AI Adoption Across HealthEdge: An Inside Look at the Marketing Team’s AI Adoption Journey 

I recently had the opportunity to sit down with the HealthEdge Marketing team to understand how they’ve been adopting AI and how that evolution reflects the broader organizational shift toward becoming an AI-first enterprise. Their exploration into what AI solutions could offer the team and the transition from exploration to adoption offers insights into how organizations can successfully integrate AI into their workflows.

Starting Small: A Grassroots Task Force

In mid-2023, a handful of marketing team members formed an informal “Marketing AI Task Force.” There was no directive from leadership—just a shared curiosity and a willingness to explore how AI tools could improve content development, campaign execution, and digital engagement.

Each person focused on researching 3–5 tools aligned to their role, spanning content writing, social media, website optimization, and video creation. Through informal shared documentation, demo sessions, and regular discussions, the team identified tools with the greatest potential impact.

One clear winner early on? Jasper, a generative AI platform for content creation. Team members invested time in fine-tuning the tool on company-specific content, including product information and brand guidelines. It wasn’t just its ability to write that impressed the team—it was how Jasper could adapt to brand voice, generate persona-specific variations, and streamline brainstorming.

Choosing the Right Tools: Practical, Not Perfect

The team prioritized tools that could address real pain points and scale across the organization. Beyond Jasper, they adopted:

• Lumen5 – A video creation platform that makes it easier to turn existing content into short-form videos for social media
• Createopy – A design automation tool that resizes ad creatives for different platforms, saving hours on production
• Qualified – An AI-powered chatbot on HealthEdge’s website, affectionately nicknamed HealthEdge Henry, that improves user experience and lead capture

Each tool chipped away at tedious, time-consuming tasks. The goal was never full automation—but rather augmentation. These tools freed up time for higher-value creative and strategic work.

Peer-to-Peer Learning: The Engine Behind Adoption

What stood out most to me in our conversation was how adoption spread—not through mandates, but through trusted peer networks.

Initial reactions to AI tools varied significantly across the team. Some team members expressed skepticism and uncertainty about how to integrate AI tools into their work. But over time, early adopters became informal “champions,” offering support through team messaging channels, internal demos, and office hours. This peer-to-peer knowledge sharing demonstrated remarkable efficacy in encouraging adoption, even though AI tool usage wasn’t mandated across the team.

By creating space for experimentation without judgment, the team fostered a culture of learning. Colleagues could try new tools at their own pace, see real use cases, and build confidence.

By mid-2025:

• 22 of 25 Jasper license holders were active users
• The team was saving over 60 hours per week
• Even initial skeptics had become regular users

Their enablement model evolved alongside adoption. Feedback loops included end-of-year surveys, quick pulse checks, and quarterly training sessions tailored to user needs.

Why It Worked: Success Factors Behind the Journey

From our discussion, four themes emerged that made the team’s approach effective:

• Encourage curious adopters. The team allowed members to gradually onboard, with enthusiastic adopters paving the way for members who were less certain about how to use AI tools in their work.
• Solve real problems. Tools that saved time or improved quality gained traction quickly.
• Enable continuous learning. Demos, Q&As, peer coaching, and sharing success stories built confidence, trust, and momentum across the team.
• Optimize and configure tools. Features and training evolved based on actual team needs rather than predetermined implementation plans. After initial implementation, team members were surveyed to identify gaps and opportunities. This led to:
  • Regular sessions with vendor representatives
  • Development of multiple brand voices within Jasper
  • Addition of new features based on team requests

This bottom-up strategy mirrors how HealthEdge is driving AI adoption company-wide. In HealthEdge’s broader AI transformation, there’s a clear focus on creating safe experimentation environments, shared infrastructure, and reusable tools that support all teams, not just technologists.

Current State and Future Directions

As of mid-2025, AI tools are fully embedded in the HealthEdge marketing team’s daily operations. What started as grassroots experimentation has become standard practice, contributing to a more agile, creative, and efficient team.

Based on their experience, here are a few key takeaways for organizations considering AI adoption:

• Peer networks are powerful channels for driving knowledge transfer and encouraging adoption
• Voluntary, user-led experimentation often surfaces use cases that go beyond what formal planning would uncover
• Ongoing feedback mechanisms—such as surveys, training sessions, and usage tracking—help ensure tools evolve in response to real user needs
• Grassroots enthusiasm, when nurtured, can lay the groundwork for organization-wide change

For organizations at the beginning of their AI journey, HealthEdge’s experience shows that successful adoption doesn’t require a sweeping initiative. It starts with a few motivated individuals, space to explore, and a culture that rewards learning and sharing.