8legs: Mit

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Defining An Intelligent Business

Panel links building an intelligent business to easy, fast access to needed insights across an organization.
Experts stress data strategy as the prerequisite for an AI strategy, not the other way around.
Panelists warn data is often fragmented, requiring a semantic layer to decode information for users.
Conversations emphasize moving from reactive reporting to proactive execution using data.
Snowflake and Thoughtspot representatives discuss the data foundation needed to support AI across functions.
Panel highlights human factors, urging boards to be AI-literate and avoid rushed, vague goals.
Experts advocate starting with high-value use cases and gradually scaling with governance.
Semantics and data context are viewed as critical for end users to access relevant information.
Panelists note AI should automate dull decisions to free humans for higher-impact work.
The discussion situates intelligent business within a broader context of data quality and governance.

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