AI & Automation guides

Where AI changes product content operations: enrichment, generation, answer engines, agentic commerce and the EU AI Act.

• Agentic commerce: preparing product data for AI shopping agentsAgentic commerce is shopping in which AI agents search, compare and complete purchases on behalf of buyers.
• AI in PIM: use cases, data requirements and governanceAI in PIM is the use of machine learning and large language models inside product information management to create, enrich, classify, translate and check product data.
• AI product data enrichment: extraction, classification, QAAI product data enrichment uses machine learning and large language models to fill missing attributes, extract values from supplier documents and images, classify products into standards such as ETIM, ECLASS or GS1 GPC, and normalise units and values.
• The EU AI Act and AI-generated product content in 2026For product content teams, the EU AI Act (Regulation (EU) 2024/1689) mainly means Article 50 transparency duties, applicable since 2 August 2026, and an obligation to support AI literacy.
• Generative AI for product descriptions: workflow and controlsGenerative AI for product descriptions uses large language models to draft titles, descriptions and bullet points from structured product attributes, brand guidelines and channel rules.
• Generative engine optimisation (GEO) for product contentGenerative engine optimisation (GEO) is the practice of structuring product content so that AI assistants and AI search features, such as ChatGPT, Gemini and Google AI Mode, can find, interpret and cite it.