Integrating AI in Course Development: Three Practical Tips for L&D Teams
Artificial intelligence (AI) has become a fixture of conversations about teaching and learning. Recent research shows that 74% of organizations struggle to scale AI practices, and 52% of workers worry about AI. Trust remains a barrier to adoption – a phenomenon often called ‘algorithm aversion’. Rather than resisting, learning and development (L&D) teams, instructional designers, and curriculum developers can approach AI pragmatically.
Here are three practical tips for integrating AI into your course development work.
1. Map Your Processes and Clarify the “Why”
Before deploying AI tools, identify the areas where AI could add value. Ask: What problems are you trying to solve? How do they connect to learner needs or organizational goals? For example, you might want to:
- Speed up course build timelines to keep pace with industry changes.
- Free instructors’ time for 1:1 learner interaction.
- Create richer multimedia to boost learner engagement.
By clarifying *why* AI is being introduced, you reduce the risk of “bolt‑on” solutions and ensure alignment between tools and outcomes.
2. Apply the Right Level of AI: Automation, Augmentation, or Human-Led
AI doesn’t need to replace whole processes; it can support them at the right level. A useful framework is:
- Automation (all AI): low‑risk, repetitive work (e.g., migrating courses, bulk copy editing).
- Augmentation (human + AI): collaborative drafting and idea generation (e.g., course outlines, assessment plans, content curation).
- Traditional (all human): high‑stakes, culturally sensitive, or ethically complex work.
This tiered approach lets you match tasks to the appropriate balance of efficiency, trust, and quality.
3. Start Small, Measure Impact, and Co‑Design with Teams
Big AI projects can overwhelm staff. Instead, pilot AI in one or two high‑impact areas. For example:
- Use AI to scan peer institutions’ curricula to identify overlaps and gaps.
- Automate research tasks, then have humans review and refine outputs.
- Test AI‑generated course prototypes to gather faster stakeholder feedback.
Starting small not only reduces resistance but also builds trust by showing measurable benefits. Co‑designing processes with faculty or SMEs ensures they feel in control of the change.
Final Thought
AI is not a magic solution, but it can be a powerful collaborator. When used thoughtfully, it accelerates routine work, supports creativity, and personalizes learning experiences. The key is to clarify your goals, choose the right level of AI integration, and start small with your teams.
Explore these great resources to fuel your journey into AI for teaching and learning:
- White Paper | From Automation to Transformation: AI Strategies for Personalized, Engaging and Inclusive Online Course Design | Quality Matters
- AI Course Compass: A Seven-Phase Framework for Ethical, Equitable, and Adaptive Course Design | Online Learning Consortium
- WorkLab: Hard Data, Compelling Stories, Vital Insights | Microsoft
Want to Learn More?Connect with your institute's D2L Customer Success Manager or Client Sales Executive, or reach out to the D2L Sales Team for more information about how Learning Services can support you on your learning journey.