What’s blocking enterprise AI agents?

Hello, and welcome to this episode of our Analyst Angle series. I’m your host, Shelley Kramer, Principal Analyst here at theCUBE Research. And today we are going to dive right into a topic that is top of mind across organizations as they realize the next step on the enterprise AI front is agentic AI. And they’re planning for significant investments in AI agents. I’m joined for this conversation today by Tray.ai CEO, Rich Waldron, who is tackling that problem head-on. Welcome, Rich. I’m so glad to have you.

Thank you for having me. Great to be here.

Absolutely. Absolutely. So an industry focus on agentic AI is beginning to boom, and of course, with good reason. When today it seems as though every app is AI enabled and the tech stack cannot be any more complex than it is, integration can be a bear and competing stakeholder priorities are also a reality in this equation. And siloed approaches and single purpose products inevitably lead to challenges with governance and vendor lock-in and, you know, I noted that Forrester predicted that 75% of firms that build agentic architectures on their own will fail. That’s an attention getter. And that’s where a scalable integration platform can play an outsized role. And that’s exactly what we’re going to explore today. So Rich, I’m so excited to have you.

Before we dive into this conversation, though, I would love for you to share a little bit about your career backstory and kind of your journey and how you made it to Tray.ai.

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You know, I love the honesty of that answer and the naivete. My favorite dad line, and I use it often, is, we don’t know what we don’t know until we know. And, right? You go into this, you bring your enthusiasm and your ambition and your drive. And then, you know, and the other thing I’m always grateful for is that I happen to be wired in such a way that I love solving problems. So, you know, so sometimes that naivete is a good thing because, you know, you sort of go in with a clean slate. You realize you don’t know what you don’t know. Then you know. And then you start figuring it out. So, I love that.

So, I know that Tray.ai recently did a survey called the state of AI agent development strategies in the enterprise. You surveyed over 1,000 enterprise tech leaders and practitioners. And the research showed, not surprisingly, that data management, security, and complexity all play a role in the ability for enterprises to capitalize on the real benefits that AI can deliver. Rich, I know that many enterprises are recognizing AI agents as, you know, really the value driving next step in AI innovation. But your study showed that 86% of those survey respondents shared they require upgrades to their existing tech stack in order to be able to deploy those AI agents. What do AI agents require that organizations don’t have today in their existing structure?

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Yeah. So solving for that on the front end of it is incredibly important.

Oh, for me, it’s probably one of the most important challenges because you can have the smartest AI in the room. But if you don’t, if you’re starving it of data and you’re starving it of the thing that it needs to go and respond to, then you’ve already kind of hamstrung its capability.

Yeah, absolutely. I know that your survey showed that almost half of enterprises, about 42%, reported that they need access to eight or more data sources to deploy AI agents successfully, among other widespread integration challenges, including security. So we talked a little bit about some of the challenges specific to integration. What are some other pressing challenges you’re finding enterprises are struggling with right now?

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Yeah. Yeah. I think there’s a nuance to that as well, which is the, you know, the historical solution to that problem was go a bit slower, right? Pick a well-known trusted vendor, run a long implementation process. Right. But there’s now this fear that, oh, we’re going to be left behind. Yeah. If we don’t move quickly, if we don’t take advantage of this technology, or if our competitor figures out how to deploy a customer support agent that accelerates the way that they can handle their overall customer experience, and we don’t, what does that mean for our business? So I do feel like it’s put a lot of pressure on organizations to be able to start getting into a place where they are comfortable adopting technology in a quick manner. Obviously, safety and security is absolutely paramount. But the way that you draw up those guardrails is really, really important.

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Well, you know, speaking of the need for speed, your survey showed the majority, I don’t know, maybe 60 plus percent of the respondents want to deploy agents in no longer than three weeks. And this is to your point, this is, you know, really shortening that cycle that we’re kind of accustomed to. So what is Tray doing to make this possible for customers? And I know you’ve developed the Merlin Agent Builder and Tray Agent Accelerator. So walk me through a little bit of what those solutions are and how they’re designed to help solve for this.

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Right. Absolutely. You know, and you mentioned the importance of iPaaS, and really I know that iPaaS is really kind of a strategic asset these days. So how do you see the role of iPaaS evolving in AI adoption? And do you think we’re going to see a greater reliance on iPaaS?

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I love it. I love it. So one of the things that is a reality is that AI is driving up data volumes and it’s requiring better management of unstructured data. And I don’t know an organization out there that’s not focused on and trying to get arms around data management, structured data, unstructured data, all of this. But specific to unstructured data, why is it so important for modern platforms to have unstructured data handling capabilities? How are you helping solve for this with customers?

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Yeah, absolutely. And can I talk you into sharing a customer use case story or two with us?

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Yeah, I love it. Well, as we wrap, it’s obvious that we’re at a transformational time, and it’s incredibly exciting. And while the development and deployment of AI agents is a high priority, I think the most significant need is the ability of an organization to create an AI-ready environment. Break down those silos, unify fragment approaches, streamline complex workflows, and provide a foundation. You know, it’s kind of like building a house, right? You got to get the foundation right. Well, you want to build on AI, you got to get the foundation right in order to have AI success at scale.

Rich Waldron, thank you so much for joining me today. It sounds like Tray is bringing the right solutions to the enterprise table at the right time. I’ve so enjoyed our conversation today, and I appreciate you making time for it. Thank you, Shelley. It’s been a pleasure. Absolutely. To our viewers and listeners, I’m your host, Shelley Kramer. Thanks so much for joining us for this conversation today, for joining us on theCUBE, your source for enterprise and emerging tech news. We’ll see you next time.