Artificial Intelligence (AI)

Full definition

AI covers a wide spectrum of techniques, from rule-based expert systems and search algorithms to modern statistical machine learning and deep neural networks. Today, the term most often refers to systems built on machine learning — especially large neural networks trained on massive datasets. The OECD defines an AI system as "a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments."

Why it matters

AI is now a board-level technology decision rather than a research curiosity. According to McKinsey survey data reported in the Stanford HAI AI Index 2025, 78% of organizations used AI in at least one business function in 2024, up from 55% the year before. Choosing where AI sits in a company's strategy now drives capital allocation, risk posture, and competitive position.

Example

A retailer uses AI to forecast demand at the SKU-store-day level, recommend products to logged-in shoppers, and route customer-service tickets — all from the same underlying machine-learning stack.

Frequently asked questions

Next steps

• Get a free workflow map →We map one of your workflows and give you a written verdict: software, a process change or AI. No obligation.
• AI consulting cost guide →Hourly rates and project budgets by firm tier, from independents to the Big Four.

Related terms

• Machine Learning (ML)
  Machine Learning (ML) is the subfield of AI in which algorithms improve their performance on a task by learning statistical patterns from data, rather than following rules a human wrote by hand.
• Deep Learning
  Deep Learning is a class of machine learning that uses neural networks with many layers ("deep" architectures) to learn hierarchical representations directly from raw data such as images, audio, or text.
• Large Language Model (LLM)
  A Large Language Model (LLM) is a deep neural network — almost always a transformer — trained on hundreds of billions to trillions of words to predict the next token, and to generate, summarize, translate, or reason over text.
• Generative AI
  Generative AI is a class of AI systems that produce new content — text, images, code, audio, or video — by learning the distribution of their training data and sampling from it, rather than classifying or predicting from existing inputs.

More fundamentals terms

• Neural Network
  A neural network is a machine-learning model composed of layers of interconnected nodes ("neurons") whose numerical weights are adjusted during training so the network maps inputs to desired outputs.