Artificial intelligence (AI) is a branch of computer science focused on building computers and machines that can perform tasks that typically require human intelligence, such as understanding language, recognizing patterns, making decisions, and solving problems.
At its core, AI works by training models on large datasets so they can learn from patterns rather than following explicitly programmed rules. Most modern AI systems are built on machine learning, and more specifically, deep learning, which uses neural networks to process complex data and make predictions.
AI systems are generally categorized by their level of capability.
- Weak AI also called narrow AI, describes systems designed to perform a specific task.
- Artificial general intelligence (AGI) refers to a theoretical form of AI that would match or surpass human intelligence across a broad range of tasks.
- Artificial superintelligence (ASI)—currently inexistent—describes AI that would exceed human intelligence in every domain.
The most common and accessible form of AI today is generative AI, which can produce text, images, video, and other content in response to prompts.
Built on top of generative AI is agentic AI, where AI agents autonomously plan and execute multi-step tasks to achieve broader goals.
AI comes with many benefits but also has real risks, such as bias from training data, lack of transparency in decision-making, and concerns around privacy and ethics, all of which have made AI governance an increasingly important consideration.