# AI glossary for business leaders · WYP.agency

Each entry defines an AI concept for decision-making: sourced definition, concrete example, executive angle. Add `.md` to any entry URL for its clean Markdown version.

109 published entries.

- [A2A (Agent2Agent)](https://wyp.agency/en/glossary/a2a/): A2A (Agent2Agent) is an open protocol that lets AI agents built by different vendors discover each other, delegate tasks to one another and exchange results securely. [Markdown](https://wyp.agency/en/glossary/a2a.md)
- [AEO (Answer Engine Optimization)](https://wyp.agency/en/glossary/aeo/): AEO (Answer Engine Optimization) is a sub-discipline of GEO, focused on producing direct answers to user questions. [Markdown](https://wyp.agency/en/glossary/aeo.md)
- [Agent orchestration](https://wyp.agency/en/glossary/agent-orchestration/): AI agent orchestration is the coordination of several specialised agents, each responsible for part of a complex task, so they collaborate towards a common goal. [Markdown](https://wyp.agency/en/glossary/agent-orchestration.md)
- [Agent Skills](https://wyp.agency/en/glossary/agent-skills/): An Agent Skill is a folder containing a SKILL.md file and, where needed, scripts and resources, which teaches an AI agent to perform a task your way. [Markdown](https://wyp.agency/en/glossary/agent-skills.md)
- [Agentic AI](https://wyp.agency/en/glossary/agentic-ai/): Agentic AI refers to the ability of an artificial intelligence system to pursue a goal autonomously: it plans steps, uses tools (software, databases, browser) and adjusts its actions based on the results it obtains. [Markdown](https://wyp.agency/en/glossary/agentic-ai.md)
- [Agentic loop](https://wyp.agency/en/glossary/agentic-loop/): The agentic loop is the iterative cycle of an AI agent that acts, observes the result, and decides on the next action, until it reaches its goal or a stopping criterion. [Markdown](https://wyp.agency/en/glossary/agentic-loop.md)
- [AGI (artificial general intelligence)](https://wyp.agency/en/glossary/agi/): AGI (artificial general intelligence) refers to an AI system able to match or exceed humans at most cognitive tasks, not just one. [Markdown](https://wyp.agency/en/glossary/agi.md)
- [AI Act](https://wyp.agency/en/glossary/ai-act/): The AI Act is European Regulation 2024/1689, the world's first legal framework to classify AI systems by risk level and to impose differentiated obligations: prohibition for unacceptable uses, strict requirements for high-risk systems, transparency for the rest. [Markdown](https://wyp.agency/en/glossary/ai-act.md)
- [AI Act for leaders](https://wyp.agency/en/glossary/ai-act-for-leaders/): The AI Act, in force since 1 August 2024, sorts AI systems by level of risk, and the Digital Omnibus postponed the high-risk obligations until the end of 2027. [Markdown](https://wyp.agency/en/glossary/ai-act-for-leaders.md)
- [AI agent](https://wyp.agency/en/glossary/ai-agent/): An AI agent is an autonomous system that combines a language model with external tools to execute multi-step tasks: it analyses a request, plans an action sequence, executes, observes, and adapts its strategy. [Markdown](https://wyp.agency/en/glossary/ai-agent.md)
- [AI agent platform](https://wyp.agency/en/glossary/agent-platform/): An AI agent platform is an environment that allows enterprises to create, deploy, and operate autonomous AI agents. [Markdown](https://wyp.agency/en/glossary/agent-platform.md)
- [AI API](https://wyp.agency/en/glossary/ai-api/): An AI API is a technical interface that lets a software application send requests to an AI model hosted by a provider, and retrieve its responses. [Markdown](https://wyp.agency/en/glossary/ai-api.md)
- [AI carbon footprint](https://wyp.agency/en/glossary/ai-carbon-footprint/): The AI carbon footprint is the set of greenhouse gas emissions related to its life cycle: model training, component manufacturing, data centre operation, and inference at usage. [Markdown](https://wyp.agency/en/glossary/ai-carbon-footprint.md)
- [AI crash-test of a board pack](https://wyp.agency/en/glossary/ai-board-pack-crash-test/): An AI crash-test runs your board pack through several cross-checked models before the meeting, to surface weak signals, internal contradictions and points that won't hold in the room. [Markdown](https://wyp.agency/en/glossary/ai-board-pack-crash-test.md)
- [AI governance in the CAC 40 (2026 study)](https://wyp.agency/en/glossary/cac40-ai-governance-2026/): In their fiscal 2025 universal registration documents, all 40 CAC 40 companies describe uses of artificial intelligence and 38 set out an AI strategy. [Markdown](https://wyp.agency/en/glossary/cac40-ai-governance-2026.md)
- [AI literacy (Article 4)](https://wyp.agency/en/glossary/ai-literacy/): AI literacy means the skills, knowledge and understanding that allow people to use AI systems in an informed way and to be aware of their opportunities, risks and possible harms. [Markdown](https://wyp.agency/en/glossary/ai-literacy.md)
- [AI Overviews and AI Mode](https://wyp.agency/en/glossary/ai-overviews/): AI Overviews are AI-generated summaries shown at the top of some Google results, with links to sources. [Markdown](https://wyp.agency/en/glossary/ai-overviews.md)
- [AI POC](https://wyp.agency/en/glossary/ai-poc/): An AI POC (proof of concept) is a short pilot project aimed at testing the technical feasibility and business value of an AI application before any industrial investment. [Markdown](https://wyp.agency/en/glossary/ai-poc.md)
- [AI ROI](https://wyp.agency/en/glossary/ai-roi/): AI ROI, modelled on classic financial ROI, is a deceptively appealing metric for evaluating an AI deployment. [Markdown](https://wyp.agency/en/glossary/ai-roi.md)
- [AI sycophancy](https://wyp.agency/en/glossary/ai-sycophancy/): AI sycophancy is the tendency of a generative AI model to tailor its answers to agree with the user, sometimes at the expense of accuracy. [Markdown](https://wyp.agency/en/glossary/ai-sycophancy.md)
- [AI TCO](https://wyp.agency/en/glossary/ai-tco/): AI TCO (total cost of ownership) is the real total cost of an AI deployment in enterprise, aggregating five items: inference model, infrastructure, application integration, operational supervision, and team cost. [Markdown](https://wyp.agency/en/glossary/ai-tco.md)
- [AI use case](https://wyp.agency/en/glossary/ai-use-cases/): An AI use case is a concrete application of artificial intelligence to an identified business process, with a measurable objective and a defined perimeter. [Markdown](https://wyp.agency/en/glossary/ai-use-cases.md)
- [AI workflow](https://wyp.agency/en/glossary/ai-workflow/): An AI workflow is the structured sequence of several AI inference steps to accomplish a complex task, usually with external tools interleaved. [Markdown](https://wyp.agency/en/glossary/ai-workflow.md)
- [AI-generated content labelling (Article 50)](https://wyp.agency/en/glossary/ai-content-labelling/): AI-generated content labelling refers to the signals, machine-readable (invisible watermark, metadata) or human-readable (label, notice), showing that an image, video, audio or text was produced or altered by AI. [Markdown](https://wyp.agency/en/glossary/ai-content-labelling.md)
- [Algorithmic bias](https://wyp.agency/en/glossary/algorithmic-bias/): An algorithmic bias is a systematic deviation in an AI model, inherited from training data, design choices, or deployment context, that produces unfair or erroneous decisions to the detriment of a population group or a type of case. [Markdown](https://wyp.agency/en/glossary/algorithmic-bias.md)
- [Alignment](https://wyp.agency/en/glossary/alignment/): Alignment is the set of techniques that aim to steer the behaviour of an AI model towards the goals and human values of its user or publisher. [Markdown](https://wyp.agency/en/glossary/alignment.md)
- [Artificial intelligence (AI)](https://wyp.agency/en/glossary/artificial-intelligence/): Artificial intelligence (AI) refers to the set of techniques that enable a machine to perform tasks associated with human intelligence: recognising an image, understanding a text, predicting, deciding, writing. [Markdown](https://wyp.agency/en/glossary/artificial-intelligence.md)
- [Auditing AI maturity](https://wyp.agency/en/glossary/ai-maturity-audit/): Auditing AI maturity means measuring what is actually used, what data flows through it and what framework exists, then placing the organisation between denial, prohibition, framing and governance. [Markdown](https://wyp.agency/en/glossary/ai-maturity-audit.md)
- [Augmented automation](https://wyp.agency/en/glossary/augmented-automation/): Augmented automation is the use of AI to assist a human worker in performing a task, rather than to replace them. [Markdown](https://wyp.agency/en/glossary/augmented-automation.md)
- [Augmented productivity](https://wyp.agency/en/glossary/augmented-productivity/): AI-augmented productivity refers to measurable production gains (volume processed, speed, quality) that a worker achieves when they benefit from generative AI assistance. [Markdown](https://wyp.agency/en/glossary/augmented-productivity.md)
- [Autonomous Claude Code](https://wyp.agency/en/glossary/claude-code-autonomous/): In autonomous mode, you no longer drive every step of Claude Code: you set a stop condition once, and a check (an evaluator model or a script) verifies it after each turn until the work is genuinely finished. [Markdown](https://wyp.agency/en/glossary/claude-code-autonomous.md)
- [Briefing a leadership team on AI](https://wyp.agency/en/glossary/brief-leadership-on-ai/): To brief a leadership team on AI, start from what teams already do, not from a lecture on the technology. [Markdown](https://wyp.agency/en/glossary/brief-leadership-on-ai.md)
- [Bringing shadow AI under control](https://wyp.agency/en/glossary/shadow-ai-framing-guide/): Bringing shadow AI under control means writing a readable AI policy, providing an approved and properly hosted tool, and having a person review every high-stakes output. [Markdown](https://wyp.agency/en/glossary/shadow-ai-framing-guide.md)
- [Chain of thought](https://wyp.agency/en/glossary/chain-of-thought/): Chain of thought means a language model writes out intermediate reasoning steps before giving its answer. [Markdown](https://wyp.agency/en/glossary/chain-of-thought.md)
- [Chatbot (conversational agent)](https://wyp.agency/en/glossary/chatbot/): A chatbot (or conversational agent) is software that converses in natural language with a human, in writing or by voice, to answer questions or trigger tasks. [Markdown](https://wyp.agency/en/glossary/chatbot.md)
- [Choosing an independent AI advisor](https://wyp.agency/en/glossary/independent-ai-advisor/): An AI advisor is independent when it takes no vendor commission, sells no tool or deployment, cross-checks several models and has a person sign every deliverable. [Markdown](https://wyp.agency/en/glossary/independent-ai-advisor.md)
- [Citability](https://wyp.agency/en/glossary/citability/): Citability is the property of a piece of content of being extracted, restituted, and attributed as is by an AI engine in its response to a user. [Markdown](https://wyp.agency/en/glossary/citability.md)
- [Claude Code](https://wyp.agency/en/glossary/claude-code/): Claude Code is Anthropic's agentic coding tool, launched in preview in February 2025 and generally available in May 2025. [Markdown](https://wyp.agency/en/glossary/claude-code.md)
- [Claude vs ChatGPT security](https://wyp.agency/en/glossary/claude-vs-chatgpt-security/): For a leadership team, the security of Claude or ChatGPT depends less on the tool than on the plan chosen, enterprise or consumer, and on the usage framework set. [Markdown](https://wyp.agency/en/glossary/claude-vs-chatgpt-security.md)
- [Computer vision](https://wyp.agency/en/glossary/computer-vision/): Computer vision is the field of artificial intelligence that enables a machine to analyse images and video: recognising objects, detecting defects, reading a document, tracking movement. [Markdown](https://wyp.agency/en/glossary/computer-vision.md)
- [Context engineering](https://wyp.agency/en/glossary/context-engineering/): Context engineering is the discipline of choosing, at each step, the full set of information placed in an AI model's context window: instructions, documents, history, tool results, memory. [Markdown](https://wyp.agency/en/glossary/context-engineering.md)
- [Context window](https://wyp.agency/en/glossary/context-window/): The context window is the maximum amount of text an AI model can process in a single query, measured in tokens. [Markdown](https://wyp.agency/en/glossary/context-window.md)
- [Conversation roles](https://wyp.agency/en/glossary/conversation-roles/): Conversation roles (system, user, assistant) are the labels assigned to each message in an exchange with an LLM. [Markdown](https://wyp.agency/en/glossary/conversation-roles.md)
- [Conversational indexing](https://wyp.agency/en/glossary/conversational-indexing/): Conversational indexing is the process by which AI engines build their responses from web content: ingestion at training (dated corpus), retrieval at inference (RAG via web search), or both combined. [Markdown](https://wyp.agency/en/glossary/conversational-indexing.md)
- [Copilot](https://wyp.agency/en/glossary/copilot/): An AI copilot is an assistant that suggests, proposes, and completes actions to the user, who keeps control of the final decision and execution. [Markdown](https://wyp.agency/en/glossary/copilot.md)
- [Cost per token](https://wyp.agency/en/glossary/cost-per-token/): Cost per token is the elementary economic unit of an AI deployment. [Markdown](https://wyp.agency/en/glossary/cost-per-token.md)
- [Deep learning](https://wyp.agency/en/glossary/deep-learning/): Deep learning is a form of machine learning that uses artificial neural networks made up of many layers, each processing data at a higher level of abstraction. [Markdown](https://wyp.agency/en/glossary/deep-learning.md)
- [Deep research](https://wyp.agency/en/glossary/deep-research/): Deep research is an AI agent feature that autonomously carries out a multi-step search on the web, sometimes in your documents, then writes a report with its sources. [Markdown](https://wyp.agency/en/glossary/deep-research.md)
- [Deepfake](https://wyp.agency/en/glossary/deepfake/): A deepfake is an image, sound or video generated or manipulated by AI that resembles a real person, place or event and can be mistaken for authentic. [Markdown](https://wyp.agency/en/glossary/deepfake.md)
- [Delegating to AI agents](https://wyp.agency/en/glossary/delegating-to-ai-agents/): An AI agent is not a tool you launch, it is a decision you delegate. [Markdown](https://wyp.agency/en/glossary/delegating-to-ai-agents.md)
- [Digital Omnibus](https://wyp.agency/en/glossary/digital-omnibus/): The Digital Omnibus is a package simplifying EU digital rules, presented by the European Commission on 19 November 2025. [Markdown](https://wyp.agency/en/glossary/digital-omnibus.md)
- [Digital sovereignty](https://wyp.agency/en/glossary/digital-sovereignty/): Digital sovereignty is the capacity of a company or a state to control its data, its infrastructure, and its AI tools, independently of foreign jurisdictions. [Markdown](https://wyp.agency/en/glossary/digital-sovereignty.md)
- [Distillation](https://wyp.agency/en/glossary/distillation/): Distillation is a technique that transfers the knowledge of a large AI model (teacher model) to a smaller model (student model), while preserving most of the performance. [Markdown](https://wyp.agency/en/glossary/distillation.md)
- [Embedding](https://wyp.agency/en/glossary/embedding/): An embedding is the numerical representation of a word, a sentence, or a document, in the form of a vector in a space of several hundred or thousand dimensions. [Markdown](https://wyp.agency/en/glossary/embedding.md)
- [Evidence-based claim resolution](https://wyp.agency/en/glossary/ai-claim-resolution/): AI claim resolution hands a specialised agent the claims whose outcome depends on a proof: it gets the evidence at the source, verifies it, applies the business rules and resolves the case in the existing tool, never refusing alone, escalating with the proof in hand when the case is doubtful. [Markdown](https://wyp.agency/en/glossary/ai-claim-resolution.md)
- [Explainable AI (XAI)](https://wyp.agency/en/glossary/explainable-ai/): Explainable AI (XAI) covers the methods that make it possible to understand why an AI system produced a given result, and to explain it to the person concerned. [Markdown](https://wyp.agency/en/glossary/explainable-ai.md)
- [Fine-tuning](https://wyp.agency/en/glossary/fine-tuning/): Fine-tuning is an adaptation technique for an already-trained AI model, which consists of continuing its training on a dataset specific to your use case. [Markdown](https://wyp.agency/en/glossary/fine-tuning.md)
- [Foundation model](https://wyp.agency/en/glossary/foundation-model/): A foundation model is a generalist AI model trained on massive, diversified data, which serves as a reusable base for dozens or even hundreds of different business applications, by adaptation (fine-tuning, RAG, prompt) rather than by specific training. [Markdown](https://wyp.agency/en/glossary/foundation-model.md)
- [Frugal AI](https://wyp.agency/en/glossary/frugal-ai/): Frugal AI refers to an AI service whose necessity compared with a less resource-intensive solution has been demonstrated, which applies good practices to reduce its environmental impact, and whose uses have been questioned to stay within planetary boundaries. [Markdown](https://wyp.agency/en/glossary/frugal-ai.md)
- [Function calling](https://wyp.agency/en/glossary/function-calling/): Function calling is the ability of an AI model to invoke predefined functions or tools to execute actions in an external system. [Markdown](https://wyp.agency/en/glossary/function-calling.md)
- [GDPR and AI](https://wyp.agency/en/glossary/gdpr-ai/): GDPR governs all personal-data processing by an AI system operated in the European Union or targeting people located there. [Markdown](https://wyp.agency/en/glossary/gdpr-ai.md)
- [Generative AI](https://wyp.agency/en/glossary/generative-ai/): Generative AI is a family of artificial intelligence models capable of producing new content (text, image, sound, video, code) from a natural-language instruction, as opposed to traditional AI which was limited to classifying, predicting, or detecting. [Markdown](https://wyp.agency/en/glossary/generative-ai.md)
- [Generative reference](https://wyp.agency/en/glossary/generative-reference/): A generative reference is the mention of a source in an AI engine's response to a user: textual citation, explicit attribution, or hyperlink to the original content. [Markdown](https://wyp.agency/en/glossary/generative-reference.md)
- [GEO (Generative Engine Optimization)](https://wyp.agency/en/glossary/geo/): GEO (Generative Engine Optimization) is the set of practices aimed at making content identifiable, trustworthy, and citable by generative answer engines (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews). [Markdown](https://wyp.agency/en/glossary/geo.md)
- [Guardrails](https://wyp.agency/en/glossary/guardrails/): Guardrails are technical control layers, added at the input or output of an AI model, that detect and block undesirable behaviours: malicious prompts, data leaks, forbidden content. [Markdown](https://wyp.agency/en/glossary/guardrails.md)
- [Hallucination](https://wyp.agency/en/glossary/hallucination/): A hallucination is a factually false statement but formulated with confidence by a generative AI model. [Markdown](https://wyp.agency/en/glossary/hallucination.md)
- [Human in the loop](https://wyp.agency/en/glossary/human-in-the-loop/): Human in the loop refers to a mode of operation in which a person approves, corrects or rejects each decision of an AI system before it takes effect. [Markdown](https://wyp.agency/en/glossary/human-in-the-loop.md)
- [Inference](https://wyp.agency/en/glossary/inference/): Inference is the usage phase of an AI model, during which the model computes a response from a given prompt. [Markdown](https://wyp.agency/en/glossary/inference.md)
- [ISO/IEC 42001](https://wyp.agency/en/glossary/iso-42001/): ISO/IEC 42001 is the international standard, published in December 2023 by ISO and IEC, that sets the requirements for an artificial intelligence management system (AIMS): policy, roles, risk and impact assessment, controls and continual improvement. [Markdown](https://wyp.agency/en/glossary/iso-42001.md)
- [LLM (Large Language Model)](https://wyp.agency/en/glossary/llm/): An LLM (Large Language Model) is a type of artificial intelligence trained on text corpora of several hundred billion words, which produces natural language by predicting, word by word, the most probable continuation of a given text. [Markdown](https://wyp.agency/en/glossary/llm.md)
- [LLM evaluation (evals, LLM as a judge)](https://wyp.agency/en/glossary/llm-evaluation/): LLM evaluation (“evals”) means measuring the quality of a model's or AI assistant's answers on a set of representative cases, against success criteria set in advance. [Markdown](https://wyp.agency/en/glossary/llm-evaluation.md)
- [llms.txt](https://wyp.agency/en/glossary/llms-txt/): llms.txt is a proposed web standard introduced in September 2024 by Answer.AI, providing AI models with a structured map of a website's content. [Markdown](https://wyp.agency/en/glossary/llms-txt.md)
- [Machine learning](https://wyp.agency/en/glossary/machine-learning/): Machine learning is the branch of artificial intelligence in which a program learns to perform a task from examples, instead of following rules written by a programmer. [Markdown](https://wyp.agency/en/glossary/machine-learning.md)
- [Making generative AI legally safe](https://wyp.agency/en/glossary/secure-generative-ai/): Banning generative AI pushes use into the shadows, and leaving it alone exposes the company. [Markdown](https://wyp.agency/en/glossary/secure-generative-ai.md)
- [Map and territory](https://wyp.agency/en/glossary/map-and-territory/): The map is not the territory. [Markdown](https://wyp.agency/en/glossary/map-and-territory.md)
- [MCP (Model Context Protocol)](https://wyp.agency/en/glossary/mcp/): MCP (Model Context Protocol) is an open standard, introduced by Anthropic in November 2024, that lets an AI model connect to data sources and external tools in a uniform way. [Markdown](https://wyp.agency/en/glossary/mcp.md)
- [MoE (Mixture of Experts)](https://wyp.agency/en/glossary/moe/): Mixture of Experts (MoE) is an AI model architecture that splits the network into specialised sub-models, called experts. [Markdown](https://wyp.agency/en/glossary/moe.md)
- [Multimodal](https://wyp.agency/en/glossary/multimodal/): A multimodal AI model is a model capable of processing and producing several types of content simultaneously: text, image, audio, video, code. [Markdown](https://wyp.agency/en/glossary/multimodal.md)
- [Neural network (artificial)](https://wyp.agency/en/glossary/neural-network/): An artificial neural network is a computing model made of small interconnected units, artificial neurons, organised in layers: each neuron combines its inputs according to weights, then passes a signal to the next layer. [Markdown](https://wyp.agency/en/glossary/neural-network.md)
- [NLP (natural language processing)](https://wyp.agency/en/glossary/natural-language-processing/): NLP (natural language processing) is the field of artificial intelligence that enables a machine to analyse, understand and produce human language, written or spoken. [Markdown](https://wyp.agency/en/glossary/natural-language-processing.md)
- [Open-source model](https://wyp.agency/en/glossary/open-source-model/): An open-source AI model is a foundation model whose weights and architecture are freely downloadable and usable under a more or less permissive licence (Apache 2.0, MIT or a custom licence). [Markdown](https://wyp.agency/en/glossary/open-source-model.md)
- [Overfitting](https://wyp.agency/en/glossary/overfitting/): Overfitting describes an AI model that fits its training data so closely that it memorises it instead of learning general rules: it scores very well in internal tests, then makes mistakes on new cases. [Markdown](https://wyp.agency/en/glossary/overfitting.md)
- [Parameter](https://wyp.agency/en/glossary/parameter/): A parameter of an AI model is a numerical value learned during training that determines the strength of connections between the artificial neurons of the network. [Markdown](https://wyp.agency/en/glossary/parameter.md)
- [Prompt](https://wyp.agency/en/glossary/prompt/): A prompt is the natural-language instruction sent to an AI model to obtain a response. [Markdown](https://wyp.agency/en/glossary/prompt.md)
- [Prompt engineering](https://wyp.agency/en/glossary/prompt-engineering/): Prompt engineering is the discipline of writing prompts methodically. [Markdown](https://wyp.agency/en/glossary/prompt-engineering.md)
- [Prompt injection](https://wyp.agency/en/glossary/prompt-injection/): Prompt injection is an attack that slips instructions into the text an AI processes in order to hijack its behaviour: ignore its instructions, disclose data, trigger an action. [Markdown](https://wyp.agency/en/glossary/prompt-injection.md)
- [Prompting patterns](https://wyp.agency/en/glossary/prompting-patterns/): Prompting patterns are formulation conventions that structure a prompt to orient the model's output. [Markdown](https://wyp.agency/en/glossary/prompting-patterns.md)
- [RAG (Retrieval-Augmented Generation)](https://wyp.agency/en/glossary/rag/): RAG (Retrieval-Augmented Generation) is an AI architecture that pairs a search engine across your documents with a generative model. [Markdown](https://wyp.agency/en/glossary/rag.md)
- [Reasoning model](https://wyp.agency/en/glossary/reasoning-model/): A reasoning model is a large language model trained to produce internal, step-by-step thinking before giving its answer. [Markdown](https://wyp.agency/en/glossary/reasoning-model.md)
- [Red teaming](https://wyp.agency/en/glossary/red-teaming/): Red teaming, borrowed from cybersecurity, is the practice of testing an AI system by simulating adverse usage attempts: rule bypassing, sensitive-data extraction, forbidden-content generation. [Markdown](https://wyp.agency/en/glossary/red-teaming.md)
- [Reinforcement learning](https://wyp.agency/en/glossary/reinforcement-learning/): Reinforcement learning is a machine learning method in which a system learns which actions to choose by trying them and receiving a reward or a penalty, so as to maximise a cumulative gain over time. [Markdown](https://wyp.agency/en/glossary/reinforcement-learning.md)
- [Responsible AI](https://wyp.agency/en/glossary/responsible-ai/): Responsible AI is a way of designing, buying and using AI that respects verifiable principles: fairness, respect for rights and privacy, transparency, robustness, clearly assigned accountability and environmental restraint. [Markdown](https://wyp.agency/en/glossary/responsible-ai.md)
- [RLHF (reinforcement learning from human feedback)](https://wyp.agency/en/glossary/rlhf/): RLHF (reinforcement learning from human feedback) is a training technique that adjusts a language model according to the preferences of people who compare and rank its answers. [Markdown](https://wyp.agency/en/glossary/rlhf.md)
- [Schema.org for AI](https://wyp.agency/en/glossary/schema-org-ai/): Schema.org is a standard structured semantic markup vocabulary (most often JSON-LD) that AI engines use to understand the nature of a web page: defined term, FAQ, article, product, event. [Markdown](https://wyp.agency/en/glossary/schema-org-ai.md)
- [Shadow AI](https://wyp.agency/en/glossary/shadow-ai/): Shadow AI refers to the use of generative AI models by employees without validation or framing from their company. [Markdown](https://wyp.agency/en/glossary/shadow-ai.md)
- [Shadow AI Barometer 2026](https://wyp.agency/en/glossary/shadow-ai-barometer-2026/): In 2026, the ungoverned use of generative AI at work is no longer marginal. [Markdown](https://wyp.agency/en/glossary/shadow-ai-barometer-2026.md)
- [SLM (Small Language Model)](https://wyp.agency/en/glossary/small-language-model/): An SLM (small language model) is a language model compact enough to run on a computer, a phone or a modest server, generally under 10 billion parameters. [Markdown](https://wyp.agency/en/glossary/small-language-model.md)
- [Strategic AI framing in 10 days](https://wyp.agency/en/glossary/ai-framing-10-days/): A strategic AI framing for general management takes 10 working days, at a fixed fee of €2,900 excl. [Markdown](https://wyp.agency/en/glossary/ai-framing-10-days.md)
- [Supervised learning](https://wyp.agency/en/glossary/supervised-learning/): Supervised learning is a machine learning method in which a model is trained on examples whose correct answer is known (a label), so that it can predict that answer for new cases. [Markdown](https://wyp.agency/en/glossary/supervised-learning.md)
- [Token](https://wyp.agency/en/glossary/token/): A token is the elementary unit of text that an AI model manipulates, generally a word fragment of 2 to 4 characters, depending on the model and the language. [Markdown](https://wyp.agency/en/glossary/token.md)
- [Training](https://wyp.agency/en/glossary/training/): Training is the construction phase of an AI model, during which the model ingests a massive corpus and adjusts its billions of internal parameters to learn the statistical regularities of that corpus. [Markdown](https://wyp.agency/en/glossary/training.md)
- [Training data](https://wyp.agency/en/glossary/training-data/): Training data is the set of texts, images, code, and other content used to train an AI model. [Markdown](https://wyp.agency/en/glossary/training-data.md)
- [Transformer](https://wyp.agency/en/glossary/transformer/): The transformer is the neural-network architecture, introduced by Google in 2017, that underpins nearly all current generative AI models. [Markdown](https://wyp.agency/en/glossary/transformer.md)
- [Unsupervised learning](https://wyp.agency/en/glossary/unsupervised-learning/): Unsupervised learning is a machine learning method that looks for structure in raw data, without any expected answer provided in advance: groups of similar items, unusual behaviour, variables that go together. [Markdown](https://wyp.agency/en/glossary/unsupervised-learning.md)
- [Usage discipline](https://wyp.agency/en/glossary/usage-discipline/): AI usage discipline is the set of rules, methods, and habits by which a company orients the daily use of AI by its employees: which use cases to activate, how to formulate requests, which models to use, how to audit outputs. [Markdown](https://wyp.agency/en/glossary/usage-discipline.md)
- [Vector database](https://wyp.agency/en/glossary/vector-database/): A vector database is a database specialised in the storage and retrieval of vectors (embeddings). [Markdown](https://wyp.agency/en/glossary/vector-database.md)
- [Vibe coding](https://wyp.agency/en/glossary/vibe-coding/): Vibe coding is a way of building software by describing what you want to an AI, in everyday language, and accepting the code it produces without reading or understanding it. [Markdown](https://wyp.agency/en/glossary/vibe-coding.md)
- [Visual AI agent](https://wyp.agency/en/glossary/visual-ai-agent/): A visual AI agent is an agent that takes the image (photo, video, screenshot, scanned document) as primary input: it perceives visual content, extracts its meaning, decides, then triggers an action in business tools, where a classical agent acts on text alone. [Markdown](https://wyp.agency/en/glossary/visual-ai-agent.md)
- [Workslop](https://wyp.agency/en/glossary/workslop/): Workslop is AI-generated work content that looks like good work but lacks the substance to meaningfully advance the task. [Markdown](https://wyp.agency/en/glossary/workslop.md)

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WYP.agency · https://wyp.agency/en/glossary/ · Last updated : 2026-10-16