Ravi Malick40:59
Interesting. So I have a viewpoint and then there's what I glean from conversations, but my viewpoint is very bullish on it. I think it is, AI, particularly Generative AI, does have a long term potential to really change the way that we do work and how work gets done. I think it has an immense positive outlook. The positive outlook is very strong in terms of its ability to scale, and this is, mentioning earlier, I'm very focused on scalability, I think that opportunity is pretty sizable there. I think we've got some time that it's gonna take to get there. The conversations that I have, and this is, I would share this viewpoint, is where is the enterprise value? How am I generating competitive difference? Almost universally, CIOs and leaders that I talk to have come to the opinion of, hey, the ChatGPT and the CoPilot and that stuff for the digital assistant, personal assistant, it's cool, it's interesting, and I get some productivity uplift, but what's next? What is gonna drive much larger value, much more quantitative value? I think we've seen the areas where, in code development we certainly have seen value there in some of the customer or user interactions and resolving issues, one click resolution, self service. We've certainly seen an uplift there, and I think that's where most people are looking. There are some other pockets of areas, maybe in marketing, writing copy, campaigns, those kinds of things. They have value, but I think people are looking for how do I really change my business? That's changing pockets. It's maybe turning the dial a little bit, but like, how do I really scale up? How do I get to this point of driving transformative change? And I think when you talk about AI agents and the workforce, and what does that future look like? Maybe that is something that is possible in the next few years. If I need to execute on a marketing campaign and I want to do outbound email and calls and messaging and targeted messaging, maybe I have the ability to spin up an AI agent workforce that goes and does that and handles that. When you think about some of the manual intervention points in processes, maybe there's an AI agent that can handle that, and you are starting to see some of that where we obviously see the future, because unstructured data and content is a fuel for Generative AI. And that's where the value's gonna be generated, is managing that, articulating, hey, here's the value, having an architecture that's flexible, that allows you to expose AI capabilities into your existing technology stack and leverage the model ecosystem. I think that's incredibly important. And to get back to some of the earlier points I made around architecture and having that flexibility and understanding how that's gonna work, the challenge a lot of us have are, everybody is coming out with their AI flavor, everybody's got an AI component, typically it's focused on that area, whatever that application is focused on, whether it's sales or marketing or HR or customer service. I want something that is gonna drive value across all areas. I want an architecture and this is where Box AI comes into play. I want architecture where I can leverage my existing investments. I have the governance and I have the level of control and understanding, and flexibility around security. The security of my data. I know that it's secure externally, it's not being used to train models that can be used by my competitors. I know that internally the access management controls are being respected. And people have access to what they should have access. They don't all of a sudden have access to data that they wouldn't have. Those things are super important to most CIOs. And so you see in this area, a lot of companies are building their own platforms. Because I think that there's still the viewpoint on risk associated with using somebody else or having multiple versions or flavors in your environment is still pretty bearish right now. And so where we feel like we can make a difference is being able to provide our customers that solution that gives them the ability to safely experiment with AI, that gives them the scalability to expose through APIs into their existing technology stack, to be able to leverage the best of breed of LLMs. I personally think that kind of flexibility in your architecture is essential because this is a market that's changing. It's moving and you're gonna see consolidation, companies that were built on ChatGPT 3, 3.5, the next version comes out and they're gone. They're irrelevant. So I look for a solution that's gonna give me a hedge to how fast it's moving to the consolidations that's gonna occur, but I can still continue to grow with.