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Artificial Intelligence (AI)

Artificial intelligence is a broad category of computer systems designed to perform tasks involving capabilities such as prediction, classification, perception, language processing, generation, or planning.

Artificial intelligence, or AI, is a broad category of computer systems designed to perform tasks that involve capabilities such as prediction, classification, perception, language processing, generation, planning, or decision support.

AI includes many technologies beyond chatbots and Large Language Models.

What AI Can Include

AI systems can be built for tasks such as:

  • Image recognition
  • Recommendation
  • Forecasting
  • Classification
  • Speech recognition
  • Natural-language processing
  • Content generation
  • Fraud detection
  • Search
  • Planning
  • Robotics

Generative AI is one subset of this broader category.

AI vs. Generative AI

Artificial intelligence is the broader field.

**Generative AI** specifically refers to models designed to create new outputs such as text, images, audio, video, or code.

For example:

A model predicting whether a transaction is fraudulent → AI

but not necessarily:

Generative AI.

AI Does Not Necessarily Mean Autonomous

An AI system may perform one very narrow task.

For example:

Support message
      ↓
AI classifies topic
      ↓
Traditional workflow routes ticket

The AI is not independently operating the customer-support system.

It is performing one classification step inside a larger Workflow Automation.

Why It Matters

Using “AI” as a catch-all term can hide important architectural differences.

A recommendation system, an LLM, and an AI Agent may all involve AI while having very different:

  • Capabilities
  • Risks
  • Data requirements
  • Costs
  • Evaluation methods
  • Maintenance needs

Understanding the actual system is more useful than knowing it contains AI.

Risk Management

AI systems should be evaluated according to their actual use, consequences, users, and environment.

NIST's cross-sector AI Risk Management Framework is designed to help organizations incorporate trustworthiness considerations into how AI systems are designed, developed, deployed, and evaluated. NIST AI Risk Management Framework resources