Generative AI Search (GenAI Search)
Definition
Generative AI Search (GenAI Search) is a neutral industry term for AI-powered search systems that answer queries not only with a list of links but also with directly generated answers, summaries, or recommendations. The term includes Google’s SGE as well as comparable offerings from Bing (Copilot), Perplexity, You.com, and other platforms.
Generative AI Search describes the combination of traditional search engine technology and generative AI to dynamically create and deliver content within the search context. It uses Large Language Models (LLMs) to process information from various sources, synthesize it, and present it in natural language.
Examples of Applications
- AI-powered Q&A sessions (“Ask Me Anything”)
- Instant thematic overviews with links
- Personalized recommendation suggestions
- Research support for complex topics or decisions
Target Groups
- Users seeking quick, context-rich answers
- Researchers, students, knowledge workers
- Companies optimizing their content for new search paradigms
Benefits
- Time savings through consolidated, easy-to-understand answers
- Support in complex decision-making processes
- Multi-platform applicability
Key Components
- LLM integration for generating context-based answers
- Relevance filters to select appropriate sources
- User interaction via chat or follow-up question features
Priorities
- Ensuring factual accuracy and source quality
- Optimization for various end devices
- Data protection and transparency in information processing
Trends
- Cross-platform integration of GenAI Search into apps, operating systems, and enterprise tools
- Combination with real-time data and personal context information
- Growing importance for content strategies and search engine optimization