在NVIDIA，ChatGPT Work正帮助知识工作者减少收集信息的时间，将更多精力投入到实际行动中。
对于GTM（市场进入）和解决方案架构等团队而言，ChatGPT已成为工作组织、自动化和规模化运作的一部分。对GTM团队来说，它改变了重复性的运营流程；而解决方案架构师则利用它将快速变化的外部动态与NVIDIA的内部优先事项连接起来。
释放团队精力，聚焦客户
Will Daney帮助NVIDIA的全球销售、业务拓展和产品领导者执行并衡量其战略。他的常规职责之一是为GTC（NVIDIA全球AI大会）相关的现场团队提供支持。
此前，GTC的筹备工作需要大量使用电子表格：整理客户名单、跟踪注册情况，并帮助团队确定为客户和合作伙伴创造高效体验所需的行动。在活动筹备期间，Will估计手动分析约占其时间的40%。如今，他已将大部分工作转化为自动化ChatGPT Work流程，每周运行两次。在12周的GTC规划周期中，该工作流每周节省约16小时。
“我能够把时间还给自己，与实际的现场团队合作，更好地了解他们，并帮助他们找到让客户更成功的方法，”Will表示。
由于他拥有该工作流的所有权，他可以根据活动变化进行调整，无需等待采购、实施和维护新工具。他还可以将底层流程分享给其他地区的团队。支持圣何塞、台北、欧洲和华盛顿特区活动的同事已收到他的ChatGPT工作流，并根据本地需求进行了定制。
“借助ChatGPT，我认为真正的关键在于，我能够将自己已经开发的工作流一次又一次地自动化应用到每场活动中，几乎零额外开销。”
——Will Daney，NVIDIA市场进入策略师
在快速发展的行业中捕捉关键信号
Rachita Jain在NVIDIA营销组织内的AI运营团队工作，负责构建AI工作流并帮助团队采用新工具。她面临的挑战是如何跟上这个每天都有新模型、基准测试和研究出现的行业节奏。
信息随处可得，但更困难的任务是判断哪些动态对NVIDIA至关重要，并将其与内部项目、讨论和优先事项联系起来。Rachita使用ChatGPT Work构建了一个工作流，该工作流在审查可信外部来源的同时结合内部背景信息，识别有意义的交叉领域，并提炼出可供行动参考的洞察。每周，它将约25至40条外部AI动态提炼为5至8条可操作的信号。
“ChatGPT帮助我将被动阅读转变为主动情报，”她说。
同一环境还支持更广泛的构建过程。Rachita可以从一个想法出发，探索可能的方案，处理代码库，调试问题，并优化结果，而无需在互不关联的工具之间来回切换。那些曾经可能只是副业项目的计划，如今可以在几天内发展成可用的产品。在一个案例中，她从想法到工作原型仅用了约3至5天，而如果她使用分散的工具手动构建各组件，预计需要2至3周。
“我认为我要解决的最大问题是信息过载，因为一切变化太快了。要跟踪所有变化变得越来越困难。而借助ChatGPT，这一切变得简单得多。”
——Rachita Jain，NVIDIA解决方案架构师
未来展望
下一个机遇是将已经奏效的方案规模化推广。通过将专业知识转化为可复用的工作流，NVIDIA各团队可以在不同职能、活动和地区之间应用经过验证的流程——同时让最贴近实际工作的人员掌握这些流程的演进方向。
随着AI格局的持续变化，这些共享工作流可以帮助NVIDIA更快地将外部动态与内部优先事项连接起来，并将AI驱动的工作方式扩展到更多员工。目标是让团队有更多时间解读发现、协作，并专注于支持客户的工作。
这一潜力已在Will的经历中显现。“ChatGPT对我来说确实是一个力量倍增器，”他说，“感觉就像有一个团队在为我工作。它帮助我摆脱琐碎事务，更专注于真正重要的工作。”
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.
Freeing teams to focus on customers
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.
And because he owns the workflow, he can adapt it as the event changes without waiting for a new tool to be purchased, implemented, and maintained. He can also share the underlying process with teams in other regions. Colleagues supporting events in San Jose, Taipei, Europe, and Washington, DC have received his ChatGPT workflows and customized them for their local needs.
“With ChatGPT, I think the real key is that I’m able to take a workflow I’ve already developed and I’m able to automate it event over event with little to no overhead.”
—Will Daney, Go-To-Market Strategist at NVIDIA
Finding the signal in a fast-moving industry
Rachita Jain works on the AI operations team within NVIDIA’s marketing organization, where she builds AI workflows and helps teams adopt new tools. Her challenge is keeping pace with an industry where new models, benchmarks, and research appear every day.
The information is readily available. The harder task is determining which developments matter to NVIDIA and connecting them with internal projects, conversations, and priorities. 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.
“ChatGPT helped me change passive reading into active intelligence,” she says.
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.
“I think the biggest problem I’m trying to solve is information overload, because everything is moving so fast. It’s getting harder by the day to keep track of all the changes. And with ChatGPT, it becomes much simpler.”
—Rachita Jain, Solutions Architect at NVIDIA
What’s next
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 the people closest to the work in control of how those processes evolve.
And as the AI landscape continues to change, these shared workflows can help NVIDIA 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.
That potential is already visible in Will’s experience. “ChatGPT has really been a force multiplier for me personally,” he says. “It feels like I have a team working for me. It’s helped me get out of the weeds and focus more on the work that matters.”
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