Information Readiness, AI Maturity, and Customer Impact – Six Five On the Road

How are businesses leveraging information readiness and increased AI maturity to drive impactful marketing and customer engagement at scale?

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From OpenText World 2025, hosts Patrick Moorhead and Daniel Newman are joined by OpenText's Sandy Ono, EVP & Chief Marketing Officer, for a conversation on information readiness, AI maturity, and customer impact. They explore how OpenText is helping enterprises utilize AI to enhance marketing and sales engagement, citing practical use cases that are delivering real value, and the crucial role of information management in enabling these outcomes. The group also shares findings from recent CIO research, diving into the integration of AI assistants, contextual AI for content creation, balancing automation with human judgment, and industry perspectives on distinguishing real AI innovation from hype.

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Key Takeaways Include:

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🔹Information readiness as a critical factor: Organizations with solid foundational information management are seeing more value from AI implementations in marketing and customer engagement.

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🔹Practical AI use cases delivering ROI: AI is being leveraged for personalization, automation, and improved customer experience, with marketing teams using contextual insights to drive results.

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🔹Balancing automation and authenticity: Enterprise users are seeking ways to keep human judgment central while scaling efficiency through AI assistants and automation.

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Learn more at OpenText

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Or listen to the audio here:

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Disclaimer: Six Five On The Road is for information and entertainment purposes only. Over the course of this webcast, we may talk about companies that are publicly traded, and we may even reference that fact and their equity share price, but please do not take anything that we say as a recommendation about what you should do with your investment dollars. We are not investment advisors, and we ask that you do not treat us as such.

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Patrick Moorhead:

The Six Five is On The Road here in Nashville for Open Text World 2025. Daniel, we are talking about our two favorite things. One thing I know for sure, but another thing that we drill into a lot because it impacts AI, and that's getting your data management ready and making sure you have the information. to feed the agents to give you what you're looking for.

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Daniel Newman:

Yeah, it's been a big couple of years for AI in general. But I think what we're really seeing is this inflection now where enterprises have this challenge. There was a number in the presentation during the opening keynote where He said something like 90% of all the data sits behind the firewall. That's right. And with that volume of data sitting behind the firewall, it means that there's still so much ramp for growth for compute. There's still so much ramp for growth of how enterprises are implementing and applying AI. And I think that conversation is going to become a bit more thematic. You know, we're kind of past the LLMs and cute videos and pictures. And now there's this whole big world of enterprise AI out there.

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Patrick Moorhead:

There is, and I was at a CIO forum last week in London, and literally the conversation was primarily about data readiness. So anyways, we're at OpenText. I want to introduce Sandy from OpenText. Great to see you.

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Sandy Ono:

Good to see you, Pat. See you, Dan.

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Patrick Moorhead:

You're sporting the colors.

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Sandy Ono:

It's Nashville.

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Patrick Moorhead:

Yeah, I mean, we got a concert at the very beginning and the very end of the keynote. So thank you for that.

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Sandy Ono:

Of course. Well, when in Nashville, you got to do it the Nashville way. Yeah. So we bring a little fun into the show today. Yeah, for sure.

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Daniel Newman:

Us Austin guys, we should have been wearing our cowboy boots. I know I didn't even do that.

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Sandy Ono:

Cowboys still have a little bit of time.

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Daniel Newman:

We got one of those tiny sombreros. I wore it around the show.

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Sandy Ono:

You probably should. And, you know, where does it work? People are enjoying it. Yeah.

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Daniel Newman:

So one of the things I love is to put executives into the position to talk about their own book in a way and you lead marketing at a company that's out there selling the idea of putting AI to work in your business. Why don't we start there with your implementation and how you're thinking about using AI in your particular discipline at Opentex?

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Sandy Ono:

Yeah, great question. So I have the pleasure of leading all global marketing and partners and alliances here at Opentex. We have been utilizing AI as a tool for two years now, and really the genitive AI. I have three big use cases. First is in the creative realm. So we do most of our advertising creative cycles. Things that would take three months down to three days. We launched the whole OT brand about 18 months ago now. Doing that creative cycle and everything you see around the show from the aviator and navigators being animated now to them having voices, to having songs generated. Those have been our creative AI use cases. We also do this a lot in prospecting. So we have a BDR-SDR team. research being relevant to the customers. And then lastly, we're actually trying to transform what we do in sales enablement. So think about what we used to do in marketing to get all that content ready so sales can consume it. Now we just teach them to prompt. So really trying to change the paradigm a little bit there as well.

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Patrick Moorhead:

So, I think we've all experimented a little bit with agents, okay, not to be confused with LLMs, that could be one of the base technologies for an agent, but there's a lot of conversations about hewing in the loop. How do I balance authenticity, right, with all the other factors, with automation, right? We can do a lot of things quickly, but if we do a lot of things quickly and it's not accurate, then you get nowhere as an enterprise. How are you seeing your customers balance this?

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Sandy Ono:

Yeah, it's on twofold. One is we like to help our customers with what we call pretty mission-critical processes, right? Things that you don't normally want to get wrong.

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Patrick Moorhead:

I saw the 100% versus, eh, it's kind of sort of right most of the time.

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Sandy Ono:

Exactly, so sometimes 90% isn't good enough, right? So we really want to focus on this notion of accuracy and relevance for our customers. And a lot of that, as you guys were saying at the beginning, goes back to content that's probably hidden away in the depths and weeds of their organization and being able to actually either clean that up, curate it, and actually have it feed AI in the right way. Because as you guys know, AI is continuous, right? So it's not a once and done thing. So that accuracy part is really important for what we're helping customers with.

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Daniel Newman:

Yeah, that is such a big thing right now. I think there was a comment made in the keynote that being 90% accurate really doesn't do what it needs to do. And I think a lot of us that are in tech, Sandy, we play with it, and we're kind of OK to get a result. I know you and I do it all the time when we're looking at, say, financial results, or we're doing it when we're kind of trying to get a quick readout on a company's competitive landscape. But we also know there's more work to be done. I think as we really see enterprise AI turn on and get adopted, the expectation is going to be real autonomy. These things really can go end-to-end. It's error-free. It's accurate. It's checked its work, especially in things like where it's working on solving customer response cases or where it's making meaningful inputs to a spreadsheet that's going to get reported to the SEC. Things like that, if we're going to use AI, have a lot of work to do.

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Sandy Ono:

Absolutely, and I call this kind of the conundrum of false confidence, right? Because sometimes you're utilizing AI as a tool or in a role as an agent, and it seems confident. And I think the kind of us being able to discern what might be falsely confident or actually, and true enough, is where the human in the loop is still so important. Because that last 10%, sure, you can get the productivity out of it, but that accuracy, that's where I see the human in the loop.

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Daniel Newman:

I think there's a lot of work there. And so that's probably an interesting thing from a marketing standpoint, though, is most AI, it's kind of contextually unaware. It's generic. But what you guys are really talking about is bringing contextual awareness to it. In your space, in marketing, and partner, and the organization, all the places you're in, it's like, how are you seeing that contextual awareness layered in to deliver value?

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Sandy Ono:

Yeah, so a lot of, for example, what we do in marketing and sales is we have to be meeting the customers where they are, right? So that contextual awareness is not just, hey, let's be able to write that blog faster or generate that advertising faster. But the combination of deep research to then what you could generate faster, with some of the tools that's today, to actually bring in that context, right? So, in our language, customer research and customer insights have always been the heart of this, but now, how do we do this? So it's been a fascinating conversation last week around, well, is now, should we trust synthetic research? I know there's some doubt around synthetic data, but synthetic research, you know, if you have a person that, a bot, that impersonates what a potential prospect customer may respond to your piece of marketing, you know, is that part of our process now? So, I don't know. Dan, I think there's a lot to be discovered and there's a lot of processes that actually have to be redefined.

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Patrick Moorhead:

Yeah, so I think like every inflection we've seen, whether social, local, mobile, even web and e-commerce, there was a lot of learning that went in before, okay, we're on a track, we know what to do. There is no cookbook for precision here. I'm sure next year we might be talking about what's beyond agents. An agent of agents we'll probably be talking about here. So, in line with what you do, you must also be wondering, hey, when do I call something AI when I do my messaging? We don't want to be doing cloud washing. We don't want to be doing AI washing. What separates what's credible innovation from, let's say, a hype, and how are you balancing that?

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Sandy Ono:

Yeah, it's a really good question. I find that education and continuing to evolve is actually kind of the key, because everybody will interpret the words differently. So rather than trying to, you know, overcome that, for example, in AI or in agents, let's use agentic AI, right? We're not going to use the big AI word, agentic AI. Now we've been starting to talk about it as well, as it applied to a role, a process or a project. And I think that helps everybody say, okay, what are you really talking about? It was a task like six months ago, and now you're talking about, is it a role, a process, or a project? Okay, I can wrap my head around that. And I think that type of education internally, and then externally, and then putting what we do in the context of that is really important. You guys heard me say this morning on stage, we don't make LLMs. There's only like three or four companies in the world that make true large language models. We're not trying to be that AI, we're just trying to meet the customers where they are, which is combining data and application of AI to something practical.

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Patrick Moorhead:

It makes sense. I'm sure we're going to come up with a new term again in six months or a year, and I think that's okay. But I think in the end, the ultimate arbiter is going to be the customers and what they see. But the funny part about it is it depends on accuracy. It depends on what you want something to do. much smaller company than the clients you service. We have a lot of agents that are there running, and we have different thresholds for accuracy, depending on what we do.

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Sandy Ono:

Yeah.

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Daniel Newman:

We're definitely going to enter a world where the org is going to look different, right? Absolutely. you're going to have a team and you know an org chart used to be just people and then maybe it was like people and contractors but it was like now you're gonna have like people freelancers contractors and agents yeah and your org may be 80 90 agents at some point because They're so efficient, and obviously businesses realize productivity gains that comes out of it. Hopefully, there's still a lot to talk about in terms of what it means from an augment, displacement, replace, and jobs, but we should see productivity skyrocket. So many of the monotonous things that people didn't want to do, maybe they won't have to do anymore. We can put people towards higher thresholds and more fulfilling kinds of work. That's all really exciting. I mean, a lot of unknown. But I mean, in your space, like in B2B as a whole, you know, how do you think AI is going to sort of redefine the entire B2B marketing experience? Because I think that's probably one of the most interesting opportunities you have is, you know, by the way, I'll just throw something out there as a thinker, is like, do you have to, as a B2B CMO and leader, have to think about agents selling to agents in the process of actually eventually reaching to humans? Like for instance, you know, where's the first line going to be in the next few years?

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Sandy Ono:

I'll tell you what we've been talking about very proactively as a team. And so a couple of things on that front, right? One, I'll tell you the other paradigms that are out there. Your website, where you think customers have been going all these years is irrelevant. Right? And so while I believe it might take a little bit of time, just like I don't think SaaS applications will go away tomorrow, it's going to take some time. That user interface is changing. And at the heart of what marketing does is the customers, speaking to the customers, and customer behaviors are changing. That part is very much true. So how we have to evolve our processes, we're very proactively redefining What is customer acquisition? What is expansion and install base? What is retention of a customer? Rethinking what that process is, redefining the roles, and then mapping in a reorganization to that. It's very classic in how you think about software, but it's just different tech now. I was speaking to my team the other day. I'm like, the good news is the team, we've been talking about Martech for 20 years. So we actually kind of know what we're talking about, it's just different technologies. The hard part is, we can sit here and be like, hey, you know what? We should start an AI ops organization, and we need to have roles that are prompt engineering, and that's what we need because we don't need copywriters anymore. Well, you know, three months down the road, the tech evolves, and you don't need prompt engineers anymore because it's low-code, no-code. So it's moving at such a pace that if we don't continue to stay ahead of it, first of all, brands are going to become irrelevant because there is some truth that your website is uncontrolled. And the pace at which you actually have to do the harder work, the easier work is using it as a tool. The harder work is redesigning what you do.

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Patrick Moorhead:

It is interesting, you know, I've heard so many times, I mean, during social media, it was, hey, we don't need long form content, right? Social media is going to replace it all. And my response was always, am I going to make a $50 million decision based on what somebody says on LinkedIn? Probably not, but it's a vehicle to get there. In the same way, what comes back from an agent, am I gonna make that $50 million decision based on what the agent says? Probably not. Actually, probably not. The answer is gonna be no. For high value, you're gonna wanna talk to somebody. And that's until, this is my thesis, until, as Daniel talked about, agents are buying from agents. And then I think things change, but, is somebody going to enable an agent to make a $50 million purchase decision and commitment? It's probably going to be probably a while. It depends on how much inflation goes up.

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Daniel Newman:

That might not be that much.

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Sandy Ono:

Well, and it's also, that's always been the fun of B2B tech, right? At some point, because of what we're talking about, both because it has to be implemented to thousands of people, that piece of technology, and also the dollar threshold on which it's at, it is hard to say what it is. In my half of the world, in the top funnel, yeah, it's absolutely going to change how we work. We're paying attention to AI overviews like it's tomorrow. We have to think about GEO, not SEO, only SEO. And the world's going to shift because the customers are shifting.

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Daniel Newman:

Makes sense. Well, that was a lot of fun, Sandy. I really appreciate you sitting down with us here at your event. I know when you're running and leading an event and as many like seven orgs or whatever it is that you're leading a big role, a lot of us really you're probably running crazy here. So hopefully a lot of customers, a lot of great conversations, you know, really solid support, but definitely enjoyed the keynote today. We think what you're doing is something that's very important that probably needs even more conversations and momentum over these next few years, because again, so much attention was on models and yeah, create a video. And, but I mean, in the future, really this technology enabling businesses to get economic, meaningful growth, that 20 trillion plus number we keep hearing about, it's going to start with that 90% data that sits behind the firewall and how we put it to work.

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Sandy Ono:

Absolutely. Thanks so much for having me.

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Daniel Newman:

Thank you. And thank you everybody for being part of this. We're at Open Text World 2025 here in Nashville, Tennessee. It's been a great time. Hit subscribe and check out all the videos that we're doing here at the event. We appreciate you being part of the community. You got to go for now. See you again really soon.

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