IT & Data
Natural language querying of business data
Let business users ask questions of the data warehouse in plain English and receive a chart or table, with the generated query shown so an analyst can verify the logic.
40–60%
reduction in ad hoc reporting requests to analysts
Opportunity assessment
Moderate impact. Meaningful cost or revenue improvement, likely noticeable at function level but modest relative to total business scale.
Moderate effort. Requires configuration, prompt engineering, and testing. A capable team can get there but expect several months.
Demanding data requirements. Relies on clean, integrated data across multiple systems. Significant data preparation work typically needed.
Moderate risk. Some customer or external exposure. Errors create rework or reputational impact but are recoverable.
Moderate people impact. Part of someone's working day changes. Requires training and some adjustment time, but roles remain broadly the same.
Tooling required
Things to consider
The failure mode is a confidently wrong number that reaches a board pack. Show the generated query and the row count every time, and restrict the tool to a governed semantic layer rather than raw tables.
Business definitions are the real problem. If 'active customer' means three different things in three teams, the model will pick one and nobody will notice. Agree the definitions in the semantic layer first.
Row-level security must be enforced at the data layer, not in the prompt. A user must not be able to ask their way into another region's numbers.
Experiment starter: Define twenty certified metrics in a semantic layer and let one business team query them in natural language for a month. Have an analyst audit fifty answers. Below 95% correctness, keep it in the analyst team's hands.
Go deeper in the playbook
Section — Opportunity Identification, including the AI Opportunity Assessment ScorecardSection — The Experimentation FrameworkThis is an augmentation opportunity — see the relevant playbook section for how to approach it.More in IT & Data
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