Enterprise AI: Time to Get Practical

Ronnie Sheth, CEO of SENEN Group, a company specializing in AI strategy, execution, and governance, highlights how many companies approach AI without adequate data preparation. According to Sheth, this is a mistake that can compromise the entire project.

"I've noticed that companies jump into adopting AI before they're ready," says Sheth. Often, company management pushes for AI adoption without a clear roadmap, leading to unmeasurable results.

The Importance of Data

SENEN Group focuses on helping companies solve data-related problems. "When companies come to us, the first order of business is really fixing their data," explains Sheth. "The next step is getting to their AI model. They are building a strong foundation for any AI initiative that comes after that."

Once the data is in place, companies can develop as many AI models as they want and get accurate outputs. Sheth cites the example of a customer who initially wanted data governance but actually needed a data strategy.

From Strategy to Implementation

SENEN Group helped this customer move from raw data to descriptive analytics, then to predictive analytics, and finally to defining an AI strategy. Sheth emphasizes that now is the time to get practical with AI, especially in enterprise adoption, focusing on obtaining value and concrete results.