Let’s do it! 4 experts, 5 questions. Join ServiceNow’s Brian Solis, Tom Freeman, Rajeev Sethi, and Kelley Steven-Waiss to discover how you can #PutAIToWork for people with our intelligent platform.

Yes, generative AI is a BIG deal. Brian Solis, head of global innovation at ServiceNow, shares how every organization is going to have to reimagine their business for an AI-first world. Plus, get some practical examples of how AI can improve the customer experience (like giving people what they want before they even know they want it!). Take Brian’s advice and allow your curiosity to run wild — reply in the comments with creative ways you plan to use #GenAI.

Sometimes you have to see it to believe it. That was the case for Tom Freeman, a self-proclaimed generative AI skeptic and director of technical marketing here at ServiceNow. Tom sits down to answer questions about how genAI will impact developing on the Now Platform, the value of our large language model, and what’s coming next in this space. See it to believe it.

The consensus is in: Generative AI is a game-changer. Rajeev Sethi, VP of digital technology and emerging technologies at ServiceNow, discusses how genAI can improve KPIs across the business from employee satisfaction to mean time to resolution (MTTR). Now, we turn the question to you — what are some ways your workplace is using generative AI?

AI isn’t new to ServiceNow — we’ve been innovating in the space for nearly a decade. ServiceNow’s Chief Transformation Officer Kelley Steven-Waiss shares how generative AI will help employees focus on the work that matters most, get the right insights, and take the right actions. Watch until the end for her personal favorite way to use Now Assist. Now it's your turn in the hot seat — Have you discovered any innovative uses of AI at work? Drop your knowledge in the comments.

For a long time, the domains of Machine Learning and AI on one side, and software development on the other side, were separate kingdoms. Sometimes, they touched, and something magical would happen. But more often, things didn’t really work out. They faced challenges stemming from a lack of mutual understanding, shared language, and compatible tools. With the meteoric rise and increased accessibility of powerful generative AI and LLMs, the need for collaboration to achieve real-world engineering and customer value has never been more vital.