62 terms and growing

AI and Tech Glossary

No jargon. No waffle. Just clear, practical definitions of the technology terms that matter to your business. Whether you are evaluating AI automation for the first time or comparing vendors, start here.

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Glossary at a Glance

Built from real project experience, not textbooks.

Frequently Asked Questions

Common questions about AI and automation terminology.

What is the difference between AI and automation?

Automation follows fixed rules to complete repetitive tasks, like sending an email when a form is submitted. AI adds intelligence on top, so the system can understand context, make decisions, and handle situations it has not seen before. Most modern business automation combines both: AI handles the thinking, automation handles the doing.

How much does AI automation cost for a small business?

It depends on complexity. Simple workflow automations start from around 500 pounds, AI chatbots range from 1,200 to 9,000 pounds, and voice agents typically cost between 1,800 and 7,000 pounds. Most small businesses see a return on investment within 3 to 6 months through saved time and reduced manual work.

What is GEO and how is it different from SEO?

SEO optimises your website to rank in traditional Google search results. GEO (Generative Engine Optimisation) optimises your content so that AI systems like ChatGPT, Perplexity, and Google AI Overviews cite your business in their responses. Both matter, but GEO is becoming increasingly important as more people use AI to find answers instead of scrolling through search results.

Do I need technical knowledge to use AI in my business?

No. Most AI tools designed for businesses require no coding. Platforms like n8n, Make, and Zapier let you build automations visually. For more advanced implementations like custom chatbots or voice agents, you would typically work with an agency that handles the technical side while you focus on your business goals.

What is RAG and why does it matter?

RAG (Retrieval Augmented Generation) is a technique that makes AI more accurate by giving it access to your specific data before it generates a response. Instead of relying only on its training data, the AI searches your documents, knowledge base, or database first. This means fewer hallucinations and answers grounded in your actual business information.