Why You Care
Ever feel like you spend more time preparing for a meeting than actually having it? What if an AI could cut that prep time dramatically? OpenAI, a leader in artificial intelligence, faced this exact challenge with its rapidly expanding sales team. They found a approach right within their own system. This internal creation is not just about efficiency; it’s about giving you back valuable time. It also ensures your customers receive faster, more informed responses. This approach could redefine how your own teams operate.
What Actually Happened
OpenAI has successfully deployed an internal AI tool called GTM Assistant. This assistant is built directly on OpenAI’s automation system, as detailed in the blog post. The company’s go-to-market team experienced rapid growth, tripling in size in less than a year. This expansion, coupled with frequent new product launches, created significant pressure on existing systems. Sales representatives were spending up to an hour preparing for a thirty-minute call. This involved navigating dozens of different systems to gather necessary context. What’s more, customer inquiries flooded subject matter experts, slowing down deal progression. The GTM Assistant was specifically designed to address these essential friction points. It integrates seamlessly into daily workflows, primarily through Slack. The goal was to reduce preparation overhead and centralize product knowledge effectively.
Why This Matters to You
This isn’t just an internal success story for OpenAI; it offers valuable lessons for your business. Imagine your sales team gaining an extra day each week. This is exactly what OpenAI sales reps are experiencing, according to the announcement. The GTM Assistant focuses on two key areas. First, it streamlines customer research and preparation. Second, it provides product Q&A. This means your team can access account history, call notes, and release updates instantly. It also provides answers sourced from a curated knowledge base. These answers include traceable links to primary documents. This ensures accuracy and builds trust.
Think of it as having a highly efficient research assistant always at your fingertips. “The advancement was training it on what a successful meeting looks like. Now it acts as an always-on teammate, driving better customer outcomes and a smoother day-to-day for our teams,” the team revealed. This directly translates to better customer interactions for you. Faster, more informed responses lead to happier clients and quicker deals. How much more productive could your team be with a similar tool?
Here’s a snapshot of the impact:
- 22 messages a week exchanged with GTM Assistant per average sales rep.
- 20% lift in productivity, equivalent to one extra day per week.
- Faster resolution of customer questions.
- Sharper, data-backed meeting starts.
The Surprising Finding
The most surprising element of this deployment wasn’t just the time saved; it was the method of betterment. The advancement wasn’t merely automation. It was capturing the expertise of top salespeople and scaling it across the entire organization. Top reps actively collaborated with GTM Assistant, shaping what ‘great’ looked like, as mentioned in the release. Their direct input trained the system. Every evaluation and correction didn’t just refine the AI; it embedded the best practices of successful sellers into the tool. This challenges the common assumption that AI tools are built in isolation by developers. Instead, it highlights the essential role of human expertise in refining AI for practical use. Scotty Huhn, GTM creation, stated, “We were constantly going back and forth on what does good look like here, really inspecting responses and operationalizing ‘good’ inside of our system.” This hands-on, iterative approach built trust and made reps designers, not just users.
What Happens Next
With trust firmly established, the GTM Assistant is already moving into its next phase. The team revealed that it is piloting new capabilities. These include logging CRM updates automatically after calls. It will also proactively spot noteworthy usage patterns. What’s more, it will draft customer follow-ups for automated sending. This means tasks that once consumed hours will begin to happen in the background. For example, imagine a sales rep finishing a call, and the AI automatically updates the CRM and drafts a personalized follow-up email. This could save hours every week. The industry implications are significant. This model suggests a future where AI acts as a true ‘virtual coworker,’ as Huhn described. It continuously reskills and adapts. Companies should consider how their own AI strategies can incorporate similar feedback loops. This will ensure their tools genuinely reflect the best human practices. Expect to see these features roll out more broadly in the coming months.