Going to Market: Selling AI to Enterprises
- Date
- 2025-12-02
- Location
- New York, NY, USA
- Host
- Runway
About this event
Selling AI into large organizations is rarely a simple product demo followed by a fast yes. Enterprise buyers move carefully, expectations are high, and the gap between technical possibility and business adoption can be wider than most founders expect. This meetup is built for people who want a sharper, more realistic view of what it actually takes to bring AI products into enterprise environments. About the Event This is an in-person meetup in New York focused on a practical question: how do you go to market with AI when your customer is an enterprise? The conversation will center on the real work behind selling AI, from positioning and trust-building to navigating long buying cycles, internal stakeholders, and procurement realities. The event is designed as a community gathering for people building, selling, advising, or exploring AI products in serious business settings. Rather than treating enterprise sales as a vague black box, the goal is to create a space for grounded discussion about what works, what breaks, and what teams need to understand before they scale. Expect a format that supports both learning and connection. This is not just about hearing ideas; it is also about meeting other people facing similar questions around autonomy, adoption, product-market fit, and enterprise decision-making. What to Expect You can expect an evening built around focused conversation and high-signal networking. The theme suggests a strong emphasis on the commercial side of AI: how products are framed, how trust is earned, and how companies move from interest to actual deployment. Topics likely to come up include: Positioning AI for enterprise buyers who care about outcomes, reliability, and risk Translating technical capability into business value that non-technical stakeholders can understand Selling products with autonomy features in environments that require control, oversight, and accountability Handling long sales cycles and the internal complexity of large organizations Learning from peers who are building in AI and navigating similar go-to-market challenges Because this is a meetup, the value will come not only from the formal discussion but also from the side conversations before, during, and after the main session. If you have been looking for a room where people understand both the promise and the friction of enterprise AI adoption, this is that kind of setting. There is also a strong community angle here. You should expect candid exchanges, practical questions, and the chance to compare notes with founders, operators, and builders who are working through enterprise AI strategy in real time. Why Attend If you are building an AI company, one of the hardest problems is often not the model or the product itself. It is figuring out how to sell in a market where buyers are curious but cautious, budgets are meaningful but guarded, and every claim needs to stand up to scrutiny. This event is useful because it focuses on that exact challenge. You will leave with a clearer sense of how enterprise customers think about AI purchases and what they need to feel confident moving forward. That may include a better understanding of messaging, objections, internal champions, and the kinds of conversations that help move deals from exploration to commitment. This meetup is also valuable if you want better pattern recognition. Hearing how others approach enterprise selling can help you avoid common mistakes, sharpen your go-to-market narrative, and identify where your current strategy may be too technical, too broad, or too early for the buyer you are targeting. Just as important, you will meet people in the same arena. The right conversation can help you pressure-test your sales approach, validate assumptions, and build relationships with peers who understand the realities of selling AI beyond the hype cycle. Practical Details The event takes place in person in New York, USA on Tuesday, December 2 at 5:30 PM EST. Being in person matters for this topic: enterprise go-to-market conversations tend to get more useful when people can speak directly, ask follow-up questions, and continue the discussion informally. The early evening timing makes this a strong fit for founders, operators, sellers, and product leaders who want to plug into the AI community after the workday. Plan for an environment where both structured discussion and open networking are part of the experience. If this topic is close to your day-to-day work, come ready to engage. Bring your questions about enterprise adoption, sales friction, buyer psychology, pricing conversations, pilots, procurement, or how autonomy changes the sales motion. The more specific your perspective, the more useful the room will be. This event is especially well suited to people who want substance over surface-level AI talk. If you care about how AI products actually make their way into enterprise organizations, this meetup will give you a better lens on the challenge and the people working through it.
Who should attend
This is for you if you want a more practical understanding of how AI products get sold, evaluated, and adopted inside large organizations. - **You are a founder or startup operator** building an AI product and trying to figure out how to sell into enterprise customers with confidence and clarity. - **You work in go-to-market, sales, or business development** and want better language, sharper positioning, and stronger instincts for enterprise AI conversations. - **You are a product or technical leader** who needs to understand how enterprise buyers think about trust, risk, control, and deployment readiness. - **You are building around autonomy or agent-like workflows** and want to learn how those capabilities are received in enterprise settings where oversight matters. - **You advise, invest in, or support AI companies** and want a closer look at the commercial realities behind enterprise adoption. - **You value meeting thoughtful peers in person** and want to trade notes with people working on the same go-to-market problems, not just talking about AI in the abstract.