Gen Z is the most likely generation to use AI for learning—but 57% say they struggle to apply what they learn

A Preply survey of more than 5,000 workers across nine countries found that 92% of Gen Z respondents use AI for learning, but 57% struggle to apply what they learn in practice, versus 40% of Gen X. Across all respondents, 76% are spending more time learning than two years ago, yet 52% said that additional time does not consistently produce better results. The findings suggest employers' AI learning investments require complementary coaching, workplace feedback, and practical human interaction to translate AI-assisted knowledge into job skills.

Analysis

This is not a demand catalyst for enterprise learning vendors; it is a warning that seat adoption can outpace measurable skill transfer. Buyers are likely to shift 2026 L&D budgets away from static content libraries and generic AI assistants toward platforms that evidence application—manager workflows, simulations, assessments, coaching, and performance-linked analytics. That raises customer-acquisition and product-investment requirements while making low-engagement content catalogs more vulnerable to renewal pressure.

For SKIL, the relevant issue is whether AI-enabled personalization converts into utilization, certification completion, and retention rather than merely lower content-production costs. The company’s ability to bundle coaching, hands-on practice, and manager dashboards will matter more than chatbot functionality; otherwise, generative AI commoditizes portions of its library and strengthens buyer leverage at renewal. The survey is directional rather than causal, so it does not independently establish AI-driven learning failure or an immediate earnings impact.

Over the next 1-3 months, watch enterprise commentary on learning-budget ROI, renewal cycles, net retention, and services attach rates across digital-learning peers. Over 6-18 months, hybrid-work onboarding gaps could create a durable premium for vendors that integrate human experts and job-specific practice, but this is a fragmented market where AI-native point solutions can capture value before legacy platforms adapt. Consensus may overestimate the near-term margin benefit from AI content generation: savings may be competed away through higher spend on coaching, data integration, and customer-success support.

Key Decisions for Investors

• No directional SKIL position on this survey alone; impact is too indirect and the article provides no evidence of changed bookings, churn, or pricing.
• Set an earnings watch on SKIL: consider a tactical long only if management shows improving enterprise renewals/net retention alongside growth in coaching, assessments, or practice-based offerings. Falsify on weaker guidance, rising churn, or evidence that AI features are bundled without monetization.
• For a 6-18 month thematic basket, favor enterprise software vendors with workflow-embedded training and measurable productivity outcomes over pure content-library exposure; require quarterly proof of paid adoption and retention before sizing.
• Monitor L&D budget surveys and large-enterprise procurement language over the next two quarters. A shift from "AI learning access" to validated competency, manager coaching, and simulation requirements would support a re-rating of outcome-oriented training vendors and pressure undifferentiated content providers.