NVIDIA Automates Expertise with ChatGPT Work

Artificial intelligence (AI) is transforming the way companies like NVIDIA operate, and one key area of improvement is in automating expertise. The tech giant has been leveraging OpenAI’s ChatGPT Work to streamline its workflows, connect fast-moving signals, and scale successful processes globally.

NVIDIA teams use ChatGPT Work to reduce manual tasks, which previously consumed a significant amount of time. For instance, during the planning cycle for NVIDIA’s global AI conference, GTC, the company saved about 16 hours per week by automating certain tasks using ChatGPT Work. This not only freed up resources but also enabled teams to focus on more critical aspects of their work.

The benefits of using ChatGPT Work are multifaceted. For one, it helps knowledge workers spend less time assembling information and more time acting on it. Teams like GTM (Global Technical Marketing) and solutions architecture have incorporated ChatGPT into their workflows, transforming recurring operational processes and connecting fast-moving external developments with NVIDIA’s internal priorities.

Will Daney, who helps NVIDIA’s global sales, business development, and product leaders execute and measure their strategies, is a prime example of how ChatGPT Work has made a significant impact. 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.

Will estimates that manual analysis consumed about 40% of his time during the lead-up to the event. However, he has since turned much of this work into an automated ChatGPT Work process that runs twice a week. This not only saves him time but also allows him to adapt the workflow as needed without waiting for new tools to be purchased and implemented.

The flexibility offered by ChatGPT Work is one of its most significant advantages. Will can share his workflows with teams in other regions, who can then customize them according to their local needs. This has been particularly useful for events held in San Jose, Taipei, Europe, and Washington, DC, where colleagues have received and adapted Will’s workflows.

Rachita Jain, who works on the AI operations team within NVIDIA’s marketing organization, faces a similar challenge: keeping pace with an industry where new models, benchmarks, and research appear every day. The information is readily available, but determining which developments matter to NVIDIA and connecting them with internal projects, conversations, and priorities requires significant effort.

Rachita built a workflow with ChatGPT Work that reviews trusted external sources alongside internal context, identifies meaningful areas of overlap, and surfaces insights that can inform action. Each week, it distills roughly 25-40 external AI updates into 5-8 actionable signals. This has been instrumental in helping her teams stay on top of the latest developments and make informed decisions.

The same environment supports the broader building process. Rachita can begin with an idea, explore possible approaches, work through a codebase, debug problems, and refine the result without continually moving between disconnected tools. Initiatives that might once have remained side projects can develop into working products within days.

In one case, she moved from idea to working prototype in about 3-5 days, compared with an estimated 2-3 weeks if she had built the components manually across separate tools. This not only saves time but also enables teams to focus on more critical aspects of their work and collaborate more effectively.

The next opportunity is to scale what’s already working by turning specialized knowledge into reusable workflows. Teams across NVIDIA can adapt proven processes across functions, events, and regions while keeping those closest to the work in control of how those processes evolve. This will help connect external developments with internal priorities more quickly and extend AI-enabled ways of working to more employees.

The goal is to give teams more time to interpret findings, collaborate, and focus on work that supports customers. As Will puts it, ‘ChatGPT has really been a force multiplier for me personally.’ It feels like he has a team working for him, allowing him to get out of the weeds and focus more on the work that matters.