Identify basic AI technology concepts

  • 3 minutes

AI is more than a set of algorithms—it’s a toolbox of capabilities that help people make better decisions, faster.

Foundations of AI

AI is a set of capabilities that help computers perform tasks that once required human judgment—understanding language, recognizing images, spotting patterns, making recommendations, and more. For business leaders, the point isn’t the algorithm; it’s where these capabilities deliver real outcomes: faster decisions, better customer experiences, and lower cost to serve.

What is generative AI?

Generative AI is a subset of AI that creates content—text, code, images, or video—and powers new productivity and creativity scenarios. AI value also comes from other capabilities:

  • Descriptive: search, classification, summarization
  • Predictive: forecasting, anomaly detection, scoring
  • Prescriptive: recommendations, optimization

Example: Use generative AI to draft follow-up questions after a meeting, create a slide image from a description, or explain a complex idea in plain language.

Diagram showing generative AI as a subset of AI.

Note

AI has powerful potential—and important responsibilities. Responsible AI means designing and using AI that's accountable, inclusive, reliable, safe, fair, transparent, secure, and respectful of privacy. For example, AI can create realistic media; using it to mislead people or violate privacy is harmful. Responsible AI practices help you unlock value while protecting customers, employees, and your brand.

Why this matters

Choose the right capability for the problem, start with high value use cases, and pair them with strong data and governance. Responsible AI practices keep value from becoming liability.

  • Speed and scale: AI can analyze large volumes of data and synthesize insights in minutes.
  • Productivity: Generative AI helps people produce drafts, summaries, and options faster.
  • Innovation: New, high value use cases—such as intelligent search, document understanding, and agentic workflows—are now practical.
  • Risk management: Governance and responsible AI keep value on the right side of risk.

Next, connect these foundations to how your organization can assess readiness and prioritize the right use cases.