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Glossary

What is artificial intelligence? Explained

A plain definition of artificial intelligence for a business reader: what it is, the main families, examples, adoption data, limits and where to start.

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Definition

Artificial intelligence

Artificial intelligence is software that learns patterns from data so it can predict, classify, generate or decide. That is what is artificial intelligence in business terms: a tool that improves with examples instead of following only fixed rules.

In short: Software that learns from data to decide.

The main families of AI

  • Machine learning

    Learns patterns from examples.

  • Deep learning

    Many-layered networks for images and speech.

  • Generative AI

    Writes text and creates images.

  • AI agents

    Plan steps and use tools.

Artificial intelligence is an umbrella term. Several families sit under it, and each does a different job.

If you want to know what are ai technologies, start with these four. Most business tools combine more than one.

  • Machine learning: models that learn from examples, covered in machine learning
  • Deep learning: many-layered neural networks, used for images, speech and language
  • Generative AI: models that write text or create images, explained in generative AI
  • AI agents: software that plans steps and uses tools, see AI agent

Everyday and business examples

  1. 01

    Take in data

    Emails, invoices, calls or records.

  2. 02

    Find the pattern

    The model compares it with what it learned.

  3. 03

    Produce an output

    A prediction, a label or a draft.

  4. 04

    Person checks

    Someone reviews what matters.

Many people use AI without noticing. Spam filters, voice assistants, map routing and product suggestions all rely on it.

In short, what is ai tech to most people is the software behind these small daily helpers.

The OECD reports that more than one-third of individuals across its member countries used generative AI tools in 2025.

At work, AI reads invoices, answers common customer questions, scores leads and flags unusual transactions. See AI use cases for more.

These ai capabilities are narrow. Each system does one kind of job well, and a person still checks the results that matter.

How many companies use AI

  • Firms using AI

    About 18 percent at the end of 2025, by Census data.

  • Finance

    63 percent report work-related generative AI use.

  • Professional services

    62 percent report the same use.

  • High performers

    Only 6 percent see 5 percent or more earnings impact.

Adoption numbers differ by survey, so always check who measured what and when.

A Federal Reserve note, drawing on Census Bureau business data, puts firm-level adoption at about 18 percent at the end of 2025.

Surveys of workers show much higher figures, because they count individuals using chat tools, not whole firms.

Sector matters too. Per the same note, financial services leads on work-related generative AI at 63 percent, with professional services at 62 percent.

Results are uneven. McKinsey found that 37 percent of respondents say AI added to their organization's earnings, and only 6 percent are high performers who credit AI with 5 percent or more of earnings.

Limits and how to start

Good first targets

  • Repetitive, high-volume tasks
  • Clear inputs and clean data
  • Results you can measure

Poor first targets

  • Vague goals with no owner
  • Messy or missing data
  • Decisions with no human review

AI makes mistakes, can reflect gaps in its data and needs oversight. Read about hallucination and AI governance before you rely on it.

People and data are the usual blockers. A PEX report lists missing in-house expertise (49 percent) among the obstacles.

To start, pick one repetitive process, measure what it costs today and test a small fix. Our AI for business guide walks through the steps.

Our data

What AI answers when buyers ask

We asked ChatGPT, Gemini and Perplexity 10 buyer questions about AI consulting. They named 95 companies, and 81% appeared in only one of the three.

CriterionChatGPTGeminiPerplexity
Companies named342560
Sites cited mostslalom.com (4 of 10)effectivesoft.com (6 of 10)phosailabs.com and wiserbrand.com (3 of 10)

Nexum measurement, October 20, 2026, via DataForSEO: 10 buyer questions to each AI, US English, 30 answers in total. 6 companies appeared in all three. Google showed an AI Overview for 7 of the 10 questions.

FAQ

Artificial intelligence questions

  • Software that learns from data and then makes predictions, sorts items, writes content or suggests decisions. It works through patterns it picked up from examples, not through a fixed list of rules.

  • Key features artificial intelligence tools share are learning from data, spotting patterns, handling language or images, and improving with feedback. Each tool has its own narrow set of skills.

  • AI changes tasks more than whole jobs. It takes over repetitive steps, while people keep judgment, relationships and final approval. The longer answer depends on the role.

  • Current systems can state wrong answers with confidence, carry bias from their data and struggle outside the task they were built for. People should review anything high-stakes.

  • Machine learning is one family inside AI, where models learn from examples. AI is the wider field. The AI vs machine learning page compares the two.

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