Moving beyond initial experiments, the long-term success of Artificial Intelligence (AI) in Learning & Development (L&D) rests on a solid, three-pronged strategy: People, Processes, and Systems. Aligning these pillars transforms AI into a business value driver, impacting productivity, retention, and upskilling. Investing in People through training enhances productivity and retention. Optimizing Processes with AI streamlines workflows, boosting productivity and upskilling. Robust Systems integrate AI tools seamlessly for measurable improvements.
Aligning AI initiatives with business drivers
To effectively leverage AI, it's crucial to connect AI initiatives with core business drivers. This ensures that L&D is supporting organizational goals and delivering measurable impact.
Productivity
Business driver
Increasing overall organizational productivity, getting new hires operating faster, or a specific group producing more.
L&D impact
Improving onboarding to accelerate new hire readiness, educating teams on efficient new processes, and enabling faster skill acquisition.
AI use cases
- Automated course creation: Leverage internal documents (policies, procedures) to quickly generate and update onboarding courses.
- Gamification elements: Introduce engaging elements to make learning more enjoyable and improve retention during onboarding.
- AI agents for managers and SMEs: Empower them to create personalized training relevant to specific departments or business leaders.
- Personal learning agents: Allow learners to ask questions about content or topics and receive personalized responses.
- Automated assessment generation: Easily create quizzes to improve knowledge retention without significant effort.
- Agents for query sourcing: Enable learners to quickly find answers to process questions, reducing downtime and increasing control.
Retention & agility
Business driver
Becoming more agile, responding quickly to market changes, and retaining top talent.
L&D impact
Rapidly creating new courses, supporting user-initiated learning, and increasing awareness of available training. Ensuring employees feel supported in their job growth.
AI use cases
- Automated course creation on any topic: Quickly develop courses for new initiatives or changing skill requirements.
- Personal learner agents for uncovered topics: Provide learners with access to information on subjects not yet in the official course catalog.
- Smart course recommendations: Increase awareness and engagement with new and existing courses.
Upskilling/Reskilling
Business driver
Addressing new skill needs, responding to organizational changes, and supporting career growth.
L&D impact
Keeping skills lists current, mapping content to skills, and enabling learners to develop skills even without formal courses.
AI use cases
- AI-generated skills lists: Rapidly create and update skills lists to reflect current needs.
- AI-powered skills mapping: Automate the tedious process of connecting course content to specific skills, even at a granular level within a course.
- AI-generated content suggestions: Review course content and suggest additions to ensure it effectively teaches a particular skill.
- Personalized learning for specific skills: Generate learning content tailored to an individual's skill development needs.
- Interactive skills assessment and coaching: Provide learners with assessments and coaching suggestions to apply learned skills at work.
By strategically implementing AI across these areas, L&D can effectively address business concerns and drive significant learning impact, transforming learning goals into reality through solutions like automated course creation, personalized learning agents, and skills mapping.