Research

Research use cases have AI search, synthesize, and structure information from multiple sources. Instead of spending hours reading, comparing, and summarizing, you direct the AI on what to investigate and it handles the collection and organization — you focus on interpretation and decisions.

Research becomes particularly powerful when paired with MCP connections to your actual data sources — the AI can pull from your CRM, project tools, internal wikis, and external databases rather than relying solely on web search or uploaded documents.

Research is one of six use case primitives identified in OpenAI’s Identifying and Scaling AI Use Cases, adapted here to be platform-agnostic.

When to apply this primitive

Use Research when:

• You need to gather and compare information from multiple sources
• The deliverable is a summary, analysis, or structured set of findings
• You’re making a decision that requires understanding a landscape (vendors, competitors, options)
• You need to monitor ongoing changes in a domain (market shifts, regulatory updates, competitive moves)

Not the right primitive when:

• The main output is a written piece for an audience — that’s Content Creation
• You’re exploring ideas and strategies rather than gathering facts — that’s Ideation & Strategy
• You’re analyzing structured numerical data — that’s Data Analysis

Worked use cases

No worked examples published yet for this primitive.

Browse the full library for adjacent ideas, or design your own using the Deconstruct step of the AI Workflow Framework.

Related

• AI Use Cases Overview — the full library, searchable and filterable by primitive
• Agents — autonomous AI that can plan and execute multi-step research
• MCP — connecting AI to external data sources for live research
• Context — providing source documents and background knowledge
• Automation — running research workflows on a schedule