Transforming Business Management with AI with Rita Jackson at OpenText World 2024

This is Techron tv. Hey everybody. We're back at OpenText World in Las Vegas and we're talking to Rita here about the impact AI is gonna have on the way we manage our businesses and maybe how it runs into that process.

But Rita, welcome to the show. Thank you. Nice to have you.

I think we all know by now that AI is gonna have this profound impact, but I don't think we're entirely sure to what degree and how it might change the way we think about managing the business. 'cause so much of what we call it data-driven organizations is, you know, maybe a slice. And sometimes people trust the data and sometimes they don't.

Are we on the cusp of some other way of thinking about managing businesses in the age of ai? Uh, I think we're already there, to be honest with you. I, I feel that AI's been around for a long time.

And the one thing that now we're able to democratize, um, a lot of what we are finding, 'cause we're being able to get the insights. So we have data processing, we got security, we have the ability to mine so much information and be able to put it into the context of the business. So I, I think one of the things that you're, everybody's gonna learn here is that AI is embedded in everything, right?

In every one of our technologies. So we're really using it and we don't know that we're using it in a lot of ways. It's kind of, uh, you make it invisible, I like to call it.

And, um, the, the fact that we have the processing powers and the ability to, to gain the insights from all of this is gonna change the way we do business. And, um, a lot of it is about automation. Uh, we all have a lot of things going on, and no matter what, whether you're in retail, you're in banking, you're in oil and gas, there's, uh, never enough time.

And when you look at what AI can do, it's, it's really able to help you, um, automate a lot of the tasks that are what I, I hate to say mundane, but they really are. There's, there's tasks that you can do that are automated, um, so that you can free up time to be able to do things that are more of high value. Mm-Hmm.

On that democratization point, there's a thought pattern that says that AI is a big company game, right? I gotta have a lot of data, I gotta have the expertise and the big companies will benefit most. However, can it go the other way and will it enable more small companies than ever?

And maybe we'll have, you know, just a plethora of companies that wouldn't have existed before if we didn't have the AI capabilities. So I, I think there's two parts to that, right? The first of all is the plethora of data.

I think that there's, um, a whole industry and a whole set, a market segment that's being created because we're able to democratize the data. So I think that there, that's one piece. I also feel that with the tools that are available and the fact that you're more and more companies are able to take advantage of being able to mine a lot of their information, um, it, it is becoming more relevant.

And it's not like it have to be a multimillion dollar corporation. It's coming down to masses. I mean, think about the fact that there's re retailers and I'm now talking about the big brick and stone.

I'm talking about the mom, pa, um, retailers that are able to leverage a lot of the applications that are using AI and take advantage of their information. So I, I believe that with the, this I, I, I'm calling it this generation of AI because it's been around, but with LLM becoming here, think about JA GPT and how it's really brought it to the norm. It's brought it to the, you know, to the consumers.

So in, in just reality of doing that, you're able to leverage it into a lot of the smaller, and I, I I used to call it consumer apps, We're also seeing the rise of small language models and they're by definition smaller Yeah. And can be managed in terabytes. And it doesn't require this massive amount of it in investment in an LLM that, you know, OpenAI is making to be successful.

I can now create very domain specific language models, very specific. And as that evolves, that makes it more accessible to these mid-size and smaller Countries. Exactly.

But you know, if you think about the, uh, where AI and analytics has come, it started out where you had to have a large corporation or a lot of money in order to mine the information. The fact that LLM has come to be, and just think about what chat CPT has done to just the world itself, right down to the students and the, the children that are leveraging AI and LLM to kind of do homework. And we, we use it in marketing and everybody's, you know, using it, it's become part of our, I would say, vernacular in a sense.

So by nature it is coming and becoming more prevalent. I think be, uh, before too long, it's gonna be where we don't even know. It's just part, part of life.

It's a technology that's just becoming part of our day-to-day routine. Do we need to change the way we think about data management? And ah, in some ways, you know, we've had structured data over here and then we've had all this unstructured data that's kinda everywhere.

And something in the middle is semi-structured. Yeah. We have got this legacy mindset to the way we manage data.

Do we need to take a step back from that? Well, I think there's a semblance of security, right? I mean, how much of the information do you wanna make public?

So I, I feel like the, uh, the corporations own their data, right? And you wanna be able to mine the data. And so there's, there's still a semblance of security and privacy.

But I also think that the technology has gotten smarter in that the information is more secure so that, um, we do need to start to think differently. We have to, and it's uncomfortable, right? When new technology comes, it's, it's very, people are at first skeptical and then, then you, you realize that, um, there, there, it's not gonna take away your, your job or your career or, you know, make things more difficult.

So I, I think there's gonna be an evolution in the way that we think, and I, I, I think the more we use it and we become more comfortable with it, we'll be able to become, it'll become more mainstream. I think that the model becomes more valuable, the more diverse types of data You show it. Yes.

So won't that drive some requirement for companies to more federate the management of data that they're sharing with each other to maybe create a smarter AI model for some purpose? Um, and that's where it gets uncomfortable, right? Because now I gotta get outta my wheelhouse.

You do. And I, I think there's another semblance of, well, remember AI is only as smart as the data that you put in it. And then the, the, the discussion that would people really don't have all the time is about unbiased, right?

How do you make sure that the information that is in the data pool is unbiased, is accurate, it's clean, it's secure. I mean, there's a lot of questions that we have to ask, but as you run the models, the models are only as smart and is only going to give you the information based on the data that you have. So I think it's, it's on the, the person that is actually creating the models to make sure that the data is unbiased as well.

Because if you give it biased data, you're gonna get biased results. And as part of that, the way we think about the role data plays in business gen AI is challenging. 'cause it's a probabilistic thing.

Yeah. That is. And I'm trying to insert that into a business process that is highly deterministic.

'cause I'm trying to get the same outcome over, over again. Um, you know, do we kind of need to figure out how to align that? Because I think we Do, right?

Yeah. I think we need to think about where exactly AI is gonna be valuable. Where in the workflow, where in your business processes.

'cause not everything is going to warrant AI or even LLM, right? I mean, so I think we need to decide, um, where you, where it's going to give you the most impact, where you need the automation and where it's gonna actually help elevate the human potential as, as you heard on, uh, during our keynote today. Not every organization is as advanced when it comes to AI as others.

What do you see in the smarter companies doing the ones that are head at the front end of that curve? Seeing the curve? Yeah.

Oh gosh. We see a lot, right? I used to work at a company and very progressive in ai.

And, um, I think there's, there's a different levels, right? You have the theory, you're always gonna have the early adopters, the ones that are going out, you know, challenging the, the status quo. And you need them.

You need the people that are going to, and the organizations that are gonna go and challenge and figure out by industry, what are the new net new innovations? And then you're gonna have the, the, the middle, and then you're gonna have the laggards. I think right now what is happening, you've got a lot of the, a lot of people looking at net new business cases and use cases that's gonna challenge the norm.

And then you've got the, the fast follow. So what I'm starting to see is things that are just, um, how, how to bring AI into our life and make it easier and more simple. And like, what I always like to think about it is that it's gotta be invisible.

Nobody wants to know and make a decision of what do I use ai? Do I not use ai? I'd rather just somebody make the decision and say, you know what?

You've been using it. Think about Google and the Maps app that we've been using forever ways. I mean, there's AI embedded in there and it's been embedded in there.

Do you also wonder, at least I do, and I'm asking you to get your little crystal ball out A little bit. Oh, okay. I got it right here.

Yeah. But might the rise of AI drive a lot of mergers and acquisitions across categories that we hadn't thought would ever be connected? Mm-Hmm.

But maybe they are connected and there'll be some interesting combinations that we wouldn't have thought of. Oh, that's an interesting one, isn't it? I mean, I think healthcare, banking, you know, you think about even oil and gas and manufacturing, right?

Who would've ever thought that you would see, you know, back in the day, you, you banking and retail, who would've ever thought that those two would like even merge? Right? They're very different.

I think about healthcare. I feel like there's a big opportunity for us leveraging AI to help in the diagnostics and in life sciences. And how, how do you bring a lot of that to the masses?

And I feel like AI is gonna help us with that. Because if you think about healthcare and, um, how complex it is around the world, and a lot of things that we just haven't figured out yet. Mm-Hmm.

I can't make up my mind as to whether or not it folks have gotten a little more business savvy over the years. Or is it more that the business folks have gotten more tech savvy? Oh, well, I'm a techie at heart.

I'm an engineer that went into the business world. I think, um, it's a little bit of both. I think that what has happened with technology is it is coming to the business user.

It just is, I think technology is embedded in everything that we're doing. And think about just the, the, the iPhone or, you know, your cell phone. That in itself is like a computer and everybody is using a phone at this moment in time, 10 years ago, probably not.

And think about how robust the phones are, you know? So I think that there's a huge melding, and I think there's blurred lines of what is really technology and what is the, the implementation of that in, in, in business. I, I, I honestly, I I'm a marketer and I'm using it in a sense, right?

In all of the applications that I'm using today, you look at a MarTech stack, it's all technology, but I'm a business user. Mm-Hmm. There's an old joke that says, you know, how do you know if someone from IT agrees with you or not?

The answer is that they agree with you. They look at your shoes. If they disagree, they look at their own Own shoes.

Yeah. I think one of the things that we have to think about though is that no, even no matter who you are, it still needs to be managed by the IT department. So I always tell people that even though, um, the, its, a lot of IT is coming into the business users, you gotta make sure that it's being governed at the end of the day by something somebody, some organization in, in the IT department.

Because you can't have business users go rogue, right? There's gotta be a semblance and a balance between IT and business. But I'm sure if the more and more it comes into the business world, the IT is being able to be freed up to do a lot more work.

Um, I, I was just, I'm doing a keynote later today and it's like 70 70,000 or 7,500, um, open tickets in the it that's like average. That's insane. Aren't we moving?

Hopefully, maybe some people are talking about getting rid of tickets altogether. Oh, Well, how, how, how do you do that? AI will help, it'll help remediate, help you identify risks faster, help you, um, maybe problem solve a bit faster, but I, I really don't think the human element is ever going away.

Mm-Hmm. One of the things we've seen is the rise of another c-level title, right? You're seeing Yeah.

Cheap AI officers. I do. And now there's You, chief data officer, Chief data officer, and any number of digital CXO.

Yeah. And we got a little c-level title happy. And maybe we need to bring this back to this person called the CIO, and that's their job.

I think the role of the CIO or the CXO or the C data officer is evolving and just like the CMO title came to be, right? And then you think about, you know, experience officer and, you know, revenue officer, you think about this, I think we're in the cusp of a lot of transformation and it will consolidate. I, I, I believe that the role of AI data insights, whatever that is, is, is part of the role of the CIO, but it's also the role of the CMO and the CTO and the CEO.

So I don't feel like there's one person responsible for all of it. We've been having a lot of conversations for decades now about it. And I noticed this thing that keeps happening seems to always come back to the data.

It Does. So why do we kinda stray away from that conversation every four or five years? Oh, because it keeps it interesting.

I mean, come on. We need something to talk about. We need another C level.

And you know, the wonderful thing about technology is it's constantly changing, right? I mean, there is always something new on the cusp of it. And, you know, like LLM is the new thing, right?

What's the next new thing that's going to be coming out that's gonna cause a buzz and create another opportunity for us to evolve and change and create maybe another role? Because if you think about when AI came to be about five to 10 years ago, who knew that the title of a, of a data scientist or a chief data officer was even possible, right? So with that comes different roles and responsibilities, right?

And also other roles that have probably kind of taken a back seat, so to speak. Right? So I, I, I look forward to what's next, to see how that is and if it's a CXO title that's coming.

Okay. All right. On the other side of that conversation, if I look inside the IT organization, if I wanna build something ai, I gotta line up some data scientists, couple of data know application developers, few security people, throw in a couple of DevOps people to deploy the model.

And in A way, we, it's got very complex, right? It's this web that we've weaved. Do we need to restructure the way IT organizations are set up?

Well, I think a lot of people already are, right? I mean, I think there's a lot of consolidation happening. I mean, you see it even with companies, but I think even roles and functions are evolving and morphing.

And I think some companies are doing it faster than others. It just, it just depends on where you are in the cycle. Yeah.

Is that part of this platform engineering? I think it is. Or is that just another buzzword we're throwing Around?

I don't know. I think that, think about the title of, um, developer. Are you a developer or are you an engineer?

Are you a DevOps? Or, you know, think about just that, those titles, right? Like people are evolving to different terminologies and different titles.

Even now, if you think about chief information officer, chief data Officer, I mean, I, I think that things are changing. There you go. Hey folks, that's the thing about it.

It's always changing. And every time there's a change, there's more opportunity for everybody going around. Rita, thanks for being on track.

Thank you. Thanks a lot. And we'll be back in a minute.