AI Labs

The AI Lab is Track 2 of Phase 2: Adoption—the operational, hands-on counterpart to Track 1: the AI Council. While the council handles strategic and governance check-ins, the AI Lab is where Ambassadors identify use cases, learn, and build.

The AI Lab is not only a learning environment. It is also the arena where you identify potential use cases and processes where AI can be used successfully. Sometimes the Ambassador can solve the use case themselves. Sometimes it requires hands-on building and development, where Intric’s Adoption Specialists and engineers help tailor the assistant or agent to the specific need.

AI Labs are recurring workshops where your organization’s AI journey truly takes flight. These sessions create a safe, collaborative environment where AI Ambassadors and creators come together to experiment, learn, and build valuable AI assistants.

Overview

An AI Lab is a regular physical or digital meeting space for learning and for finding where AI can work in your operations. During these sessions, participants explore advanced concepts from the SAMR model—specifically Modification and Redefinition—by demonstrating what they’ve built, solving challenges together, identifying new use cases, and redesigning workflows with AI.

Think of it as your organization’s innovation sandbox: a high-trust environment where experimentation is encouraged, failure is a learning opportunity, and collective knowledge drives individual growth.

What Happens in an AI Lab?

AI Lab sessions typically include:

• Demo Time: Participants showcase assistants they’ve built, explaining their use cases and demonstrating functionality
• Identify use cases: Find processes where AI can be used successfully
• Collaborative Problem-Solving: Team members work together to overcome technical challenges or refine assistant designs—or bring in Intric’s Adoption Specialists and engineers when a case needs tailored development
• Knowledge Sharing: Learning from each other’s successes and setbacks
• Hands-On Building: Creating and testing new assistants as a group, including cases Ambassadors can take forward themselves
• Workflow Redesign: Exploring how AI can transform tasks, not just automate them

Key Benefits

Promotes Trying & Learning

The AI Lab acts as a high-trust “sandbox” where you can experiment without fear of making mistakes. This hands-on environment is crucial for moving past technical anxiety and building genuine competence with AI tools.

Facilitated Growth

Rather than leaving learning to chance, AI Labs provide structured opportunities for growth. The group’s collective knowledge lifts individual capabilities, making the journey up the AI Staircase feel achievable and supported.

Collaborative Prototyping

Instead of working in isolation, creators build together. This transparency makes “ease of use” visible to everyone and accelerates learning across the organization.

Cross-Functional Knowledge Sharing

When HR demonstrates a policy-searching assistant, Finance can apply those same principles to build a procurement assistant. This cross-pollination reinforces the value of AI across different domains and use cases.

Getting Started

Frequency

We recommend bi-weekly or monthly sessions to maintain momentum without overwhelming participants. Consistency is more important than duration—regular touchpoints keep the innovation flowing.

Structure

While each organization’s AI Lab will evolve to fit their needs, a typical session might include:

1. Check-in (5–10 min): Quick round of updates and wins
2. Demonstrations (20–30 min): Showcasing new or updated assistants
3. Collaborative Work (30–45 min): Building, troubleshooting, or planning together
4. Knowledge Sharing (10–15 min): Lessons learned and best practices
5. Next Steps (5 min): Planning for the next session

Tips for Success

• Create Psychological Safety: Emphasize that all questions are valid and mistakes are learning opportunities
• Share Both Wins and Failures: Learning what doesn’t work is just as valuable as celebrating successes
• Keep It Practical: Focus on solving real problems, not theoretical exercises
• Document and Share: Capture insights so knowledge isn’t lost between sessions
• Celebrate Progress: Acknowledge achievements, no matter how small

Next Steps

Ready to establish your own AI Lab? Here are your next actions:

1. Identify potential facilitators (usually from your admin team)
2. Schedule your first session and invite AI Ambassadors
3. Choose a format that works for your organization
4. Start with simple demonstrations and build from there
5. Establish a regular cadence that fits your team’s schedule