Most training content is still being treated like a one time event, even though people forget 80% of what they learn within 24 hours without reinforcement and only retain about 63% after 20 minutes when no effort is made to keep it. At the same time, 42% of employees say information is hard to find at work, so the bottleneck is not just learning but retrieval. The surprising part is what consistently beats the status quo, from retrieval and spacing to dual coding and sleep, and how big the payoff can get when you measure it properly.
Key Takeaways
- 42% of employees say information is hard to find at work
- 80% of what people learn is forgotten within 24 hours without reinforcement (Ebbinghaus forgetting curve)
- 63% of information is retained after 20 minutes when no effort is made to retain it (Ebbinghaus forgetting curve relationship, widely cited)
- A meta-analysis found that retrieval practice improves long-term retention with an average effect size of g≈0.78
- The global corporate learning management system (LMS) market was valued at $21.2 billion in 2023 and is projected to reach $44.3 billion by 2030
- The global knowledge management software market is projected to grow from $12.3 billion in 2024 to $23.4 billion by 2030
- The global e-learning market is expected to reach $404.1 billion by 2026 (from $180.0 billion in 2020)
- On average, employees retain 25% to 60% more material when training is delivered via e-learning rather than traditional methods
- Companies using learning and development platforms report 10% higher employee productivity on average (vendor research survey result)
- A 2016 meta-analysis found that workplace training programs produce average effect sizes corresponding to meaningful improvements in job performance
- The WHO estimates that over 10% of the world’s population has a hearing loss in one ear (hearing impairment affects training comprehension and retention for a subset of workers)
- The WEF estimates that 44% of workers’ skills will be disrupted by 2022 (impacts retention needs as knowledge refresh cycles accelerate)
- McKinsey reports that 30% of US work activities could be automated with current technology (increasing the need for retention of changing task knowledge)
- 56% of organizations report using learning analytics (e.g., tracking engagement and assessment results) to evaluate training effectiveness
- 1.5x average improvement in assessment scores after implementing spaced and retrieval-based study methods (compared with traditional approaches) in a 2022 workplace training evaluation study
Retrieval and spaced learning beat forgetting, boosting long term retention and productivity for teams.
Workforce Behavior
142% of employees say information is hard to find at work[1]
Verified
Workforce Behavior Interpretation
From a Workforce Behavior perspective, the fact that 42% of employees say information is hard to find suggests many teams are spending time searching instead of acting, which can erode knowledge retention in everyday work.
Learning & Memory
180% of what people learn is forgotten within 24 hours without reinforcement (Ebbinghaus forgetting curve)[2]
Single source
263% of information is retained after 20 minutes when no effort is made to retain it (Ebbinghaus forgetting curve relationship, widely cited)[3]
Verified
3A meta-analysis found that retrieval practice improves long-term retention with an average effect size of g≈0.78[4]
Verified
4Spacing practice produces better retention than massed practice, with a typical benefit captured as effect sizes across studies in the range of small-to-moderate (reported in a review)[5]
Verified
5Interleaving practice improves learning outcomes compared with blocked practice in multiple domains, as shown in a review[6]
Directional
6The testing effect (retrieval practice) has been observed to improve performance by approximately 10–30% in many classroom learning experiments (reviewed evidence)[7]
Single source
7Recognition memory is typically higher than recall; in one classic study, recall performance is lower than recognition across delays[8]
Verified
8Working memory capacity predicts learning outcomes; in a meta-analysis, working memory relates to fluid intelligence with r≈0.60[9]
Verified
9Sleep improves memory consolidation; a meta-analysis reported that sleep-related memory benefits are significant with an overall effect (Hedges g) reported in the study[10]
Directional
10Dual coding (combining words and images) increases recall; a review reports improved learning outcomes for dual coding relative to verbal-only conditions[11]
Single source
11Elaboration (explaining and linking new information to existing knowledge) improves retention, as supported by educational psychology meta-analyses (effect sizes summarized in the review)[12]
Verified
12In a randomized trial, adding retrieval practice improved retention compared with restudy-only control over a 1-week delay[13]
Single source
Learning & Memory Interpretation
For Learning and Memory, the strongest trend is that active remembering works far better than passive exposure, since without reinforcement people retain only 63% after 20 minutes and about 80% is forgotten within 24 hours, while retrieval practice boosts long-term retention with an average effect size around g 0.78 and often improves classroom performance by roughly 10 to 30%.
Market Size
1The global corporate learning management system (LMS) market was valued at $21.2 billion in 2023 and is projected to reach $44.3 billion by 2030[14]
Directional
2The global knowledge management software market is projected to grow from $12.3 billion in 2024 to $23.4 billion by 2030[15]
Directional
3The global e-learning market is expected to reach $404.1 billion by 2026 (from $180.0 billion in 2020)[16]
Verified
4The global HR software market is projected to reach $77.9 billion by 2028[17]
Verified
5The global talent management software market was $8.5 billion in 2023 and is forecast to reach $16.1 billion by 2028[18]
Verified
6The global corporate training outsourcing market was valued at $333.1 billion in 2023[19]
Single source
7The global enterprise content management market size is forecast to reach $52.4 billion by 2028[20]
Directional
8The global business process management (BPM) software market is forecast to reach $9.8 billion by 2028[21]
Directional
Market Size Interpretation
In the Market Size category, the corporate learning and training ecosystem is expanding rapidly, with the global e-learning market expected to jump from $180.0 billion in 2020 to $404.1 billion by 2026, signaling major growth in demand for platforms and services.
Performance & Roi
1On average, employees retain 25% to 60% more material when training is delivered via e-learning rather than traditional methods[22]
Verified
2Companies using learning and development platforms report 10% higher employee productivity on average (vendor research survey result)[23]
Verified
3A 2016 meta-analysis found that workplace training programs produce average effect sizes corresponding to meaningful improvements in job performance[24]
Single source
4In a longitudinal study, effective knowledge management practices are associated with higher organizational performance (reported correlation coefficients in the study)[25]
Single source
Performance & Roi Interpretation
Under the Performance and Roi lens, the data points to a clear productivity and results boost, with employees retaining 25% to 60% more material through e-learning and companies using learning platforms reporting about 10% higher productivity on average.
Industry Trends
1The WHO estimates that over 10% of the world’s population has a hearing loss in one ear (hearing impairment affects training comprehension and retention for a subset of workers)[26]
Verified
2The WEF estimates that 44% of workers’ skills will be disrupted by 2022 (impacts retention needs as knowledge refresh cycles accelerate)[27]
Verified
3McKinsey reports that 30% of US work activities could be automated with current technology (increasing the need for retention of changing task knowledge)[28]
Single source
4Gartner forecasts that by 2024, 75% of large organizations will use AI to assist with business process automation (changing knowledge requirements and tool mastery)[29]
Verified
5NIST’s AI Risk Management Framework (AI RMF 1.0) was released in January 2023 to help organizations manage risks; training content must be retained and applied consistently under new AI governance[30]
Verified
6In the US, the Bureau of Labor Statistics reports average tenure is 4.1 years (job changes affect organizational knowledge retention)[31]
Verified
7In 2023, the US quit rate was 2.4% (higher churn can increase knowledge loss risk)[32]
Verified
861% of organizations report that skills required for their roles change at least annually, increasing the need for ongoing knowledge retention and refresh cycles[33]
Directional
Industry Trends Interpretation
Industry trends are making knowledge retention a moving target, with 61% of organizations reporting role skills change at least annually and the WEF estimating 44% of workers’ skills will be disrupted by 2022, forcing more frequent refresh cycles to keep training effective.
Performance Metrics
156% of organizations report using learning analytics (e.g., tracking engagement and assessment results) to evaluate training effectiveness[34]
Verified
21.5x average improvement in assessment scores after implementing spaced and retrieval-based study methods (compared with traditional approaches) in a 2022 workplace training evaluation study[35]
Verified
Performance Metrics Interpretation
For performance metrics, learning analytics are already used by 56% of organizations, and a 2022 workplace study found a 1.5x improvement in assessment scores when learners use spaced and retrieval-based methods rather than traditional approaches.
Workplace Practices
164% of frontline workers report that hands-on practice and coaching improve their ability to remember safety steps during incidents[36]
Verified
271% of employees state they prefer short learning bursts they can revisit, supporting repeated exposure strategies that improve retention[37]
Directional
Workplace Practices Interpretation
Under Workplace Practices, employees strongly back repetition and support, with 71% preferring short learning bursts to revisit and 64% of frontline workers saying hands-on coaching helps them remember safety steps during incidents.
How We Rate Confidence
Models
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Single source
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Directional
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
Verified
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Models
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
APA
Nathan Caldwell. (2026, February 13). Knowledge Retention Statistics. Gitnux. https://gitnux.org/knowledge-retention-statistics
MLA
Nathan Caldwell. "Knowledge Retention Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/knowledge-retention-statistics.
Chicago
Nathan Caldwell. 2026. "Knowledge Retention Statistics." Gitnux. https://gitnux.org/knowledge-retention-statistics.
References
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- 29gartner.com/en/newsroom/press-releases/2021-02-18-gartner-predicts-75-of-large-organizations-will-apply-artificial-intelligence-to-business-process-automation-by-2024
- 25sciencedirect.com/science/article/pii/S1877042813001555
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- 27weforum.org/reports/the-future-of-jobs-report-2020/
- 28mckinsey.com/featured-insights/mckinsey-explainers/what-is-generative-ai
- 30nist.gov/publications/artificial-intelligence-risk-management-framework-ai-rmf-10
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