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The AI Expectation Gap In Learning Tech 2026: What Learning Tech Vendors Need To Know About L&D Buyer Expectations

by eLearning Industry

Want to understand what L&D buyers really expect from AI-powered learning technology—and what that means for your marketing and product strategy?

Based on insights from 500+ L&D professionals and learning technology vendors, this benchmark report reveals where buyer expectations and vendor priorities align, where they diverge, and where opportunities exist. Use the findings to sharpen your positioning, strengthen your messaging, understand buying priorities, and better align your go-to-market strategy with market demand.

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AI Learning Technology Market Research 2026 | Buyer Insights The AI Expectation Gap In Learning Tech 2026: What Learning Tech Vendors Need To Know About L&D Buyer Expectations - eLearning Industry
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Key Chapters

  1. Executive Summary

    Get the key findings vendors need to understand the emerging AI expectation gap and changing market demand.

  2. Introduction & Scope Of Research

    Understand the research methodology, audience, and market context behind the findings.

  3. Part I: The Learning Solutions Landscape

    See how L&D buyers select platforms, what they use today, and where adoption opportunities are emerging.

  4. Part II: AI Importance And Integration

    Discover which AI capabilities buyers value most—and where vendor investment may be ahead of or behind demand.

  5. Part III: Learning About AI

    Learn what information buyers want from vendors, how they educate themselves, and which content formats influence them.

  6. Part IV: Skills For The AI Era

    Understand the skills priorities shaping organizational demand and future learning technology needs.

  7. Part V: L&D Buyer Personas & Decision-Making Dynamics

    Identify the roles involved in purchasing decisions and what matters across the buying committee.

  8. Part VI: Measuring Business Impact Of AI

    See which outcomes buyers use to assess AI value and how vendors can better communicate business impact.

  9. Conclusion, Insights & Recommendations

    Turn the AI expectation gap into actionable opportunities for product positioning, messaging, and go-to-market strategy.

  10. Appendix: Research & Sample Information

    Review the methodology, sample composition, and supporting research details.

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