New Report Reveals 67% of L&D Professionals Want AI Skills They Don’t Have – A Significant Opportunity for Education Affiliates

A new industry report has quantified what many in the training space suspected: professionals know they need AI skills, but most don't have access to the training that would give them confidence to use these tools effectively. For affiliates promoting courses, certifications, and upskilling platforms, the data points to substantial demand waiting to be served.

Synthesia's AI in Learning & Development Report 2026, based on 421 responses from L&D professionals globally, found that 67% want AI skills and design training, 63% need help with L&D workflows, and 63% are seeking support in measuring AI's impact. Half of respondents said they need integration help, while 44% want guidance on responsible AI use.

These aren't theoretical knowledge gaps. They represent professionals who are already using AI—87% of respondents are actively deploying it in their work—but who feel underprepared to use it well.

The Gap Between Adoption and Competence

The report captures an interesting moment in AI adoption. The experimentation phase appears to be ending. Last year, 20% of L&D professionals weren't using AI at all. That figure has dropped to just 13%, with only 2% saying they have no adoption plans.

But adoption without competence creates its own problems. While 57% of teams are actively using AI and another 30% are running early pilots, the maturity distribution tells a different story. Only 9% have reached the stage of scaling AI across their organisation, and just 6% describe themselves as “fully integrated” or operating with an “AI-first mindset.”

Dr Philippa Hardman, a learning science expert and co-author of the report, put it directly: “Maturity is rising—but it's far from uniform. Many teams are still early-stage; a small group is sprinting ahead.“

The implication for affiliates is clear. There's a large middle ground of professionals who have moved past scepticism but haven't yet developed the skills to use AI strategically. They're actively looking for training that bridges that gap.

What Professionals Actually Want to Learn

The skills gap isn't abstract. The report identifies specific areas where L&D professionals feel underprepared.

At the top of the list is AI skills and design training, requested by 67% of respondents. This goes beyond basic tool usage—professionals want to understand how to integrate AI into instructional design workflows, how to evaluate AI outputs, and how to design learning experiences that leverage AI capabilities effectively.

Workflow guidance comes next at 63%. Teams have tools, but they're uncertain about optimal processes. How should AI fit into existing content development cycles? When should human review happen? What quality assurance processes work best?

Impact measurement, also at 63%, reflects growing pressure on L&D teams to demonstrate value. As Kristen Budd, a learning experience designer quoted in the report, noted: “L&D teams are under growing pressure to demonstrate the impact of AI. Measuring value is one of the top capability gaps, with 63% saying they need support in assessing impact rather than just speed.“

Integration support (50%) addresses technical challenges—connecting AI tools to existing learning management systems, productivity tools, and enterprise platforms. And responsible AI guidance (44%) reflects awareness that AI use carries ethical and compliance implications that most L&D professionals haven't been trained to navigate.

The Blocker Landscape Creates Additional Opportunities

Beyond skills gaps, the report identifies blockers that are slowing AI adoption—each representing potential content angles for affiliates in the education space.

Security concerns top the list at 58%, followed by accuracy worries at 52%. Legal constraints affect 41% of respondents, while integration challenges impact 46%. Budget approvals (44%) and lack of internal expertise (46%) round out the major obstacles.

These blockers suggest that training focused purely on “how to use ChatGPT” may miss the mark. Professionals need education on security considerations when deploying AI in enterprise environments, on evaluating AI accuracy for professional applications, and on compliance frameworks governing AI use in regulated industries.

The governance angle is particularly underdeveloped. The report found that 59% of teams avoid using personal or sensitive learner data with AI, and 18% say their approval process for AI use remains unclear. As adoption moves toward personalisation—which 72% expect to be AI's biggest future impact—these governance gaps will become more pressing.

Tool Preferences Highlight Content Opportunities

The report also reveals which tools L&D professionals are actually using, providing direction for affiliates creating reviews and tutorials.

ChatGPT dominates at 74% usage, followed by Microsoft Copilot at 54% and Gemini at 38%. NotebookLM (33%), Claude (28%), and Perplexity (25%) round out the top tools. Only 2% report using no general-purpose AI tools.

The heaviest use sits in production tasks: voice generation (63%), quiz and content drafting (60%), video creation (52%), and translation (38%). These activities cluster in the design and develop stages of the ADDIE model, with more than 65% of respondents routinely using AI to create learning materials.

For affiliates, this tool landscape suggests opportunities to promote AI platforms with strong L&D applications—particularly those offering voice generation, video creation, and translation capabilities. The market has moved beyond general-purpose chatbots toward specialised tools that address specific professional workflows.

The Emerging Agentic AI Opportunity

Looking ahead, the report identifies agentic AI—AI that can autonomously take actions rather than simply generate content—as an emerging area of interest.

27% of respondents are actively exploring agentic AI, while 39% are interested but cautious. Notably, none rejected it outright. The hesitation appears to stem from unfamiliarity rather than resistance.

Exploration patterns show where interest is highest: AI tutors lead at 48%, followed by coaching and mentoring applications at 43%, personalised guidance at 43%, admin automation at 38%, and course building at 37%.

For affiliates tracking AI innovations, this signals a shift from content creation tools toward performance support systems. The next generation of L&D AI tools won't just help professionals create training materials—they'll deliver that training directly to learners through AI tutors, coaching systems, and personalised guidance engines.

The LMS Disruption Creates Platform Uncertainty

One of the report's more significant findings concerns the future of Learning Management Systems. Only 47% of respondents believe the LMS will remain the backbone of their learning ecosystem over the next three years.

Where will AI capabilities live instead? Responses split almost evenly across four possibilities: embedded in the LMS or learning experience platform (19%), embedded in productivity tools like Microsoft 365 or Google Workspace (17%), delivered through standalone AI platforms (17%), or operating as cross-system agentic layers (19%).

The largest group, at 27%, simply doesn't know yet.

This uncertainty reflects a market in transition. As Kevin Alster, Strategic Advisor at Synthesia, observed: “L&D is entering a new ‘AI-integrated' era where the real question isn't which tools to use but how to build a learning ecosystem that drives performance.”

For affiliates, this suggests opportunity in platforms that bridge multiple categories—tools that integrate with existing LMS infrastructure while also offering standalone capabilities and productivity tool connections.

What This Means for Education Affiliates

The data points to a substantial market of professionals who have adopted AI but feel underskilled, who face organisational blockers they don't know how to navigate, and who are uncertain about which platforms will define the next generation of their tech stack.

Several specific opportunities emerge for affiliates in the education and training space.

First, the demand for practical AI skills training—not theoretical overviews, but workflow-integrated instruction on using AI for specific professional tasks—appears strong and underserved. Content and courses that address the 67% seeking AI skills and design training have an addressable audience that self-identifies as needing help.

Second, the blocker landscape suggests opportunity for compliance-focused training. Security, accuracy, legal constraints, and governance represent areas where professionals feel uncertain. Training that helps navigate these concerns addresses real barriers to adoption.

Third, tool-specific training has a clear audience. With ChatGPT at 74% penetration and Copilot at 54%, courses that go beyond basics to address professional applications—particularly for content creation, video generation, and translation—address documented use cases.

Fourth, the agentic AI space is early enough that educational content can establish authority. Professionals are interested but cautious; training that demystifies AI tutors, coaching systems, and automated assessment tools could capture attention as this category develops.

Finally, the measurement challenge affects 63% of respondents. Training that helps L&D professionals demonstrate ROI from AI investments addresses a capability gap that has direct business implications.

The Optimism Factor

Despite the skills gaps and blockers, the report's overall tone is optimistic. 66% of respondents believe AI will strengthen L&D's influence within their organisations, and 72% think the function will thrive by adapting to AI.

This optimism matters for affiliates. Professionals who believe AI will enhance their careers are more likely to invest in training that helps them capture that opportunity. The narrative isn't “AI will replace us” but “AI will elevate what we do—if we develop the skills to use it well.”

As Dr Hardman concluded: “Over the next 12-24 months, I expect to see a sharper divide between teams who use AI to go faster, and teams who use AI to build smarter, more personalised, more evidence-based learning ecosystems.“

That divide creates the market. Affiliates who can connect professionals with training that helps them land on the right side of it are addressing documented demand.

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