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Key Takeaways:
- Customer Education teams are using AI to create more content faster, analyze data, summarize meetings, and supplement decision-making.
- AI-powered personalization is still developing. We are closing the gap with skill development and better content & data organization.
AI models have improved exponentially each year since ChatGPT’s 2022 release, expanding the limits of productivity across many disciplines. Customer Education is no exception.
In Well CEd!, CloudShare’s annual collection of expert insights on key topics and trends in the industry, AI’s impact on Customer Education is a recurring topic. With the longstanding challenge of proving value, Customer Education practitioners are wise to look for ways AI can speed workflows, produce content, and analyze performance and outcomes.
However, the experts agree: implementing AI for AI’s sake can distract from core learning objectives, and AI’s most promising use cases in education are still taking shape.
The experts break down the current state of AI in Customer Education, their favorite tools and use cases, and where the technology is headed.
AI Expectations and Reality
Personalization
Last year, in Well CEd! 2025, the experts identified several areas where they expected AI’s capabilities to develop significantly. One common target was personalization of learning content and experiences. Customer Education practitioners anticipated that current AI would enable the ability to surface highly-tailored content at just the right time for each individual learner.
While teams have made some moves toward AI-powered personalization, most of the experts agree we are still a ways from true personalization. Barriers include a lack of data architectures that support cohesive, personalized experiences, hesitancy to adopt due to security or resource constraints, and added complexity for teams.
Support
The Customer Education leaders also predicted that AI would improve the speed and level of support offered to learners. In 2026, the experts report increased speed through support automation, which comes largely in the form of AI chatbots. Roberto Aiello of Personio observed that AI has improved the user experience by summarizing data. With AI-generated overviews, customers can understand their data more quickly and clearly, which reduces the need for support tickets.
Content
By far the biggest benefit of AI for Customer Education practitioners is content production. The latest AI tools allow teams to generate course outlines and content in less time — without increasing resources. As a result, teams can publish more content and update content faster.
Multiple experts highlighted video content as a format enhanced by AI. Steven Carr of Infoblox shared that avatar-based video tools have reduced his team’s development time by around 60 percent, allowing them to keep pace with product updates and publish content faster. Dror Kroparo of MDClone agreed, giving an example: “using Guidde AI, ChatGPT, and NotebookLM, our team of just two people created 90 how-to video tutorials in only 3 weeks, compared to just 34 videos over 3 months using our previous tools.”
Analysis
Another function AI has improved for the experts is data analysis. AI enables Customer Education practitioners to more quickly synthesize customer inputs and activities, gaining critical insights into behavior change and facilitating decision-making.
For example, Dan Braithwaite of Mediaocean says his team uses Microsoft’s Copilot to analyze whether factors like class size and implementation impact NPS scores.
Favorite AI Tools for Customer Education
Customer Education teams have a variety of tools to choose from, often feeling pressured to adopt the latest to remain current and competitive. When it comes to AI tools, the influencers advocate for an intentional approach; teams should do their due diligence to ensure each tool meaningfully contributes to learning and business outcomes. These are some of the tools they identified as strong contenders, depending on your Customer Education goals:
General-Purpose AI Models
An all-purpose LLM is a must-have for modern teams looking to save time on tasks such as ideation, research, text generation, editing, and data analysis. The most popular models can perform these functions, with slightly different strengths and weaknesses to consider based on your primary purpose in using the tool.
Here is the experts’ short list:
Content Creation
AI has sliced content creation time in half for Customer Education teams. While general-purpose models are helpful for creating text- and image-based content, specialized tools expedite the creation of complex content, such as training videos and documentation. Here are some of the experts’ recommendations.
- Guidde AI – Generative AI tool for creating video documentation for onboarding, training, how-to guides, feature notes, and more
- Synthesia – Text-to-video creation with AI avatars and voiceovers
- Zenious AI – AI-powered product education tool supporting documentation and videos
- HeyGen – AI video generator translating photos and videos to longer videos with avatars
- Descript – AI video editing tool
Productivity
At the individual and team levels, AI tools can help simplify everyday workflows. Many of the experts save time by using tools such as Otter.ai or Fathom.ai to record, transcribe, and summarize meetings.
For research purposes, including document analysis and summarization, NotebookLM is frequently cited. This tool also draws connections between multiple uploaded documents, accelerating learning and decision-making.
What’s Next for AI in CEd?
Customer Education teams will continually need to evolve in response to new technologies and discern which AI tools will add value rather than create a distraction. This will require teams to invest in developing AI expertise and skills, and, as Dave Derington of VAST Data suggests, potentially hiring for AI-specific roles.
While personalization in learning delivery has not fully emerged, the Customer Education experts share a conviction that we will soon achieve this capability as models become more sophisticated and organizations solve for structuring their data for AI.
Debbie Smith, President of CEdMA, champions a ‘Jobs to Be Done’ framework for designing training content. By focusing on customers’ roles and the jobs they aim to accomplish with your software, Customer Education teams can break training into tasks. Then, AI will be able to use data to serve the right content to the right customers based on the tasks they need to complete, enabling true personalization.
This marks a shift from focusing primarily on generative AI to exploring and expanding the capabilities of agentic AI in workflow automation, personalized learning paths, real-time feedback, and beyond. With AI managing large parts of the content development and learning delivery processes, Customer Education teams will be able to work more efficiently and focus on what truly matters: delivering positive customer outcomes and proving the value of their programs.
