Many companies invest heavily in employee training, yet results often fall short. Mentor126.ai, an enterprise upskilling platform powered by agentic AI, argues that the issue isn’t the quantity of learning materials available but how well they meet individual needs. “The challenge is not about content,” says co-founder and CEO Ted Theocheung. “It’s about ensuring learning reaches each person effectively.” The company focuses on tailored, evidence-based experiences that evolve with the learner’s goals and progress.
Training Gaps and the Limits of Standard Models
The report shows the average employee spends about 10.5 hours annually on training. Yet 43% say it feels disconnected from their role. This suggests that while access to content matters, relevance and application shape retention. Traditional models, Theocheung explains, often prioritize completion metrics over real learning. “Employees consume content, pass assessments, and move on,” he says. “But these activities create data points, not necessarily mastery.”
Related: Argentina and Chile Reveal Border Security Trends
This approach assumes a hypothetical average learner, ignoring the unique experiences, motivations, and goals of individuals. Learning science, which blends cognitive psychology, neuroscience, and data analytics, offers a better framework. Research shows people absorb information at different rates, and retention improves when knowledge is revisited in practical contexts.
Adapting Frameworks for Individual Needs
Many companies rely on Bloom’s Taxonomy as a guide, but Mentor126 argues that other models can be more effective in certain situations. For instance, some learners benefit from inverting Bloom’s hierarchy, focusing on application before memorization. Theocheung highlights the value of theories like Knowles’ andragogy, which emphasizes adult learning principles. “Systems must adapt to the individual,” he says. “Not every learner fits the same model.”
AI introduces new possibilities for scaling personalized learning. Mentor126 uses a Personal Knowledge Graph (pKG) to track learners’ goals, job roles, learning styles, and progress without relying on self-reported surveys. This system continuously updates based on behavioral patterns, skill gaps, and engagement data.
Related: Thindal and Core Capital defend BCSC appeal record
Learning as an Ongoing Process
Traditional training often ties to onboarding, quarterly initiatives, or compliance deadlines. But business environments change faster than these schedules can keep up. New products, shifting customer expectations, and evolving regulations create gaps. Mentor126’s solution, React Micro-Training, delivers learning in response to real-time needs. “Instead of waiting for scheduled cycles,” Theocheung says, “learning can adapt to what’s happening now.”
This approach tailors experiences to specific roles—sales representatives, engineers, or customer service staff—ensuring relevance. Continuous learning systems also help new hires reach productivity faster by aligning with their existing experience. Sales teams can practice dynamic roleplay scenarios, while employees gain confidence by addressing role-specific knowledge gaps.
Related: Top 10 Tips for Crafting a Winning Business Plan in 2026
Measuring Impact Beyond Metrics
Organizations are increasingly focusing on outcomes. A survey shows 68% of employees believe training improved their job performance. Initiatives targeting professional and interpersonal skills often yield measurable business value. Mentor126 stresses that relevance drives engagement. “When learning connects to daily decisions,” Theocheung says, “organizations create opportunities for people to apply new information while it still matters.”
As AI and learning science advance, the future of enterprise training may hinge on how well systems adapt to individual needs. Companies that invest in understanding how people learn—and what they need to learn—could better support long-term growth, capability development, and workforce readiness.
