Definitely ai highlights issues with underlying data quality. However I think that is a benefit. Ie shine the spotlight to then fix the issues. Ai is very useful in resolving these issues.

Personally where I think the value of ai is in agentic workflows. These could be user initiated or part of an autonomous workflow.

Over the weekend I was playing with Claude.ai desktop and then plugging in Thoughtspot’s mcp server to access structured data.

Ie assume you are planning a quarterly review with your manager. Traditional bi would allow you to get a list of accounts and metrics that you capture. Ie acv, number of bugs, calculated nps. Agnetic flows allow you to mash this structured data with things like

• what is the sentiment of slack or support discussions with each client

• return me a summary of communications in the last qtr

• search the web and provide a summary of any news articles for my company.

This is what AI is unlocking today.