AI Use Cases and Applications

An AI use case refers to a specific problem, challenge, or scenario where artificial intelligence can be applied to add value, improve efficiency, or enable new capabilities. An AI application, on the other hand, is the actual system, product, or tool that implements AI techniques to address that use case in practice.

Because AI touches so many industries and functions, this topic cannot be captured fully within a single module. Instead, our goal here is to highlight a variety of use cases alongside different applications to help illustrate the broader landscape of how AI is being used today.

It is also important to note that AI use cases and applications are evolving at an extraordinary pace. What is considered cutting-edge today may become commonplace tomorrow. Therefore, this module is not meant to provide an exhaustive list, but rather to give you a sense of the wide spectrum of opportunities where AI is making an impact—from healthcare and finance to education, manufacturing, and creative industries.

By the end, you should have a clearer understanding of how use cases differ from applications, and how both play a role in shaping the ongoing growth of AI.

Big Question

How do AI use cases (the problems AI can solve) and AI applications (the tools that solve them) together shape the way industries, organizations, and individuals adopt and benefit from artificial intelligence?

To read:

The applications of AI span a remarkably wide spectrum—from everyday conveniences to highly specialized domains like engineering and healthcare. On one end, AI powers tools we interact with daily, such as recommendation engines, smart assistants, and productivity aids. On the other, it drives complex, mission-critical systems in areas such as fraud detection in finance, predictive maintenance in manufacturing, supply chain optimization in logistics, intelligent tutoring systems in education, and even drug discovery in healthcare.

A growing number of these applications now fall under the umbrella of Generative AI (GenAI). Unlike traditional AI systems that primarily analyze data or automate predefined tasks, GenAI refers to AI models capable of generating new content, ideas, or solutions—whether in the form of text, images, code, audio, or even molecular structures. In other words, GenAI does not just recognize patterns; it creates. This capability has opened up entirely new use cases, such as conversational agents, automated design tools, personalized learning platforms, and accelerated biomedical research.

For a deeper look into how GenAI is being applied across industries, here is a recommended read covering real-world use cases of generative AI and how they are transforming both work and daily life.

601 real-world gen AI use cases from the world's leading organizations

By the end of the reading, you will likely have come across the term “AI Agents.” An AI agent is a type of AI application designed to autonomously perceive its environment, make decisions, and take actions in pursuit of specific goals. These agents often leverage methods such as reinforcement learning, large language models (LLMs), or multi-agent systems to operate effectively.

It’s important to note that AI agents are not use cases themselves. Instead, they are a form of AI application that can be deployed across many different use cases—for example, in customer service, robotics, financial trading, or healthcare support. In this way, agents function as a flexible toolset that can bring intelligence, adaptability, and autonomy into diverse problem spaces.

For those interested in exploring this concept further, an excellent resource is the following book:

Poole, D. L., & Mackworth, A. K. (2023). Artificial Intelligence: Foundations of Computational Agents (3rd ed.). Cambridge: Cambridge University Press.

To read or watch:

OpenAI's Sam Altman talks ChatGPT, AI agents and superintelligence

With AI, anyone can be a coder now

How AI is unlocking the secrets of nature and the universe

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Exploring the Spectrum of AI Applications

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