NVIDIA teams use ChatGPT Work to reduce manual tasks, connect fast-moving signals, and scale successful workflows globally.

Hours saved per week using ChatGPT Work during the GTC planning cycle

Days to create a working prototype with ChatGPT Work, compared to 2–3 weeks previously

Actionable signals surfaced per week by ChatGPT Work from 25–40 external AI updates

At NVIDIA, ChatGPT Work is helping knowledge workers spend less time assembling information and more time acting on it.

For teams like GTM and solutions architecture, ChatGPT has become part of how work gets organized, automated, and scaled. For GTM, it transforms recurring operational processes, while solutions architects are using it to connect fast-moving external developments with NVIDIA’s internal priorities.

Will Daney helps NVIDIA’s global sales, business development, and product leaders execute and measure their strategies. One of his recurring responsibilities is supporting the field organization around GTC, NVIDIA’s global AI conference.

Previously, preparing for GTC required extensive work in spreadsheets: assembling account lists, tracking registrations, and helping teams identify the actions needed to create a productive experience for customers and partners. During the lead-up to the event, Will estimates that manual analysis consumed about 40% of his time. Today, he has turned much of that work into an automated ChatGPT Work process that runs twice a week. Across the 12-week GTC planning cycle, the workflow saves about 16 hours per week.

“I’m able to give time back, work with the actual field team, get to know them better, and help them figure out how to help our customers be more successful,” Will says.

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