Working on connected data, business intelligence, and AI products has reinforced the importance of three layers: a reliable data foundation, business intelligence that reflects how people operate, and an AI experience that makes those insights easier to reach and use.
Putting a conversational interface over fragmented data does not solve the underlying problem. The product still needs clear definitions, dependable data and a place in the decisions people make every day.
Context has to survive the handovers.
Automotive retail makes this particularly visible because it is inherently omnichannel. Sales, stock, service, finance and customer activity move between digital journeys, retailer conversations, several systems and multiple teams.
An answer that looks convincing but cannot carry the right context across those touchpoints—or be traced, understood and kept current—will not earn lasting trust.
Start with the decision, establish the data product needed to support it, and then design the AI interaction.
The question for product leaders.
What decision is the AI product helping someone make, and what would make them trust the answer? That question should shape the data, experience, controls and operating model around it.