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Fortune
Sheryl Estrada

Why building a strong data culture is key to AI strategy

(Credit: Graham Uden/FORTUNE)

Good morning. AI feeds on data, but that data must be robust and reliable. For companies, managing this process effectively isn’t easy. But it can help to build a strong data culture—getting everyone on the same page when it comes to using data responsibly, including in a way that protects privacy. 

During the Fortune Brainstorm AI Singapore conference on Tuesday, experts shared their insights on the topic. Geraldine Wong is the group chief data officer of GXS Bank, a Singapore-based digital bank, launched in August 2022. She played a pivotal role in building the data culture. Wong found that employees joining the company needed guidance in that area. 

“Being able to assess their level of maturity was very important for us,” she said during a panel session. Wong created an operating model to answer questions such as: What does the data team actually do? What are some of the use cases that we have seen in the past being adopted? How can it help you? What does data responsibility mean? How do we approach governance?

The company implemented data visualization software tools for employees to have hands-on experience. What Wong discovered in the process is that employees “have trust in the data that they see,” she said. “Expanding it into a dashboard and visualization is what helps the users create use cases,” Wong said. 

Panelist Satyen Sangani is the cofounder and CEO of Alation, a data intelligence platform provider, based in Redwood City, Calif. Culture is effectively a set of habits and behaviors that exist within any organization, and incentives can be helpful, Sangani said. “You really want to build in immediate rewards,” he said. The best companies tie their outcomes to value very quickly, he added. "The work that they do is often very clearly measurable and outcome-oriented, and the stories are very quickly socialized,” he explained. 

Another aspect of building a robust data culture is tying it to the most important problems of the business, Sangani said. “It's the ones that executives care about the most,” he said. “And often we find that data teams forget about this. They just work on the data problems that are most interesting.”

CFOs are working toward using AI for data-driven decisions as part of long-term strategies and exploring how generative AI can create value. There are a lot of companies considering the use of gen AI tools just for specific tasks, Wong said. However, she predicts the use of the technology will eventually expand to transform the entire workflow process across an organization.

“We're so early in terms of understanding what use cases are appropriate, how these models can be used, how to tune them appropriately, what the right prompts are,” Sangani said. “There's a lot to do, and I think, just tons of excitement in front of us.”

Sheryl Estrada
sheryl.estrada@fortune.com

Quick note: You'll be hearing from my Fortune colleagues over the next few days in CFO Daily. Take care.

The following sections of CFO Daily were curated by Greg McKenna.

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