Why AI in Learning & Development Is Surging
Artificial Intelligence (AI) is no longer just a buzzword in HR tech. According to McKinsey's 2025 State of AI report, 78% of organizations now use AI in at least one business function—a dramatic rise from 2024. Learning & Development (L&D) is among the areas being reshaped, with early adopters reporting efficiency gains, faster knowledge delivery, and better personalization.
The potential is clear: traditional training models are costly, slow, and often ineffective. The promise of AI-driven training is faster onboarding, higher retention, and measurable ROI. But what does the evidence actually show?
The Retention Problem with Traditional Training
Over a century ago, psychologist Hermann Ebbinghaus illustrated the "forgetting curve": without reinforcement, people quickly forget new information. Modern L&D leaders still face this challenge—studies consistently show that employees lose much of what they learn in one-off training within days or weeks.
AI can counter this problem by:
- Delivering spaced reinforcement (nudging employees at the right time)
- Adapting pace and difficulty to each learner
- Tracking knowledge gaps automatically
Instead of static training sessions, AI can turn learning into a continuous process.
The ROI Case for AI in Training
1. Faster Skill Acquisition
AI tutors and adaptive platforms allow learners to progress at their own pace. While exact figures vary, PwC found that VR-based training (an AI-enabled immersive modality) helped employees learn up to 4× faster than classroom training, and boosted confidence by 275%.
2. Improved Retention & Confidence
Adaptive AI systems can personalize reinforcement, helping employees retain and apply what they've learned. While retention gains are context-specific, immersive and adaptive methods consistently outperform lecture-based training.
3. Reduced Training Costs
Deloitte highlights that AI can streamline training content creation and delivery, reducing administrative burden and freeing L&D teams to focus on strategy. While Deloitte doesn't assign exact percentages, case studies show meaningful savings in time and development effort.
4. Shorter Onboarding Cycles
Onboarding is one of the most expensive stages of employment. Industry benchmarks suggest it often takes 6–12 months for a new hire to reach full productivity. AI-driven simulations, just-in-time learning, and adaptive onboarding paths can help reduce that time—directly improving ROI by cutting the "time-to-value" of new employees.
The Future: Where AI in Training Is Heading
Gartner predicts that by 2028, 40% of employees will be trained and coached by AI when entering new roles—a strong signal that AI-powered learning is moving from experimental to mainstream.
We're also likely to see:
- Smarter skills gap analysis: AI that proactively maps employee skills against evolving role requirements
- Seamless integration into workflows: learning embedded directly into the tools employees already use
- More immersive training modalities: AI avatars, simulations, and VR/AR experiences providing "learning by doing"
Bottom Line
AI-powered training does deliver measurable ROI, but the real benefits aren't in flashy percentages—they're in:
- Shorter onboarding times
- More confident, capable employees
- Reduced content development costs
- Training that adapts to individuals instead of treating everyone the same
As adoption accelerates, the question for organizations is no longer "Should we explore AI in training?" but "How do we integrate it responsibly, effectively, and in a way that aligns with our workforce strategy?"
Measuring Real ROI with Velenta
The ROI of AI training becomes tangible when organizations can measure actual performance improvements. Velenta delivers measurable training ROI by combining Quick-Learn micro-courses for efficient knowledge transfer with AI-driven scenario simulations where employees practice client-facing situations—renewal conversations, expansion discussions, handling escalations—in risk-free environments.
After each simulation, AI provides comprehensive performance analysis across communication clarity, decision-making, process knowledge, and professionalism, creating a clear before-and-after comparison that demonstrates skill development. This data-driven approach allows organizations to quantify training effectiveness, track time-to-competency improvements, and calculate actual ROI based on measurable performance gains rather than just completion rates.
Sources:
- McKinsey & Company. The State of AI in 2025.
- Gartner. Predicts 2024: AI and the Future of Work.
- PwC. The Effectiveness of Virtual Reality Soft Skills Training in the Enterprise.
- Deloitte. 2024 Global Human Capital Trends.
- Hermann Ebbinghaus. Memory: A Contribution to Experimental Psychology (1885).