Although significant focus has been placed on the role of AI in automation and efficiency, it also holds promise in continuous learning and personalization development.
Yet despite this promise, most organizations are still in the early stages of adoption, with only about 30% of companies actively embracing AI practices in their learning and development initiatives.
In a recent episode of our “Welcome to the Machine Podcast,” industrial-organizational psychologists Charles Handler and Mang Lee shared their frontline perspectives on how AI is actually being used in learning & development.
4 Traditional Challenges in Employee Development
Before examining AI’s potential, it’s important to understand the fundamental challenges organizations face with traditional approaches to employee development.
- One-Size-Fits-All Training
Traditional corporate training programs often follow a standardized approach that fails to account for individual learning styles, preferences, and needs. Organizations typically offer rigid curriculum structures that may not align with actual learning requirements.
This standardization makes it particularly challenging to scale specialized training across large organizations, leaving many employees with suboptimal learning experiences.
- Feedback and Growth Limitations
The traditional approach to employee development often relies on infrequent feedback cycles, typically tied to annual performance reviews. This creates significant blind spots in identifying and addressing skill gaps and development needs as they arise.
Rather than proactively guiding employee growth, organizations find themselves reacting to performance issues after they become apparent. Moreover, measuring the effectiveness of learning initiatives remains a persistent challenge.
- Resource Constraints
Organizations face numerous resource limitations in delivering effective employee development. Access to expert mentors and coaches is often limited, particularly in large organizations. Both learners and trainers struggle with time constraints, making it difficult to engage in meaningful development activities. Budget limitations frequently restrict access to specialized training programs, while geographic barriers can prevent employees from accessing valuable development resources.
- Knowledge Transfer Issues
Perhaps one of the most critical challenges is the effective transfer of knowledge within organizations. When experienced employees leave, they often take valuable institutional knowledge with them. Learning experiences can vary significantly across teams, creating inconsistencies in skill development. Organizations struggle to capture and share tacit knowledge effectively, and employees often lack safe environments to practice new skills without risk.
The Promise of AI in Learning & Development
AI technologies offer compelling solutions to many of these traditional challenges, fundamentally changing how organizations approach employee development.
Personalized Learning Journeys
AI as a Personal Coach
Modern AI systems can serve as always-available personal learning coaches, providing continuous feedback and guidance tailored to each employee’s needs. These systems can create adaptive learning paths that evolve based on individual progress and performance. Through real-time performance insights, AI can identify skill gaps as they emerge and suggest targeted interventions.
Simulation-Based Learning
One of the most promising applications of AI is in creating realistic learning simulations. These environments provide safe spaces for employees to practice new skills and receive immediate feedback. AI-powered simulations can be customized to specific job requirements, allowing employees to gain practical experience without real-world risks.
Bridging Assessment and Development
Seamless Integration
AI enables organizations to create seamless connections between initial assessment and ongoing development. Instead of storing valuable insights from the hiring process in file cabinets, AI systems can use this information to inform personalized development plans. This creates a continuous tracking system that monitors progress and adjusts learning interventions accordingly.
Data-Driven Growth
By leveraging AI’s analytical capabilities, organizations can move beyond intuition-based development to data-driven growth strategies. Real-time performance analytics provide objective measures of progress, while predictive analytics can anticipate future development needs. This enables truly personalized intervention points that maximize learning effectiveness.
2 Examples of Leading Companies Transforming Employee Development with AI
ServiceNow’s Personalized Learning Platform (frED)
ServiceNow exemplifies the potential of AI-driven learning through their internal platform frED, named after founder Fred Luddy. Built on their Now Platform, frED demonstrates how AI can transform corporate learning at scale.
Platform Features
The platform leverages AI to deliver personalized learning journeys where employees can map career paths, identify skill gaps, and receive tailored program recommendations. Its intelligent content recommendation system makes it easier for employees to discover relevant learning materials.
The implementation has successfully streamlined learning tools and resources, with over 65% of employees engaging with the platform within its first month of launch.
Johnson & Johnson’s Skills Inference Approach
Johnson & Johnson pioneered an innovative approach to AI-enabled development through their skills inference system, offering valuable insights into large-scale implementation of AI in learning and development.
Strategic Implementation
J&J’s approach began with developing a comprehensive taxonomy of 41 “future-ready” skills grouped into 11 capabilities. Their system collects data from multiple sources, including HR systems, recruiting databases, and learning management platforms. A sophisticated machine learning model evaluates employee proficiency across these skills, using a scale from 0 to 5.
Measurable Results
The implementation has yielded impressive results, including a 20% increase in engagement with professional development resources. The system provides leadership with valuable insights for strategic workforce planning, enabling data-driven decisions about hiring, retention, and talent movement.
Future Vision
AI represents a transformative opportunity in employee learning and development, offering solutions to long-standing challenges while enabling new possibilities for personalized, continuous learning.
As demonstrated by companies like ServiceNow and Johnson & Johnson, successful implementation can drive significant improvements in employee engagement and development effectiveness.
The key to success lies not in viewing AI as a replacement for traditional learning methods, but as an enabler of more effective, personalized, and scalable development approaches. Organizations that thoughtfully integrate AI into their learning strategies while maintaining the crucial human element will be best positioned to develop the workforce capabilities needed for future success