What Are Your Thoughts on AI for BI?

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Rebecca Griifin

Updated 2 days ago in

I’m curious to hear your thoughts on AI features in BI tools. I’ve been exploring options like Tableau and Power BI — especially their natural language query functions. Has anyone here actually used these? Are they true time-savers or more trouble than they’re worth?

For instance, Tableau’s Ask Data seems handy for quick visualizations, but I’ve heard it sometimes misses key filters, like specific years. Power BI’s Q&A feels a bit more responsive, especially for things like “sales by region in 2022.” I also came across FineBI’s new AI Q&A feature — seems beginner-friendly for self-service data prep. Anyone given it a try? How does it stack up?

Would love to know — are these AI features genuinely helpful, or do they still require too much oversight? And are there any other BI tools with solid AI capabilities you’d recommend?

Looking forward to your insights!

I’m curious to hear your thoughts on AI features in BI tools. I’ve been exploring options like Tableau and Power BI — especially their natural language query functions. Has anyone here actually used these? Are they true time-savers or more trouble than they’re worth?
For instance, Tableau’s Ask Data seems handy for quick visualizations, but I’ve heard it sometimes misses key filters, like specific years. Power BI’s Q&A feels a bit more responsive, especially for things like “sales by region in 2022.” I also came across FineBI’s new AI Q&A feature — seems beginner-friendly for self-service data prep. Anyone given it a try? How does it stack up?
Would love to know — are these AI features genuinely helpful, or do they still require too much oversight? And are there any other BI tools with solid AI capabilities you’d recommend?
Looking forward to your insights!

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Maha Sarhan 2 days ago

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.

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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 
<ul> 
<li> 
what is the sentiment of slack or support discussions with each client 
</li> 
<li> 
return me a summary of communications in the last qtr 
</li> 
<li> 
search the web and provide a summary of any news articles for my company. 
</li> 
</ul> 
This is what AI is unlocking today.

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