Glossary
AI Product Ops Terminology Glossary
A practical glossary for AI product operations terms used in discovery, synthesis, workflow governance, and operating memory.
Use this glossary to keep AI product operations language grounded in product work, evidence standards, review gates, and decision ownership. These definitions are operational. They do not create legal, security, privacy, compliance, or regulatory assurance.
Terms
AI-native product operations
AI-native product operations are product operating practices that use AI systems as part of discovery, synthesis, prioritization, documentation, execution, and measurement workflows.
AI-assisted discovery
AI-assisted discovery is the use of AI systems to help collect, organize, summarize, compare, or analyze discovery inputs while preserving human review of source material and decisions.
Source-grounded synthesis
Source-grounded synthesis is an AI-assisted or human synthesis process where conclusions remain traceable to original inputs such as customer interviews, support tickets, usage data, or research notes.
Prompt workflow
A prompt workflow is a repeatable set of instructions, inputs, review steps, and outputs used to complete a product operation with an AI system.
Human review gate
A human review gate is a required checkpoint where a person evaluates AI-assisted output before it influences a customer-facing asset, product decision, or operating process.
AI evidence risk
AI evidence risk is the chance that AI-assisted synthesis misstates, overweights, omits, or invents evidence in a way that weakens product judgment.
Operating memory
Operating memory is the maintained record of product decisions, assumptions, evidence, rationale, and outcomes that teams use to preserve context across planning cycles.
AI product ops scorecard
An AI product ops scorecard is an assessment artifact that evaluates how effectively a product organization uses AI across discovery, prioritization, execution, governance, and measurement.
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