2026年人工智能在客户教育领域应用状况研究报告

Benchmarks, budgets & ROI from 270+ leaders Listen to the key findings in 5 minutes Table of contents 16 AI adoption and ownershipAI budgets and ROIUse cases and tools The way forward 1. Educate your team: AI literacy is now part of the job2. Audit your workflows: See where AI is already appearing A word fromSection 1 LearnWorlds’ CEO A word from LearnWorlds’ CEO AI has moved from “interesting demo” to everyday tool in customer education. The leaders we spokewith describe real momentum: AI is speeding first drafts, transcript clean‑ups, repurposing, transla‑tions, and routine updates, so teams can focus on the parts of the craft that actually drive outcomes. Two things can be true at once. AI acceleratesproduction by default; excellence still requires in-tent and human judgment. If your system is strong,AI amplifies it. If your system is weak, AI exposes it.The programs we see pulling ahead treat AI as in-frastructure, not novelty. They name an owner, set Our point of view.AI buys back time for instruc-tional design and the human touches that makelearning stick. That’s the philosophy behind ourplatform. In essence, we’re building a LearningOperating System: assistive AI that speeds creationand upkeep; a model that makes content struc- You’ll see that pragmatism throughout this report.Budgets are rising, experiments are paying off onreasonable timelines, and teams are learning howto keep the human voice at the center. The gaps If you’re ready to turn experiments into an oper-ating model, we’d love to compare notes. I hopethe insights here save you months of trial anderror, and help you build deeper, more human Why we’re publishing this.LearnWorlds sits atthe intersection of product and learning for thou-sands of teams around the world. With that van-tage point comes a responsibility: separate signal Panos Siozos,PhDCo-Founder & CEO @ LearnWorlds Section 2Main takeaways Main takeaways 1. AI adoption is uneven and deeply contextualAI is already reshaping customer education, but not in a single, uniform way. Insights from 274 CE pro- fessionals and 12 in-depth interviews show a landscape defined by uneven, contextual adoption rather 2. A clear maturity gap is emergingAround 60% of teams are still in “pre-production” mode, either not using AI, planning to adopt it, or experimenting in isolated pockets. Meanwhile, 37% say AI is in pilots, embedded into some workflows, orcore to most initiatives. This more advanced group treats AI as infrastructure that supports how content 3. AI is entering through grassroots experimentation, ownership remains muddyMore than a third of respondents say their first AI initiative started through grassroots experimentation, not a leadership directive. At the same time, 42.5% report no clear owner for AI strategy in CE. This mixof high practitioner energy and low structural clarity explains why many teams remain stuck between 4. Budgets and expectations are rising faster than systemsAI spend is still modest (median ~$1,000/year), yet nearly half expect this to increase. Most anticipate tangible ROI within 12 months, over a third expect it in under six. But a significant portion don’t knowwhen AI will pay off or what their future budget will be. 5. AI is already woven into everyday content workflowsA majority of CE teams say AI now supports up to a quarter of new content, and more than a quarter report AI assisting over 25% of educational content. ChatGPT dominates (82%), with tools like Gemini, Claude, Per-plexity, Synthesia, HeyGen, Clueso, and ElevenLabs forming a second wave of specialized capabilities. 6. The biggest wins are happening early in the content lifecycle AI is most commonly used for text generation, course outlines, transcript cleanup, and repurposingexisting materials. For now, it carries the weight of drafting and maintenance so humans can focus on 7. Risks and quality concerns are significant Nearly half worry about quality and accuracy; around a third fear losing the human touch. Others high-light data privacy, job security, over-reliance, and erosion of critical thinking. Most CE professionals rateAI content a “3 out of 5.” It makes it easier to create more content, but not necessarily better content. 8. Skills and systems are lagging behind ambition More than half say there is no formal plan to improve AI literacy in their team by 2026. Many turn to ex-ternal specialists rather than building internal capability. Meanwhile, fragmented tech stacks (LMS, prod-uct analytics, support, community, and AI tools) stitched together with brittle integrations and manual 9. Teams are prioritizing more contextual, in‑product learning Trigger-based and just-in-time learning are becoming a priority. Teams are exploring ways to surfacethe right content exactly when a customer needs it, often inside the product. There is also growing in-terest in using AI to turn data (usage, behavior, support queries) into actionable signals and short