S&P Global is gearing up for a future where the primary consumer of its vast data resources will not be humans, but artificial intelligence acting on their behalf, a senior company executive said.
"We are designing for a world where AI will increasingly be the interface between humans and our data," Dan Bennett, head of Data Technology, Enterprise Data at the US-based company told ET. "Historically, it's been humans directly accessing our data. We believe AI is going to be the tool humans use to do that."
Bennett leads S&P Global's new Enterprise Data Organization (EDO), launched on January 1 this year to centralise and standardise how data is processed and distributed across all divisions of the financial information, analytics and credit ratings provider. The majority of EDO staffers are located in India, in cities like Ahmedabad, Hyderabad, Bengaluru, Noida and Gurugram.
"Every one of our divisions, whether it's ratings, market intelligence, or commodities, was doing data collection and distribution in its own way. Now, we have one group doing it for all, so we can make that data truly AI-ready," he said.
The aim is to make it easier for large language models (LLMs) to connect with S&P Global's structured datasets, Bennett said. "Most of the data we create is numerical and tabular, and LLMs don't train on that," he explained. "They process text, not numbers. So, our mission is to help AI understand our data by adding layers of context and semantics." One way the company is doing this is through its Open Data programme and metadata marketplace, which Bennett described as 'giving AI the language it needs to talk to our data".
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"We are designing for a world where AI will increasingly be the interface between humans and our data," Dan Bennett, head of Data Technology, Enterprise Data at the US-based company told ET. "Historically, it's been humans directly accessing our data. We believe AI is going to be the tool humans use to do that."
Bennett leads S&P Global's new Enterprise Data Organization (EDO), launched on January 1 this year to centralise and standardise how data is processed and distributed across all divisions of the financial information, analytics and credit ratings provider. The majority of EDO staffers are located in India, in cities like Ahmedabad, Hyderabad, Bengaluru, Noida and Gurugram.
"Every one of our divisions, whether it's ratings, market intelligence, or commodities, was doing data collection and distribution in its own way. Now, we have one group doing it for all, so we can make that data truly AI-ready," he said.
The aim is to make it easier for large language models (LLMs) to connect with S&P Global's structured datasets, Bennett said. "Most of the data we create is numerical and tabular, and LLMs don't train on that," he explained. "They process text, not numbers. So, our mission is to help AI understand our data by adding layers of context and semantics." One way the company is doing this is through its Open Data programme and metadata marketplace, which Bennett described as 'giving AI the language it needs to talk to our data".
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