The 10 most valuable AI skills students want to learn

There are 10 foundational AI skills education leaders should embed in their curriculum to ensure graduates are ready for the workforce, a new Coursera report contends.

Student interest in generative AI is exploding as employers across industries make the technology a key part of daily operations.

Participation in Coursera’s generative AI courses has increased by 234% over the last year, while professional certificate enrollment jumped by 91% as employers wish to verify what job candidates are learning.

The fastest-growing, non-technical AI skill is creating content that promotes a business’ strategy or services.

Courses that focus on critical thinking around responsible and ethical AI use have grown by 185%. Critical thinking is increasingly taught in STEM disciplines, including data, IT and software development.

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Higher education leaders should integrate foundational generative AI skills into non-technical coursework to ensure students excel after graduation, Coursera wrote.

The 10 fastest-growing, non-technical AI skills

Coursera analyzed its enrollment from 2023 to 2025 to identify these 10 most sought-after AI skills:

1. Content creation: Producing and sharing articles, videos and social media posts to engage with different audiences across multiple platforms.
2. AI personalization: Using data about a customer’s actions to make content and online experiences more relevant to them.
3. Generative AI agents: Crafting prompts that let AI systems work independently.
4. Image analysis: Teaching computers how to “see” and make sense of pictures and videos.
5. Information privacy: Protecting personal data from unauthorized access
6. Critical thinking: The ability to evaluate information and situations to make good decisions and solve problems.
7. Debugging: Finding and fixing problems in software or hardware.
8. Multimodal prompts: Giving an AI instructions with different types of information, such as text and images, to get better and more relevant results.
9. AI product strategy: Using technology to help plan, build and manage products.
10. LLM application: Using large language models to create chatbots that can understand and respond to human input.