AI and automation are hot topics in learning, but clients often ask: “What’s actually working today, and where should we start?”
Let’s separate reality from hype and explore some practical steps.
✅ What’s Real: Practical AI in Docebo Today
AI in learning isn’t just theory. Many organizations are already seeing impact. Here are the most impactful ways customers are already using Docebo’s AI features:
- AI Content Creation: Generate lessons, revise text, create assessments, and even produce lifelike presenters with Docebo Creator. This dramatically reduces content build time.
- Auto-Tagging and Skills: Let AI scan videos and documents to add relevant tags and skills, making content easier to find.
- Personalized Recommendations: Help learners discover what’s most relevant to them based on their interests and skill gaps.
- Conversational and Neural Search (Harmony search): Ask questions in natural language and surface both structured and unstructured knowledge instantly.
- AI Coaching and Scenarios: Build immersive practice simulations with real-time feedback to boost skills in context. Learn more about AI Virtual Coach here.
Remember, our Best Practice Kits in Docebo University offer detailed guidance to help you get the most out of these tools
🚩 What’s Hype: Common Misconceptions
With all the buzz around AI, it’s easy to get caught up in myths. These are the misconceptions we hear most often, and the realities behind them:
Myth: AI will replace L&D roles
- Reality: AI takes on repetitive tasks (like tagging, enrollment, workflow management), freeing L&D pros to focus on strategy, design, and mentoring. Deep dive: Agentic AI in L&D
Myth: AI in L&D is a black box
- Reality: Transparency and oversight are key. In Docebo, admins can review, adjust, and audit AI-generated tags, recommendations, and content. The AI Settings dashboard and Audit Trail give visibility so AI acts as a partner, not an unchecked authority.
Myth: AI implementation is a one-time project
- Reality: Success requires iteration. Quarterly reviews, skill framework updates, and data checks keep AI aligned with changing business needs.
🛠 How to Get Started
Successful AI adoption doesn’t happen overnight. Teams that see the most value approach it step by step. Here’s how to set yourself up for success.
- Start Small: Pilot one AI use case (like Creator for onboarding) to validate outcomes, collect feedback, and show early wins.
- Check Infrastructure: Run a readiness review: clean up legacy content, validate HRIS/CRM syncs, and confirm your data is accurate before scaling.
- Engage Stakeholders Early: Involve leaders, SMEs, and even learners to build trust and alignment. Co-created pilots often see stronger adoption.
- Leverage Built-In Tools: Maximize what’s already available in Docebo (Creator, auto-tagging, recommendations, Discover Coach & Share) before customizing.
- Measure and Iterate: Use Insights dashboards and quarterly reviews to monitor adoption, track outcomes, and refine AI use cases.
📚Further Reading & Resources
AI adoption works best when treated as a phased journey. Start with pilots, ensure your data is solid, involve stakeholders, and use built-in tools before scaling. Continuous measurement and iteration turn early wins into lasting value.
Want to explore more? The resources below dive deeper into change management, data quality, and long-term AI success in learning.
- AWS Prescriptive Guidance: Enterprise adoption of AI requires phased rollouts, data governance, and continuous monitoring - not instant transformation. AWS Best Practices for Enterprise Generative AI
- TechRadar: “AI and machine learning projects will fail without good data.” Strong reminder that data quality and oversight matter - AI isn’t “set it and forget it.” TechRadar on AI & Data
- SmartDev: AI in L&D reduces admin tasks but requires analytics and feedback loops to refine learning programs. SmartDev — AI Use Cases in L&D
- Knolskape: Adaptive learning with AI can personalize at scale but still needs tailoring to org culture and ongoing adjustment. Knolskape - Integrating AI in L&D
💬 Your turn: Which AI use case are you testing in Docebo right now? Share your lessons in the comments so we can learn together. 👇