi-channel learning approach demonstrates that successful AI transformation requires more than technology implementation. It demands thoughtful change management that meets diverse learning needs while maintaining focus on practical application.

The learning ecosystem has successfully shifted organizational sentiment from AI apprehension to enthusiasm. As Wendi Ellis, our VP of Talent and Learning, noted in team discussions, the focus has evolved from making employees “not afraid” of AI to driving actual adoption and practical application.

By combining centralized resources, live community learning, self-paced professional development, and continuous feedback loops, we’re building the foundation for sustainable AI adoption that drives real business value.

Why This Matters

For AI to be truly transformational, it must be accessible. That means investing in both learning and tools. Our approach is built around the understanding that no single learning method fits all. A product owner needs something different than a care manager, and a developer learns differently from a sales lead. Multi-channel learning lets us respect those differences while unifying our organization around a common goal: using AI to drive smarter decisions and better outcomes. We’re encouraged by the momentum and even more excited about where this can go.