Understanding AI: a complete guide

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Meta

Type: knowledge_hub

Language: en-GB

Last updated: 2026-10-01

Retrieval summary

What: An introductory guide to artificial intelligence, explaining the differences between AI models, applications, assistants, agents, APIs and retrieval, and how they relate to websites and digital services.

Who

Organisation: Feel Created

Relevant for

Problems solved

Article

Type: Knowledge Hub guide

Primary topic: Understanding AI: A Complete Guide

Intent: An introductory guide to artificial intelligence, explaining the differences between AI models, applications, assistants, agents, APIs and retrieval, and how they relate to websites and digital services.

Audience

Topics

Content focus

Canonical claims

Item 1

Claim: An AI model does not automatically know everything about an organisation; it needs access to current information to answer organisation-specific questions.

Evidence type: page_content

Evidence strength: medium

Source section: what-information-does-an-ai-enabled-website-rely-on

Item 2

Claim: AI systems can retrieve relevant information from approved sources when a question is asked, rather than relying only on the model's training knowledge.

Evidence type: page_content

Evidence strength: medium

Source section: how-does-an-ai-website-feature-access-approved-information

Item 3

Claim: AI is most useful where it helps interpret information, support a decision or complete a task that would otherwise be difficult or time-consuming.

Evidence type: page_content

Evidence strength: medium

Source section: what-is-an-ai-model

Item 4

Claim: AI can get things wrong, so organisations need clear safeguards around security, privacy, accountability and human judgement.

Evidence type: page_content

Evidence strength: medium

Source section: what-sits-behind-an-ai-enabled-website

Item 5

Claim: AI allows computer systems to process information and carry out tasks that usually require human input.

Evidence type: page_content

Evidence strength: medium

Source section: what-is-artificial-intelligence

Item 6

Claim: Retrieval-augmented generation allows source information to be updated without retraining the model.

Evidence type: page_content

Evidence strength: medium

Source section: how-does-an-ai-website-feature-access-approved-information

Item 7

Claim: Structured content stores information in defined, reusable parts, distinct from structured data.

Evidence type: page_content

Evidence strength: medium

Source section: how-does-structured-content-support-ai-enabled-websites

Item 8

Claim: AI agents have more freedom to choose steps towards a goal compared to conventional assistants.

Evidence type: page_content

Evidence strength: medium

Source section: overview

Common questions

Item 1

Question: What is the difference between a website assistant and an AI agent?

Answer: A website assistant usually works through a set process, while an AI agent has more freedom to choose steps towards a goal using approved information or tools.

Item 2

Question: How does structured content differ from structured data?

Answer: Structured content organises information into defined, reusable parts, while structured data adds machine-readable labels to published webpage information to help external systems understand it.

Item 3

Question: Where can AI improve a website or digital service?

Answer: AI is most useful where it helps interpret information, support a decision or complete a task that would otherwise be difficult or time-consuming. It should support a genuine need rather than being added simply because it is available.

Item 4

Question: What is retrieval-augmented generation (RAG)?

Answer: RAG is a method where relevant information is found first, then used by a model to produce a response, allowing source information to be updated without retraining the model.

Item 5

Question: How does AI affect the future of websites?

Answer: AI is unlikely to remove the need for websites. It is already changing how people interact with them, how information is reused and what digital services can do. Traditional webpages, navigation and search will continue to matter.

Item 6

Question: How does AI become part of a website?

Answer: Most people interact with a website feature or application built around an AI model, which adds the interface, information and controls that make the model usable.

Item 7

Question: What is artificial intelligence?

Answer: AI allows computer systems to process information and carry out tasks that usually require human input, such as recognising patterns, understanding language, making predictions, creating content or recommending what should happen next.

Services

Digital planning & research

Relationship: supporting

Url: /services/digital-planning-research/

AI features & integrations

Relationship: primary

Url: /services/ai-features-integrations/

Information architecture

Relationship: supporting

Url: /services/information-architecture/

Content architecture

Relationship: supporting

Url: /services/content-architecture/

Sections

Overview

Content

Item 1

Text: Artificial intelligence is becoming part of everyday digital services, but the terminology can make it seem more complicated than it is. Models, applications, assistants, agents, APIs and retrieval all describe different parts of an AI system. Understanding those differences helps organisations judge where AI could improve a website or digital service. This Topic Hub explains the main concepts, how they connect and what they mean for modern websites and digital platforms.

What is artificial intelligence?

Items

Content

Item 1

Text: Artificial intelligence allows computer systems to process information and carry out tasks that usually require human input. These tasks might include recognising patterns, understanding language, making predictions, creating content or recommending what should happen next. Generative AI has brought the subject into everyday conversation, but it is only one part of a much wider field. Artificial intelligence has developed through several different approaches over many years. Some earlier systems were built around instructions written in advance. Newer systems are often trained using large collections of examples, allowing them to recognise patterns and produce results without every decision being set out as a fixed rule. Deep learning has helped drive progress in areas such as image recognition, speech tools and large language models. Generative AI uses these approaches to create new content, including text, images, audio and software. Tools such as ChatGPT have made this type of AI widely accessible, but organisations also use AI for forecasting, recommendations, fraud detection, scientific analysis and many other specialist tasks. These technologies are beginning to appear on websites and in digital services, too. They may support conversational experiences, answer common questions, summarise information or help people complete more complicated tasks. Understanding the wider field helps organisations avoid treating every AI feature as though it works in the same way. These areas are related, but the diagram is a simplified guide rather than a complete map of every form of AI.

AI Models, AI Systems and AI Applications Explained

Content

Item 1

Text: Learn the difference between AI models, AI applications and AI systems, and discover why information... 14 minutes read Read the guide

What Is an AI Model?

Content

Item 1

Text: More information coming soon Coming soon

Item 2

Text: An AI model is a system trained to recognise patterns and produce a particular type of result. Different models may generate language, identify objects in an image, make predictions or classify information. A model can provide some of the intelligence behind a website feature, but it is not usually the complete service that a visitor or editor uses. Models learn from examples provided during training. A language model, for example, learns patterns from large collections of text. This helps it interpret prompts and generate responses. Different models are created for different purposes. Some can handle a wide range of tasks, while others are better suited to a particular subject or activity. A single model may support several parts of a task. An AI application can also use different models where each one offers the best balance of performance, speed and cost. That difference affects where information is processed and how much control the organisation has over the service. For a website project, these choices influence how quickly an AI feature responds, what it costs to run, where information is processed and how much control the organisation retains. The newest or largest model is not automatically the best choice. What matters is whether it suits the task, the information involved and the way the service needs to operate.

Language models

Parent id: what-is-an-ai-model

Parent heading: What Is an AI Model?

Content

Item 1

Text: Can support website assistants, conversational search and content-related tasks.

Image models

Parent id: what-is-an-ai-model

Parent heading: What Is an AI Model?

Content

Item 1

Text: Can recognise, classify or create imagery.

Prediction models

Parent id: what-is-an-ai-model

Parent heading: What Is an AI Model?

Content

Item 1

Text: Use patterns in data to estimate likely outcomes.

Specialist models

Parent id: what-is-an-ai-model

Parent heading: What Is an AI Model?

Content

Item 1

Text: Are designed or adapted for a particular subject or service.

How does AI become part of a website?

Key points

Items

Content

Item 1

Text: Most people do not interact directly with an AI model. They use a website feature or application built around it. The model provides some of the capability. The website or application adds the interface, information and controls that make it usable. An AI model can interpret an instruction and generate an output, but it does not provide a complete website experience on its own. The surrounding application may add a search box, conversation screen, account controls, document uploads, saved history or connections to other services. For website features, the possibilities go far beyond basic chatbots. AI could help interpret what someone needs, make sense of information or recommend what should happen next. It might guide a visitor to the right information, help editors understand complex data, explain technical recommendations or support tasks that would previously have required several different tools. This is why choosing an AI model and designing an AI-enabled website feature are separate decisions. These areas are related, but the diagram is a simplified guide rather than a complete map of every form of AI.

Organising Information for AI

Content

Item 1

Text: More information coming soon Coming soon

What sits behind an AI-enabled website?

Content

Item 1

Text: An AI feature may depend on approved information, connected software, security controls, business processes and people who review important results. Together, these parts form an AI system. The website may be the part people see, but it is only one part of the complete service. A website assistant might answer questions, help someone find the right service or support part of an application process. To do that, it may need access to approved information, connections to existing systems and rules that determine what it can and cannot do. It may also need monitoring, approval processes and a clear route for people to get help when the system cannot provide a suitable response. Looking at the complete system helps organisations avoid focusing too heavily on the visible AI feature. A chatbot is one of the best-known examples, but AI can support much more across a website or digital service. It can help people find what they need, interpret complex information, support editors, analyse data and connect tasks across different systems. Making those features useful depends on more than the model. The information, integrations, controls and people around them determine what they can do and how well they work.

Model

Parent id: what-sits-behind-an-ai-enabled-website

Parent heading: What sits behind an AI-enabled website?

Content

Item 1

Text: Interprets requests and produces an output.

Website or application

Parent id: what-sits-behind-an-ai-enabled-website

Parent heading: What sits behind an AI-enabled website?

Content

Item 1

Text: This is where someone interacts with the service.

Information

Parent id: what-sits-behind-an-ai-enabled-website

Parent heading: What sits behind an AI-enabled website?

Content

Item 1

Text: The system relies on content, guidance or records to respond.

Controls

Parent id: what-sits-behind-an-ai-enabled-website

Parent heading: What sits behind an AI-enabled website?

Content

Item 1

Text: Limits are needed around what it can see, use and change.

People

Parent id: what-sits-behind-an-ai-enabled-website

Parent heading: What sits behind an AI-enabled website?

Content

Item 1

Text: Set the rules, monitor how the system performs and review results where judgement or responsibility matters.

What Makes Organisational Knowledge AI-Ready?

Content

Item 1

Text: More information coming soon Coming soon

What information does an AI-enabled website rely on?

Items

Content

Item 1

Text: An AI model does not automatically know everything about an organisation. It may contain broad knowledge from its training, but it will not reliably know current services, policies, records or internal decisions unless that information is made available to it. For website projects, the key question is which information the AI feature should be allowed to use. A general-purpose model may be able to explain common ideas or respond to questions about widely discussed subjects. Questions about a particular organisation are different. The answer may depend on a recently updated service page, an internal procedure, a current record or information held within another platform. Some of that information may already be published on the website. Other sources may include documents, databases, guidance or internal systems. The organisation needs to decide where the information comes from, who maintains it and whether the AI feature should be able to access it. A public website assistant may need approved service information, but it should not automatically have access to confidential records or unrestricted internal material.

How does an AI website feature access approved information?

Items

Content

Item 1

Text: AI systems do not always depend only on what a model learned during training. They can retrieve relevant information from approved sources when someone asks a question or starts a task. For websites, this can help an AI feature use current, organisation-specific information rather than relying only on the model’s general knowledge. Retrieval begins when the system searches for information related to the question or task. A website assistant might search approved service pages, guidance documents or a managed knowledge base. Another feature could retrieve content, records or technical data before making a recommendation. The system does not have to treat every source in the same way. Content can be organised, labelled and given different levels of importance so that the most relevant information is more likely to be used for a particular subject, audience or task. A developer can put the technical rules in place that determine where the system searches, how results are ranked and which sources should take priority. This makes the organisation’s information easier for the AI feature to use in a controlled and purposeful way. The relevant material is then supplied to the model as part of the request. The model can use it to interpret the information, produce a response or help determine what should happen next. One common approach is called retrieval-augmented generation, usually shortened to RAG. The term sounds technical, but the idea is straightforward: find the relevant information first, then use the model to work with it. Retrieval allows the source information to be updated without retraining the model. This makes it easier for a website feature to use current content, guidance or records. It does not guarantee that every result will be correct. The system still needs suitable sources, clear limits and a way for people to check important results. This is different from AI Search and website visibility. Retrieval within an organisation’s own service uses information that has deliberately been made available to that system. AI Search concerns how external platforms discover, interpret and present information from across the web.

How does structured content support AI-enabled websites?

Content

Item 1

Text: Structured content organises information into defined, reusable parts instead of storing everything as complete webpages or documents. This is not the same as organisational knowledge, retrieval or structured data. For modern websites, it can make the same information easier to reuse across pages, applications and AI-enabled services. A traditional webpage may combine a title, description, date, location and contact details into one large block of content. A structured approach stores those parts separately and gives each one a defined purpose. This can make it easier to update information once and reuse it consistently across websites, apps, search features and AI-enabled services. For example, an event’s date, location and booking details can be stored as separate fields. A webpage may present all of them together, while an AI assistant may retrieve only the information needed to answer a particular question. Structured content does not automatically make information accurate, well written or useful. Organisations still need clear ownership and sensible maintenance. Structured data is different. It adds machine-readable labels to published webpage information to help external systems understand what that information represents.

Organisational knowledge

Parent id: how-does-structured-content-support-ai-enabled-websites

Parent heading: How does structured content support AI-enabled websites?

Content

Item 1

Text: The information an organisation holds and uses.

Structured content

Parent id: how-does-structured-content-support-ai-enabled-websites

Parent heading: How does structured content support AI-enabled websites?

Content

Item 1

Text: A way of organising information into defined and reusable parts.

Structured data

Parent id: how-does-structured-content-support-ai-enabled-websites

Parent heading: How does structured content support AI-enabled websites?

Content

Item 1

Text: Machine-readable labels that describe what published webpage information represents.

Retrieval

Parent id: how-does-structured-content-support-ai-enabled-websites

Parent heading: How does structured content support AI-enabled websites?

Content

Item 1

Text: Finds the most relevant approved information for a particular question or task.

Entities

Retrieval-augmented generation

Artificial intelligence

Structured content

Machine learning

Human oversight

Deep learning

Generative AI

AI assistants

AI agents

AI model

API

Concept relationships

Item 1

Subject: AI system

Predicate: includes

Object: approved information, connected software, security controls, business processes, and people

Item 2

Subject: AI model

Predicate: does not automatically know

Object: organisation-specific information

Item 3

Subject: Retrieval-augmented generation

Predicate: uses

Object: approved information sources

Item 4

Subject: Structured content

Predicate: enables

Object: reuse across AI-enabled services

Item 5

Subject: AI feature

Predicate: can retrieve information from

Object: approved sources

Item 6

Subject: Deep learning

Predicate: powers

Object: Many modern generative AI systems

Item 7

Subject: Artificial intelligence

Predicate: includes

Object: Machine learning

Item 8

Subject: APIs

Predicate: connect

Object: AI features with business systems

Item 9

Subject: AI agents

Predicate: differ from

Object: website assistants

Item 10

Subject: AI-enabled website

Predicate: is part of

Object: AI system

Implementation patterns

Item 1

Pattern: Use AI for interpretation, summarisation or guided assistance

Description: Implement AI where it genuinely improves the service by helping users interpret information, summarise content, or receive guided assistance.

Benefit: Enhances user experience without overcomplicating the service.

Item 2

Pattern: Define what an AI agent can access and when human approval is needed

Description: When giving an AI agent freedom to choose and carry out actions, clearly define its access, allowed actions, and points where a person must review or approve.

Benefit: Maintains control and accountability.

Item 3

Pattern: Retrieval from approved sources

Description: The system searches approved service pages, guidance documents, or a managed knowledge base at query time to supply relevant information to the model.

Benefit: Enables use of current, organisation-specific information in a controlled way.

Item 4

Pattern: Content prioritisation

Description: Content is organised, labelled, and given different levels of importance so that the most relevant information is more likely to be used.

Benefit: Improves relevance and control over AI responses.

Item 5

Pattern: Retrieval-augmented generation workflow

Description: Find relevant approved information first, then use the model to interpret, recommend or respond.

Benefit: Allows source information to be updated without retraining the model

Item 6

Pattern: API integration for AI features

Description: Use APIs to request information or actions from other systems, such as checking appointment availability.

Benefit: Allows AI features to interact with live records and services

Item 7

Pattern: Using different models for different parts of a task

Description: An AI application can use different models where each one offers the best balance of performance, speed and cost.

Benefit: Optimises performance and cost

Item 8

Pattern: Structured content storage

Description: Store information parts separately with defined purposes, such as event date, location and booking details.

Benefit: Enables reuse across webpages, apps and AI assistants

Practical guidance

Item 1

Guidance: Consider the task, the information involved and the way the service needs to operate when choosing an AI model, rather than assuming the newest or largest is best.

Importance: high

Item 2

Guidance: Understand the differences between AI models, applications, assistants, agents, APIs and retrieval to judge where AI could improve a website or digital service.

Importance: high

Item 3

Guidance: Before choosing an AI feature, understand what needs to be achieved, where the existing website or process falls short, and what kind of support would make a meaningful difference.

Importance: high

Item 4

Guidance: Organise and label content so that the most relevant information is more likely to be used for a particular subject, audience, or task.

Importance: medium

Item 5

Guidance: Implement monitoring, approval processes, and a clear route for users to get help when the system cannot provide a suitable response.

Importance: medium

Item 6

Guidance: Decide which information the AI feature should be allowed to use, and ensure it does not automatically access confidential records.

Importance: high

Item 7

Guidance: Use RAG to keep AI features current without retraining models, but ensure sources are suitable and results are reviewable.

Importance: high

Item 8

Guidance: Adopt structured content to enable consistent reuse across websites, apps and AI services, but maintain clear ownership.

Importance: medium

Risk areas

Item 1

Risk: AI feature may access confidential or unrestricted internal material if not properly controlled

Impact: Data breach or unauthorised disclosure

Item 2

Risk: Overemphasis on the visible AI feature without considering the complete system

Impact: Underperformance or failure to meet user needs

Item 3

Risk: Choosing the newest or largest model without considering suitability

Impact: May result in poor performance, higher costs or lack of control

Item 4

Risk: Treating every AI feature as though it works in the same way

Impact: May lead to inappropriate use or unrealistic expectations

Item 5

Risk: API connections may allow actions that change records

Impact: Connections must be limited, secure and appropriate to the task

Item 6

Risk: Structured content does not ensure accuracy

Impact: Needs clear ownership and sensible maintenance

Item 7

Risk: RAG does not guarantee correct results

Impact: Requires suitable sources, clear limits and human review of important results

Item 8

Risk: Adding AI without a genuine need

Impact: May not improve the service and could complicate the user experience.

Common misconceptions

Item 1

Misconception: AI Search is the same as retrieval within an organisation's service

Clarification: Retrieval within an organisation uses deliberately made available information, while AI Search concerns external platforms discovering and presenting web information.

Item 2

Misconception: Generative AI represents all forms of artificial intelligence

Clarification: Generative AI is only one part of a much wider field, which also includes forecasting, recommendations, fraud detection and scientific analysis.

Item 3

Misconception: An AI model provides a complete website experience on its own

Clarification: The model provides capability, but the website or application adds the interface, information and controls that make it usable.

Item 4

Misconception: Structured content automatically makes information accurate

Clarification: Structured content does not automatically make information accurate, well written or useful; organisations still need clear ownership and maintenance.

Item 5

Misconception: Every website problem needs artificial intelligence.

Clarification: Sometimes people need clearer information, a simpler journey or better-designed software. AI is only useful when it adds something a conventional improvement cannot.

Item 6

Misconception: An AI model knows everything about an organisation

Clarification: Models have broad training knowledge but need access to current, organisation-specific information to answer accurately.

Item 7

Misconception: AI will remove the need for websites.

Clarification: Websites will continue to provide official information and access to services, but some interactions may become more conversational or task-focused.

Item 8

Misconception: The website is the entire AI service

Clarification: The website is only one part; the complete system includes information, integrations, controls, and people.

Technical context

Model types

Ai components

Retrieval mechanism: Searches approved sources at query time, ranks results, and supplies relevant material to the model as part of the request.

Content organisation: Content can be organised, labelled, and given different levels of importance to influence retrieval.

System components: Model, website/application, information, controls, and people.

Rag: Retrieval-augmented generation: find relevant information first, then use the model to work with it.

Structured content: Organises information into defined, reusable parts, distinct from structured data.

Api: Application programming interface: agreed way for software to request information or actions.

Ai agent: Works towards a goal across several steps, with more freedom than a conventional assistant.

Reasoning paths

Item 1

User problem: Overemphasis on visible AI features without considering the complete system

Why this guide is relevant: This page explains the topic and gives practical points to consider.

Evidence refs

Relevant sections

Item 2

User problem: Choosing the newest or largest model without considering suitability

Why this guide is relevant: This page explains the topic and gives practical points to consider.

Evidence refs

Relevant sections

Item 3

User problem: Treating every AI feature as though it works the same way

Why this guide is relevant: This page explains the topic and gives practical points to consider.

Relevant sections

Item 4

User problem: Updating AI source information without retraining models

Why this guide is relevant: This page explains the topic and gives practical points to consider.

Evidence refs

Relevant sections

Knowledge hub

Page type: guide

Learning intent: An introductory guide to artificial intelligence, explaining the differences between AI models, applications, assistants, agents, APIs and retrieval, and how they relate to websites and digital services.

Topic hierarchy

Primary: Understanding AI: A Complete Guide

Supporting

Evergreen use: true

Content profile

Content type: Knowledge Hub guide

Primary topic: Understanding AI: A Complete Guide

Supporting topics

Primary audience

Retrieval topics

Organisation

Name: Feel Created

Type: Digital partner specialising in websites and digital platforms

Url: https://www.feelcreated.com/

Service model: We work as an extension of our clients' teams, combining strategy, UX, accessibility, content design, WordPress development and ongoing support to create digital platforms that help organisations communicate more clearly, work more efficiently and grow sustainably.