TDWI surveyed 208 data and analytics leaders. Only 17% have moved generative BI into broad or enterprise-standard production. The rest are still stuck researching or running an isolated pilot that won’t hold at scale, and that’s the gap this report’s Blueprint closes. It lays out the data, semantic, governance, and operational capabilities that separate real business impact from stalled experiments.
What you’ll learn:
- 48% of organizations point to productivity as the top driver for generative BI, well ahead of cost reduction’s 23%. That gap changes how you should pitch the internal business case.
- Four capability layers make up the TDWI Blueprint: from the data and analytics foundation to the analytics experience layer, plus the governance, evaluation, and people practices that connect them.
- Organizations that treat their semantic layer as strategic infrastructure are more likely to have generative BI running in production instead of stuck in pilot.
- How to prepare unstructured data, like documents and call transcripts, as a governed analytical asset instead of piping it straight into a model.
- A five-stage maturity path, from conversational access to AI-native, agentic analytics, and why just 17% of organizations have reached broad or enterprise-standard production.
