Generative AI is an advanced technology that can rapidly produce lifelike images, text, and animations. In our research, we examined its use across various industries, including healthcare and banking.
While other technologies, such as conversational AI and robotic process automation (RPA), are being implemented in education, generative AI is not being properly implemented in education.
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Use Cases |
Description |
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Creates customized curricula by analyzing individual student data. |
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Organizes and tailors course materials to student needs. |
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Generates quizzes, exercises, study guides, and video scripts. |
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Enhances security for sensitive student information. |
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Restoring Learning Materials |
Revitalizes and digitizes old or damaged educational content. |
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Provides on-demand, individualized academic support. |
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Enhanced Creativity/Critical Thinking |
Fosters innovative problem-solving and analytical skills through AI prompts. |
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Language Learning & Communication |
Facilitates practice and improves fluency through interactive AI agents. |
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Designs engaging, game-like educational experiences for motivation. |
Let’s explore the top 10 use cases of generative AI in education and how it’s driving change in classrooms and beyond.
1. Adaptive Content Generation for Personalized Learning
Generative AI excels at creating customized educational materials that match individual student needs, learning styles, and proficiency levels. The technology analyzes student performance data to generate appropriate content variations automatically.
Real-life Examples
For example, Speechify is a generative AI in education tool. It offers text-to-speech or speech-to-text generation on desktops or online.
Khan Academy’s Khanmigo: Built on GPT-4, Khanmigo acts as a tutor and teaching assistant. It helps students solve problems step by step, encourages critical thinking rather than just providing answers, and even assists teachers by drafting lesson plans.
Duolingo Max: This premium version of Duolingo integrates GPT-4 to create conversational practice scenarios and explain learners’ mistakes in natural language, making language acquisition more engaging and personalized.
Socratic by Google: While not fully generative, Socratic leverages AI to guide students through problem explanations, showing how adaptive AI tools are becoming a key learning aid.
These kinds of generative AI tools in education are especially useful for children with learning disabilities such as dyslexia or ADHD. When a child suffers from a lack of concentration due to such disorders, it can be harder to follow the course content via reading. However, with such tools, they can generate texts into speech notes when they are bored.
2. Course Design
Generative AI tools can help design and organize course materials, including syllabi, lesson plans, and assessments. They can also personalize course material based on students’ knowledge gaps, skills, and learning styles, such as practice problems or interactive exercises.
Generative AI can create simulations and virtual environments once paired with other technologies, such as virtual reality. Consequently, it offers more engagement and interactive courses, improving students’ learning experience.
For example, a generative AI in education could create a virtual laboratory setting where students can conduct experiments, observe the results, and make predictions based on their observations.
3. Content Creation for Courses
Generative AI can assist in creating new teaching materials, such as questions for quizzes and exercises, or explanations and summaries of concepts. This can be especially useful for teachers who need to create a large amount and a variety of content for their classes. By using AI, it is possible to create modified or brand-new content from the original content.
Furthermore, generative AI in education can facilitate generating additional materials to supplement the main course materials, such as:
- Reading lists
- Study guides
- Discussion questions
- Flashcards
- Summaries.
Additionally, AI can generate scripts for video lectures and podcasts, streamlining the creation of multimedia content for online courses. Image generation is another crucial capability of generative AI in education. Teachers may want to generate images with specific modifications that respond to particular course needs.
Real-life examples
Quizlet Q-Chat: Quizlet has integrated GPT-4 into its platform to create an AI tutor that interacts with students conversationally. It generates adaptive quizzes, explanations, and feedback in real time.
Canva Magic Write: Teachers increasingly use Canva’s generative AI tools to create presentation slides, lesson outlines, and visual learning aids quickly.
For example, NOLEJ offers an e-learning capsule that is AI-generated in only 3 minutes. This capsule offers an interactive video, glossary, practice exercises, and a summary for a target topic (see Figure 1 below).
Figure 1. An example of AI-generated course content.
More established companies are utilizing AI to create content that supports their primary products.
4. Data Privacy Protection for Analytical Models
One advantage of using generative AI in education to create training data sets is that it can help protect student privacy. A data breach or cyberattack can expose sensitive personal information belonging to school-age children, putting their privacy at risk
Using synthetic data, which is created by AI models that have learned from real-world data, can provide anonymity and protect students’ personal information. Synthetic datasets generated by AI models are valuable for training other algorithms, offering both effectiveness and enhanced data security.
For more on how generated synthetic data enables data privacy, you can check out these articles:
5. Restoring Old Learning Materials
Generative AI can enhance the quality of outdated or low-quality learning materials, including historical documents, photographs, and films. By utilizing AI to enhance the resolution of these materials, they can be brought up to modern standards and become more engaging for students accustomed to high-quality media.
These updates can also make it easier for students to read, analyze, and understand the materials, leading to a deeper understanding of the content and, ultimately, better learning outcomes.
Using a version of generative AI in education, Generative Adversarial Networks (GANs), it is possible to restore low-quality images and remove simple watermarks. In Figure 2 below, you can see a prototype for image restoration via GANs. Such image restoration can be adapted to educational materials. For example, in art and design schools, restoring old images would provide the detection of important details of artworks. Also in history classes and research, scanning and restoring old documents can be facilitated.
6. Virtual Tutoring
Generative AI can be used to create virtual tutoring environments, where students can interact with a virtual tutor and receive real-time feedback and support. This can be especially helpful for students who may not have access to in-person tutoring.
According to academic studies, private tutoring for children with severe reading difficulty improved their reading skills by 50% in a year. However, providing tutoring to all students can be a challenge. Generative AI in education can tackle this issue by creating virtual tutoring environments. In these environments, students can interact with a virtual tutor and receive feedback and support in real-time. This can be especially helpful for students who may not have access to in-person tutoring.
Real-life Example
For example, TutorAI is trying to implement this kind of use of generative AI in education. It offers an educational platform that generates interactive content on a variety of topics.
Another application of generative AI in education for teaching purposes is the implementation of chatbots for tutoring. According to Chatbot Life’s 2019 report, the education sector ranks as the third-largest industry using chatbot technology. Check out our conversational AI in education article and learn the top use cases.
Recently, ChatGPT from OpenAI has stormed the internet with its ability to engage in highly personalized conversations and provide definitive answers. It can answer course-related questions from various domains and even write essays on the target topic.
7- Assessment & Feedback
Grading and providing feedback are among the most time-consuming tasks for educators. Generative AI helps by analyzing student work essays, problem sets, or projects and generating constructive, personalized feedback. It can also evaluate grammar, coherence, and argument quality, offering students immediate insights into how they can improve.
Generative AI in assessment can:
- Grade short-answer or essay responses with explanations
- Provide real-time feedback on drafts before submission
- Highlight grammar, style, and clarity issues for non-native speakers
- Suggest improvements without replacing human grading judgment
Real-life examples
ChatGPT for essay reviews: Students worldwide already use GPT models to polish drafts, get readability suggestions, and receive grammar corrections before submission.
Turnitin Draft Coach: While traditionally known for plagiarism detection, Turnitin has developed AI tools to provide formative writing feedback, including grammar checks and structure suggestions.
Gradescope (by Turnitin): Uses AI to speed up grading workflows, especially for large classes, by identifying common errors and allowing teachers to apply feedback consistently.
8-Critical Thinking
AI tools inspire creativity by encouraging students to think outside the box. Generative AI in education can create engaging scenarios for problem-solving tasks or generate stories for writing exercises, helping students develop critical thinking skills. Tools like DALL·E and MidJourney enable students to visualize abstract ideas, transforming imagination into tangible creations that enhance the learning experience.
9-Language Learning and Communication
Generative AI bridges language gaps by offering real-time translation, grammar correction, and pronunciation guidance. This makes education more inclusive for non-native speakers. For instance, tools like Grammarly and DeepL assist students in improving their writing skills, while AI-powered speech tools help in mastering new languages through real-time conversation feedback.
10-Gamified Learning Experiences
To enhance engagement, generative AI is used to gamify education by creating interactive quizzes and simulations. Gamified learning fosters interest and helps students retain knowledge through playful yet informative activities. Platforms like Kahoot! Use AI to design games that align with curriculum goals, making learning both fun and effective.
11. Interactive Virtual Tutoring Systems
AI-powered virtual tutors provide 24/7 student support, offering personalized assistance that adapts to individual learning preferences and schedules. These systems combine natural language processing with domain expertise to deliver human-like tutoring experiences.
Virtual tutoring capabilities:
- Step-by-step problem guidance without providing direct answers
- Socratic questioning to encourage critical thinking
- Multi-modal explanations using text, images, and interactive elements
- Progress tracking with adaptive intervention strategies
Industry example: Carnegie Learning’s MATHia platform serves over 600,000 students globally, providing individualized math tutoring. The system identifies specific misconceptions and generates targeted exercises, resulting in 68% of students showing significant learning gains compared to traditional instruction methods.
Squirrel AI, deployed across 2,000+ learning centers in China, uses generative AI to create personalized tutoring sessions. Students using the platform demonstrated learning efficiency improvements of 5-10 times compared to traditional group instruction.
12.Curriculum Design and Course Material Development
Educators spend considerable time creating course materials, lesson plans, and supporting resources. Generative AI accelerates this process while maintaining quality and alignment with learning objectives.
Content creation applications:
- Syllabi generation based on learning outcomes and time constraints
- Interactive exercise creation with automatic answer key generation
- Multimedia content production including scripts for video lectures
- Cross-curricular connection identification and implementation
NOLEJ’s platform generates complete interactive learning modules within minutes, including video content, practice exercises, glossaries, and assessments.
Teachers using Canva’s AI writing tools create lesson materials faster than traditional methods, with consistent formatting and age-appropriate language automatically applied.
13. Accessibility Enhancement and Universal Design
Generative AI significantly improves educational accessibility by automatically creating content variants that accommodate different learning needs and disabilities.
Accessibility features:
- Automatic text-to-speech conversion with natural voice synthesis
- Visual content description generation for screen readers
- Simplified language versions for different reading levels
- Sign language animation generation for deaf and hard-of-hearing students
Microsoft’s Immersive Reader, integrated into Office 365 Education, uses AI to provide reading support for students with learning differences, serving over 23 million students globally with features like syllable breakdown and picture dictionaries.
Challenges of generative AI in education
Although generative AI has considerable potential to enhance educational practices, it also poses some potential challenges. These are as follows:
- Biases in educational materials
- False or inaccurate information
- Abuse of it for self-interest
- Unemployment risks for some teachers or other education professionals
For more on generative AI
To explore more about generative AI, you can check our other articles:
Discover the top generative AI tools from our detailed list, sorted by category:
Principal Analyst
Cem Dilmegani
Principal Analyst
Cem’s work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE and NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and resources that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem’s work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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Researched by
Sena Sezer
Industry Analyst
Sena is an industry analyst in AIMultiple. She completed her Bachelor’s from Bogazici University.
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