{ "meta": { "type": "knowledge_hub", "language": "en-GB", "last_updated": "2026-10-01", "ai_endpoint": "/knowledge-hub/ai-models-ai-systems-and-ai-applications-explained/ai.json", "source_page": "/knowledge-hub/ai-models-ai-systems-and-ai-applications-explained/" }, "retrieval_summary": { "what": "This guide explains the difference between AI models, AI systems and AI applications, and why understanding these distinctions matters for organisations considering AI.", "who": { "organisation": "Feel Created" }, "relevant_for": [ "Digital and web managers", "Website owners", "Marketing and communications teams", "Organisations exploring artificial intelligence", "Teams considering AI features or integrations", "People responsible for digital strategy and technology decisions" ], "problems_solved": [ "People use AI product names interchangeably, causing confusion", "Organisations focus on choosing a model rather than considering the whole system", "AI models are limited on their own and need additional components", "Comparing AI products is difficult because they differ in models, information, and tools.", "Organisations may think they are choosing between AI applications when the real differences lie in the underlying models.", "Off-the-shelf AI applications may not provide access to organisation-specific information.", "Poor information quality undermining AI outcomes", "Outdated or duplicated content affecting AI reliability" ] }, "page": { "title": "AI models, AI systems and AI applications explained", "slug": "ai-models-ai-systems-and-ai-applications-explained", "url": "/knowledge-hub/ai-models-ai-systems-and-ai-applications-explained/", "canonical_url": "https://www.feelcreated.com/knowledge-hub/ai-models-ai-systems-and-ai-applications-explained/", "status": "published" }, "article": { "type": "Knowledge Hub guide", "primary_topic": "The difference between AI models, AI systems and AI applications and how they relate to each other in practical AI use.", "intent": "This guide explains the difference between AI models, AI systems and AI applications, and why understanding these distinctions matters for organisations considering AI.", "audience": [ "Digital and web managers", "Website owners", "Marketing and communications teams", "Organisations exploring artificial intelligence", "Teams considering AI features or integrations", "People responsible for digital strategy and technology decisions" ] }, "topics": [ "The difference between AI models, AI systems and AI applications and how they relate to each other in practical AI use.", "AI models", "AI systems", "AI applications", "AI terminology", "AI application definition", "AI application examples", "Custom AI applications", "AI application comparison", "Information quality" ], "content_focus": [ "Definitions of AI models, AI systems and AI applications", "Importance of information in AI outcomes", "Practical considerations for organisations adopting AI", "Definition of AI applications", "Examples of AI applications", "Custom AI application development", "Comparison of AI applications", "Components of an AI system", "Role of information quality in AI effectiveness", "Why AI projects often become information projects" ], "canonical_claims": [ { "claim": "The quality of information available to the system, how well it is organised and how effectively it reflects the organisation often has as much influence on the value AI can deliver as the model itself.", "evidence_type": "page_content", "evidence_strength": "medium", "source_section": "overview", "id": "claim-001" }, { "claim": "Two applications built on the same AI model may behave differently due to different tools, information, and interaction methods.", "evidence_type": "page_content", "evidence_strength": "medium", "source_section": "what-is-an-ai-application", "id": "claim-002" }, { "claim": "The quality of an AI system is determined by more than the model powering it; the information it can use is equally important.", "evidence_type": "page_content", "evidence_strength": "medium", "source_section": "why-information-matters-as-much-as-the-ai", "id": "claim-003" }, { "claim": "AI can only work with the information it receives, so inaccurate documentation or outdated policies will affect AI responses.", "evidence_type": "page_content", "evidence_strength": "medium", "source_section": "ai-can-only-work-with-the-information-it-receives", "id": "claim-004" }, { "claim": "Clear, accurate and well-connected information gives AI systems a much stronger foundation for producing useful responses.", "evidence_type": "page_content", "evidence_strength": "medium", "source_section": "ai-can-only-work-with-the-information-it-receives", "id": "claim-005" }, { "claim": "Organisations with well-maintained information and clear content ownership are better positioned to benefit from AI.", "evidence_type": "page_content", "evidence_strength": "medium", "source_section": "ai-can-only-work-with-the-information-it-receives", "id": "claim-006" }, { "claim": "Organisations are increasingly building their own AI applications tailored to their knowledge and processes.", "evidence_type": "page_content", "evidence_strength": "medium", "source_section": "organisations-arent-limited-to-off-the-shelf-ai-applications", "id": "claim-007" }, { "claim": "AI applications combine a model with software interfaces and tools to make intelligence useful.", "evidence_type": "page_content", "evidence_strength": "medium", "source_section": "what-is-an-ai-application", "id": "claim-008" } ], "common_questions": [ { "question": "What questions should organisations ask instead of 'Which AI model should we choose?'", "answer": "Organisations should ask: What problem are we trying to solve? What information is available? Can it be trusted? How do people need to use it?" }, { "question": "What is the difference between an AI model, an AI system and an AI application?", "answer": "An AI model provides the underlying intelligence, an AI application makes that intelligence accessible, and an AI system combines models with information, technology and business processes to solve real-world problems." }, { "question": "Why do organisations using the same AI model achieve different results?", "answer": "Because the quality of information available to the system, how well it is organised and how effectively it reflects the organisation often has as much influence on the value AI can deliver as the model itself." }, { "question": "Why do AI projects often become information projects?", "answer": "Because AI depends on reliable information to produce reliable answers, discussions about AI often lead to discussions about improving information quality and management." }, { "question": "Can organisations build their own AI applications?", "answer": "Yes, organisations can build custom AI applications that access their own knowledge, services, and processes, complementing public AI tools by providing access to information only the organisation can offer." }, { "question": "Why does information quality matter for AI?", "answer": "AI can only work with the information it receives. If the information is inaccurate, outdated, or poorly organised, AI responses will reflect those problems." }, { "question": "Why is comparing AI products difficult?", "answer": "Comparing AI products is difficult because they may use different models, offer different information and tools, and have different interaction methods, so you are often comparing more than just the underlying AI model." } ], "services": [ { "name": "Website architecture & integrations", "relationship": "technical", "url": "/services/website-architecture-integrations/" }, { "name": "Digital planning & research", "relationship": "supporting", "url": "/services/digital-planning-research/" }, { "name": "AI features & integrations", "relationship": "primary", "url": "/services/ai-features-integrations/" } ], "sections": [ { "id": "overview", "heading": "Overview", "type": "introduction", "content": [ { "type": "paragraph", "text": "Artificial intelligence has quickly become part of everyday business conversation. Organisations are exploring AI to improve customer service, automate routine tasks, support staff, analyse information and create content. Products such as ChatGPT, Microsoft Copilot, Claude, Gemini and Perplexity are regularly mentioned in meetings, procurement discussions and digital strategies. The difficulty is that people often use these names interchangeably. One conversation might compare ChatGPT with Microsoft Copilot. Another might discuss GPT-5 or Claude Sonnet. Elsewhere, someone may suggest building an AI assistant or an AI-powered application. Although these terms all relate to artificial intelligence, they describe different parts of the same technology. Understanding those differences helps organisations make better decisions. It becomes easier to compare products, ask the right questions, and identify where AI can genuinely add value rather than simply adopting the latest technology. Perhaps more importantly, it changes the way we think about AI itself. Many organisations begin by asking which AI platform or model they should use. Generally, that’s only one part of the picture. The information available to an AI system, how that information is organised and the problem the organisation is trying to solve can have just as much influence on the outcome as the model itself. Before exploring those wider areas, it’s useful to look at the building blocks that make up modern AI." } ] }, { "id": "why-ai-terminology-feels-confusing", "heading": "Why AI terminology feels confusing", "type": "section", "items": [ "AI models provide the underlying intelligence.", "AI applications allow people to interact with that intelligence.", "AI systems combine AI with organisational knowledge, business processes and other technologies to solve real-world problems." ], "content": [ { "type": "paragraph", "text": "Part of the confusion stems from the way AI products are presented. Take ChatGPT as an example. People often say they are “using ChatGPT” when they actually mean they are interacting with one of OpenAI’s GPT models through the ChatGPT application. Claude is used in much the same way, referring both to Anthropic’s family of AI models and the application people use to access them. Google’s Gemini follows a similar pattern, while Microsoft Copilot describes a growing family of AI-powered products built around different models and services. The technology industry doesn’t always make these distinctions clear, largely because most users don’t need to understand what happens behind the scenes and are usually very happy not to. For organisations thinking about how AI might support their own work, however, those distinctions become much more important. Understanding the relationship between AI models, AI applications and complete AI systems makes it much easier to consider different approaches and identify which technologies are best suited to particular problems. Although different vendors use different terminology, the underlying concepts remain remarkably consistent. It helps to think of most AI solutions as three connected layers. Once you can distinguish between those three layers, discussions about AI become much easier to follow." } ] }, { "id": "what-is-an-ai-model", "heading": "What is an AI model?", "type": "section", "content": [ { "type": "paragraph", "text": "An AI model is the underlying intelligence that performs the reasoning. It has been trained using large amounts of information, allowing it to recognise patterns, generate text, analyse images, write code, answer questions and perform many other tasks depending on how it has been designed. When people refer to models such as GPT-5, Claude Opus, Gemini 2.5 Pro or Llama, they are talking about this underlying intelligence rather than the software people use every day. Despite their impressive capabilities, AI models are surprisingly limited on their own. They don’t provide a chat window, automatically search the web or connect to business systems on their own. They don’t remember previous conversations unless the application using them has added that capability. Nor do they have an inherent understanding of your organisation beyond the information they’re given during a conversation or through connected systems. A useful way to think about an AI model is as the engine in a car. The engine provides the power, but it isn’t the vehicle. On its own it has no steering wheel, dashboard or controls, and there’s no straightforward way for people to use it. Those additional components transform the engine into something practical. AI models work in much the same way. They provide the intelligence, but they aren’t the complete experience." } ] }, { "id": "examples-of-ai-models", "heading": "Examples of AI models", "type": "section", "parent_id": "what-is-an-ai-model", "parent_heading": "What is an AI model?", "items": [ "GPT-5 (OpenAI)", "Claude Opus and Claude Sonnet (Anthropic)", "Gemini 2.5 Pro (Google)", "Llama (Meta)", "Mistral Large (Mistral AI)" ], "content": [ { "type": "paragraph", "text": "Some of the best-known AI models include: Although these models are built by different organisations and have different strengths, they all perform the same basic role. They provide the intelligence that powers the applications and systems people interact with every day." } ] }, { "id": "what-is-an-ai-application", "heading": "What is an AI application?", "type": "section", "content": [ { "type": "paragraph", "text": "If AI models provide the intelligence, AI applications are what make that intelligence useful. An AI application combines a model with the software people need to interact with it. That might include a conversational interface, conversation history, file uploads, web search, memory, user accounts and a growing range of tools that help people complete real tasks. Most people never interact directly with an AI model. They use an application built around it. That distinction matters because organisations often think they’re choosing between AI applications when the real differences may lie in the models that power them. While the underlying model clearly influences the experience, the surrounding application is often just as significant. Two applications built on the same AI model may behave very differently because they have access to different tools, different information and different ways of interacting with users. One might search the web before responding, while another only works with uploaded documents. One may integrate with email and calendars, while another focuses entirely on creative writing or software development. The application is what turns an AI model into something people can actually use." } ] }, { "id": "some-familiar-ai-applications", "heading": "Some familiar AI applications", "type": "section", "parent_id": "what-is-an-ai-application", "parent_heading": "What is an AI application?", "content": [ { "type": "paragraph", "text": "The following examples illustrate how different organisations package AI models into products designed for everyday use." } ] }, { "id": "ChatGPT", "heading": "ChatGPT", "type": "section", "parent_id": "some-familiar-ai-applications", "parent_heading": "Some familiar AI applications", "content": [ { "type": "paragraph", "text": "ChatGPT is OpenAI’s AI application. It combines GPT models with a conversational interface, conversation history, file uploads, web browsing, memory and other tools that make the underlying models practical for everyday tasks." } ] }, { "id": "microsoft-copilot", "heading": "Microsoft Copilot", "type": "section", "parent_id": "what-is-an-ai-application", "parent_heading": "What is an AI application?", "content": [ { "type": "paragraph", "text": "Microsoft Copilot is a family of AI applications that integrate with Microsoft 365, Windows and other Microsoft services. Depending on the version, Copilot can combine AI models with documents, email, calendars and organisational information to support day-to-day work." } ] }, { "id": "claude", "heading": "Claude", "type": "section", "parent_id": "what-is-an-ai-application", "parent_heading": "What is an AI application?", "content": [ { "type": "paragraph", "text": "Claude is Anthropic’s AI application. It provides access to the Claude family of models through a conversational interface and includes features designed to support writing, analysis, coding and document review." } ] }, { "id": "gemini", "heading": "Gemini", "type": "section", "parent_id": "what-is-an-ai-application", "parent_heading": "What is an AI application?", "content": [ { "type": "paragraph", "text": "Gemini is Google’s AI application. It combines Gemini models with Google’s wider ecosystem, allowing users to interact with AI while benefiting from integration with Google’s services and, where appropriate, live information from the web." } ] }, { "id": "perplexity", "heading": "Perplexity", "type": "section", "parent_id": "what-is-an-ai-application", "parent_heading": "What is an AI application?", "content": [ { "type": "paragraph", "text": "Perplexity searches the web before generating a response and includes citations to the sources it uses. That makes it particularly useful when researching unfamiliar topics or checking current information. Although these applications all provide access to artificial intelligence, they don’t necessarily use the same models, nor do they offer the same information or tools. That’s one reason comparing AI products can sometimes feel surprisingly difficult. You’re often comparing much more than the underlying AI model." } ] }, { "id": "organisations-arent-limited-to-off-the-shelf-ai-applications", "heading": "Organisations aren’t limited to off-the-shelf AI applications", "type": "section", "parent_id": "what-is-an-ai-application", "parent_heading": "What is an AI application?", "content": [ { "type": "paragraph", "text": "When people think about AI applications, they often picture products developed by large technology companies. Increasingly, organisations are building their own. Imagine a university receiving thousands of questions each year about admissions, accommodation, wellbeing and assessments. Rather than expecting staff to answer every enquiry manually, the university develops an AI-powered application that searches approved guidance, university regulations and support information before generating a response. The underlying AI model might be exactly the same one available through a public AI application. What makes the experience different is everything built around the model. The university decides what information the application can access, how answers should be presented, when staff should become involved and which services students should be directed towards. The result isn’t a general-purpose AI assistant. It’s an application designed around a particular organisation and the people it serves. Housing associations, charities, healthcare providers, manufacturers and commercial businesses are all beginning to explore AI applications built around their own knowledge, services and processes. Rather than replacing public AI tools such as ChatGPT or Copilot, these applications often complement them by providing access to information that only the organisation itself can offer. The AI model provides the capability to understand and generate information. The application determines how that capability is applied." } ] }, { "id": "what-is-an-ai-system", "heading": "What is an AI system?", "type": "section", "items": [ "one or more AI models", "websites and content platforms", "document libraries", "CRM and business systems", "search and retrieval technologies", "APIs connecting different services", "security and authentication", "business rules and workflows" ], "content": [ { "type": "paragraph", "text": "As organisations begin to connect AI to their own information and business processes, the conversation moves beyond individual applications towards AI systems. An AI system brings together multiple technologies to solve a specific problem or support a particular objective. The AI model remains an important component, but it is no longer the whole story. A typical AI system might combine: Not every AI system includes all of these components, and different organisations will assemble them in different ways. Rather than thinking of AI as a single product, it’s often more helpful to think of it as one component within a wider system that brings together technology, information and business processes." } ] }, { "id": "ai-model", "heading": "AI Model", "type": "section", "parent_id": "what-is-an-ai-system", "parent_heading": "What is an AI system?", "content": [ { "type": "paragraph", "text": "The underlying intelligence that understands requests and generates responses." } ] }, { "id": "ai-application", "heading": "AI Application", "type": "section", "parent_id": "what-is-an-ai-system", "parent_heading": "What is an AI system?", "content": [ { "type": "paragraph", "text": "The software people use to interact with an AI model, combining it with tools such as chat, search, memory and file uploads." } ] }, { "id": "ai-system", "heading": "AI System", "type": "section", "parent_id": "what-is-an-ai-system", "parent_heading": "What is an AI system?", "content": [ { "type": "paragraph", "text": "The complete solution that combines AI with organisational information, business processes and connected technologies." } ] }, { "id": "information", "heading": "Information", "type": "section", "parent_id": "what-is-an-ai-system", "parent_heading": "What is an AI system?", "content": [ { "type": "paragraph", "text": "Policies, documents, websites and knowledge." } ] }, { "id": "search-retrieval", "heading": "Search & Retrieval", "type": "section", "parent_id": "what-is-an-ai-system", "parent_heading": "What is an AI system?", "content": [ { "type": "paragraph", "text": "Finding the right information when it’s needed." } ] }, { "id": "integrations", "heading": "Integrations", "type": "section", "parent_id": "what-is-an-ai-system", "parent_heading": "What is an AI system?", "content": [ { "type": "paragraph", "text": "Connects with APIs, CRM platforms and business systems." } ] }, { "id": "business-rules", "heading": "Business Rules", "type": "section", "parent_id": "what-is-an-ai-system", "parent_heading": "What is an AI system?", "content": [ { "type": "paragraph", "text": "Controls workflows, permissions and governance." } ] }, { "id": "security", "heading": "Security", "type": "section", "parent_id": "what-is-an-ai-system", "parent_heading": "What is an AI system?", "content": [ { "type": "paragraph", "text": "Protects system information through authentication and access control." } ] }, { "id": "people", "heading": "People", "type": "section", "parent_id": "what-is-an-ai-system", "parent_heading": "What is an AI system?", "content": [ { "type": "paragraph", "text": "The employees, customers and others who use the system. Consider an organisation creating an AI assistant to help staff answer questions about internal policies. The application may use a large language model (LLM) to understand the question, search an internal knowledge base for the latest guidance, check whether the employee has permission to view particular documents, retrieve the relevant information and present it through a simple conversational interface. To the person asking the question, the experience feels seamless. The AI model is only one part of a much larger system working with information, business rules and connected technologies to produce that response. That’s why organisations rarely deploy an AI model on its own. They build systems that allow that intelligence to work alongside their own knowledge, processes and people." } ] }, { "id": "why-information-matters-as-much-as-the-ai", "heading": "Why information matters as much as the AI", "type": "section", "content": [ { "type": "paragraph", "text": "It’s easy to assume that the quality of an AI system is determined primarily by the model powering it. While the model is undoubtedly important, it is only one part of the equation. Imagine two organisations using exactly the same AI model. The first has invested time in maintaining its website, reviewing its documentation and organising its information. Services are described consistently, policies are up to date and staff know which sources of information can be trusted. Content has clear ownership and changes are managed through established processes. The second organisation has accumulated years of duplicated content, outdated guidance and disconnected systems. Different departments describe the same services in different ways, documents contradict one another and nobody is entirely certain which version of a policy is current. The AI model hasn’t changed, but the outcome probably will. The difference isn’t the model itself, but the information it can use." } ] }, { "id": "ai-can-only-work-with-the-information-it-receives", "heading": "AI can only work with the information it receives", "type": "section", "content": [ { "type": "paragraph", "text": "Modern AI models are remarkably capable at interpreting language, recognising patterns and generating useful responses. They don’t, however, create organisational knowledge. If an AI system is connected to inaccurate documentation, outdated policies or poorly organised content, those problems don’t disappear simply because AI has been introduced. In many cases, AI exposes those problems more quickly because it depends on reliable information to produce reliable answers. Organisations that have invested in clear content, logical information architecture and well-maintained knowledge often discover they already possess many of the foundations needed for successful AI systems. That doesn’t necessarily mean every document is perfect or every piece of information has been carefully structured for AI. Few organisations begin from that position. What matters is having information that can be trusted, maintained and improved over time. The stronger those foundations become, the more value organisations are likely to gain from AI." } ] } ], "entities": [ { "name": "Large language model (LLM)", "type": "Technology" }, { "name": "Information quality", "type": "Topic" }, { "name": "Microsoft Copilot", "type": "Product" }, { "name": "AI application", "type": "Topic" }, { "name": "Perplexity", "type": "Product" }, { "name": "AI system", "type": "Topic" }, { "name": "AI model", "type": "Topic" }, { "name": "ChatGPT", "type": "Product" }, { "name": "Claude", "type": "Product" }, { "name": "Gemini", "type": "Product" } ], "concept_relationships": [ { "subject": "AI system", "predicate": "combines", "object": "AI with organisational knowledge and business processes" }, { "subject": "AI system", "predicate": "combines", "object": "models, information, technology and business processes" }, { "subject": "AI application", "predicate": "combines", "object": "AI model with software interface and tools" }, { "subject": "AI model", "predicate": "provides", "object": "intelligence that powers applications" }, { "subject": "AI application", "predicate": "allows interaction with", "object": "AI intelligence" }, { "subject": "Application", "predicate": "determines", "object": "how AI capability is applied" }, { "subject": "AI system", "predicate": "includes", "object": "organisational information" }, { "subject": "AI system", "predicate": "includes", "object": "connected technologies" }, { "subject": "AI system", "predicate": "includes", "object": "AI models" } ], "implementation_patterns": [ { "pattern": "AI assistant for internal policy questions", "description": "An organisation creates an AI assistant that uses an LLM to understand questions, searches an internal knowledge base, checks permissions, retrieves relevant information, and presents it via a conversational interface.", "benefit": "Provides seamless access to up-to-date policies while ensuring security and governance." }, { "pattern": "Custom AI application development", "description": "Organisations build AI applications that search approved guidance, regulations, and support information before generating responses, with controls on information access, answer presentation, and staff involvement.", "benefit": "Provides tailored, organisation-specific AI assistance that complements public tools." }, { "pattern": "Information-first AI preparation", "description": "Reviewing content, strengthening governance, improving information architecture and maintaining digital platforms before or alongside AI implementation.", "benefit": "Improves organisational knowledge and AI outcomes, with benefits extending beyond AI." } ], "practical_guidance": [ { "guidance": "When comparing AI products, consider the underlying model, the tools and information available, and the interaction methods.", "importance": "high" }, { "guidance": "When planning AI, consider the wider system including information, business rules, and integrations, not just the model.", "importance": "medium" }, { "guidance": "Understand the three layers of AI (models, applications, systems) to compare products and ask the right questions.", "importance": "high" }, { "guidance": "For organisational needs, consider building custom AI applications that access internal knowledge and processes.", "importance": "medium" }, { "guidance": "Consider the information available to an AI system and how it is organised, not just the model choice.", "importance": "high" }, { "guidance": "Review and improve information quality, governance and architecture as part of AI preparation.", "importance": "high" }, { "guidance": "Ensure content has clear ownership and changes are managed through established processes.", "importance": "high" }, { "guidance": "Consider how different departments describe services consistently to support AI accuracy.", "importance": "medium" } ], "risk_areas": [ { "risk": "Confusing AI models, systems and applications can lead to poor technology decisions.", "impact": "Organisations may choose the wrong AI solution or fail to address underlying information issues." }, { "risk": "Focusing on model selection without understanding the problem or information quality", "impact": "May lead to poor AI outcomes and wasted investment" }, { "risk": "Assuming AI applications are interchangeable without considering model differences.", "impact": "May lead to selecting an application that does not meet performance or suitability needs." }, { "risk": "Overlooking the importance of the application layer in determining behaviour.", "impact": "May result in unexpected differences in functionality, information access, and user experience." }, { "risk": "Inaccurate or outdated information in an AI system", "impact": "AI produces unreliable answers, eroding trust and potentially leading to poor decisions." }, { "risk": "Duplicated content and disconnected systems", "impact": "AI may retrieve conflicting information, reducing the quality of responses." }, { "risk": "Lack of clear content ownership", "impact": "Information may become outdated or inconsistent, undermining AI reliability." }, { "risk": "Poor information governance", "impact": "AI systems may produce inaccurate or inconsistent responses" } ], "common_misconceptions": [ { "misconception": "People often say they are 'using ChatGPT' when they mean they are interacting with a GPT model through the ChatGPT application.", "clarification": "ChatGPT is an application that provides access to OpenAI's GPT models; the model is the underlying intelligence." }, { "misconception": "The quality of an AI system is determined primarily by the model powering it.", "clarification": "While the model is important, the information it can access and the surrounding processes are equally critical to outcomes." }, { "misconception": "Choosing the right AI model determines the success of an AI project.", "clarification": "The model is only one part; information quality and organisation often have as much influence on outcomes." }, { "misconception": "Choosing an AI application is the same as choosing an AI model.", "clarification": "The application layer includes tools, information, and interaction methods that significantly affect the experience." }, { "misconception": "Most people interact directly with an AI model.", "clarification": "Most people use an application built around a model, not the model itself." }, { "misconception": "AI projects are primarily about technology.", "clarification": "Successful AI projects often begin with understanding the organisation itself, with technology as the means of delivery." }, { "misconception": "AI can create organisational knowledge.", "clarification": "AI models interpret language and generate responses but do not create knowledge; they depend on the information they receive." } ], "technical_context": { "components_of_ai_system": [ "One or more AI models", "Websites and content platforms", "Document libraries", "CRM and business systems", "Search and retrieval technologies", "APIs connecting different services", "Security and authentication", "Business rules and workflows", "User interfaces designed for different audiences" ], "definitions": { "AI model": "Provides the underlying intelligence.", "AI application": "Makes AI intelligence accessible.", "AI system": "Combines models with information, technology and business processes to solve real-world problems." }, "key_principles": [ "AI can only work with the information it receives.", "Better information benefits more than AI, including search, accessibility and analytics.", "The same AI model can produce different results depending on information quality and organisation." ] }, "reasoning_paths": [ { "user_problem": "Organisations may think they are choosing between AI applications when the real differences lie in the underlying models.", "why_this_guide_is_relevant": "This page explains the topic and gives practical points to 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