Qlik Connect: Mary Kern On Building AI People Will Actually Use

[00:00:00] - [Speaker 0]
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[00:00:33] - [Speaker 0]
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[00:01:15] - [Speaker 0]
Welcome back to the tech talks daily podcast. Now today's conversation was recorded at ClickConnect. And one of the things I'm noticing with many of the attack events I'm attending this year is just how much the conversation around AI has matured. It's no longer just about what the technology can do. It's about how you explain it, how you position it, and ultimately, how you make it real for the people who are expected to use it every day.

[00:01:44] - [Speaker 0]
Because for all the innovation happening behind the scenes, there's still a gap between what vendors are building and what customers actually understand, what they trust and want to adopt. So how do you close this gap? Well, today, I'm joined by Mary Kern, vice president of analytics, go to market at click. And Mary sits right at the center of how these products are brought into market from positioning and messaging right through to how customers experience them in the real world. So today, I wanna explore how the narrative around AI is shifting from features to outcomes and understand why agentic capabilities need to be framed in a way that makes sense to business users and how customers, how they're really responding as they move from experimentation, not just into production, but scaling too.

[00:02:41] - [Speaker 0]
So we'll dig into all that and also explore the role of trusted data, the growing importance of context, and why getting started even with imperfect data is often more valuable than waiting for everything to be perfect. Or as I always say on this podcast, version one is always better than version none. But enough from me. Let me officially introduce you to Mary now. So thank you for joining me here at Qlik Connect.

[00:03:10] - [Speaker 0]
Mary, can you tell everyone listening a little about who you are and what you do?

[00:03:13] - [Speaker 1]
Sure. Thanks, Neil. It's so great to be here. Hi, everyone. I'm Mary Kern.

[00:03:18] - [Speaker 1]
I actually am part of the product organization, and I lead product go to market. So we actually are the teams that take the handoff from product and engage with our various go to market teams in terms of marketing, sales, customer success. So we do everything in terms of really identifying how are we going to make our numbers, where we get to target from a market perspective, commercialization, from products, packaging. We do solutions. We do the messaging and positioning for buyers.

[00:03:50] - [Speaker 1]
We do all the high end demos and launches.

[00:03:53] - [Speaker 0]
It's a busy week for you this week as well. There's a lot of announcements, a lot of conversations. What what has excited you so far?

[00:03:59] - [Speaker 1]
I find a lot of it I mean, I do find a lot of exciting. I really find where we're going from an agentic perspective super exciting. While I'm responsible for the entire portfolio, my background is in analytics and with predictive. I feel like when it comes to analytics, the holy grail has always been about using data to support better business decisions to drive better performance and outcomes. And so it's an exciting time with AgenTic.

[00:04:26] - [Speaker 1]
You know, for forty years, we've gotten better in terms of the data that we have to do that, the techniques we have to do that, the new technologies to make it easier for business users and decision makers to be able to use that. So I think, really, with some of the like, innovations in Intentiq, I really think we're really close to being able to enable those folks just ask a question about their business, not have to worry about how am I asking that question that I named the data fields, What kind of analytics technique do I need? What application should I go to? What kind of data? Just being able to ask a simple question as a business user would and go is super exciting.

[00:05:07] - [Speaker 1]
I also hear just in terms of talking with the customers, a lot of folks are really excited about data product. And data product data quality becomes so important as we move into our authentic future. As we know panes of glass are going to change, people aren't necessarily going to be going into their enterprise applications. And even from an analytics perspective, although we have an agentic experience rolled out across the platform, we know that, you know, you're also gonna wanna engage them with those AI tools that you're also using. And, you know, that does put a level of onus back on the data layer to make sure that you are getting trusted answers that you can move forward with.

[00:05:51] - [Speaker 1]
So data products in terms of data quality, being able to get trusted data and context to be able to make those decisions is something I've heard from a lot of customers that they're interested in.

[00:06:02] - [Speaker 0]
Excellent. And you're talking about AgenTiK, and the one of the key messages I keep hearing is you're much closer to AgenTiK than you think you are because when you read out all those requirements and what you need to do, it sounds overwhelming, doesn't it? But it doesn't have to be.

[00:06:14] - [Speaker 1]
It sounds overwhelming. I think, you know, the great thing about Click and our customers is they have been investing in their data estates. They've been investing in putting their data together, making it of high quality, making it accessible. They have been having all the lineage that goes with it. They've been investing in their analytics, and how are you making decisions?

[00:06:38] - [Speaker 1]
And so they've made a lot of the significant investments that you actually need to make AI work well. And I think when you're one of our customers and you're on a ClickCloud, ClickTalent Cloud, ClickCloud Analytics, it is literally simple couple clicks to enable those AgenTic capabilities and all of a sudden be in production with AgenTic, which is pretty amazing. And I think it's something that a lot of customers don't really think about, but they've already done the hard yards for most of it.

[00:07:08] - [Speaker 0]
And one of the things that I've particularly enjoyed here is I go to a lot of tech conferences, and there seems to be a deliberate move here away from talking about shiny AI features and focusing on business outcomes. So how hard is it to get that message to land with customers who who many of them are still focused on just the tech itself?

[00:07:25] - [Speaker 1]
Just the tech. I think it's really easy for us here at Click two to also focus on just the tech. I mean, we do have you know what? That's what drives us at the end of the day. We have developers who are developing these new capabilities, and they're super cool.

[00:07:40] - [Speaker 1]
But I think once you get especially in terms of my organization, it's really about we have new ways of solving old problems. And what is the benefit of doing it this way now? And where how is that going to enable your organization, you, your organization to go further and farther? And I think before we get I say this, and I'm like, I worked on the product keynote. But to me, I think what we've done with MCP is amazing.

[00:08:07] - [Speaker 1]
All the endpoints that all the skills that are available for tools and skills that are available for others to use is really amazing. But for me, it's less about the number of tools that are available and more like what you can do differently to really enable your organization to excel within your own existing ecosystem without having to rip and replace with taking advantage advantages of the investments you've already made to get to your authentic future. So it is tough, though, because everybody wants to talk about the tech because it's super cool.

[00:08:41] - [Speaker 0]
It really is. And another thing, I think many businesses have been stuck in pilot phase or pilot purgatory and not reaching production, and even those that have have been unable to scale. So what are customers actually telling you about what's happening? I'm curious.

[00:08:55] - [Speaker 1]
It's really interesting. And, you know, of course, there's, like, you know, the marketing speak aspect of it. And we do know even from when we were piloting our agentic experience, people start you know, we were in preview with Answers, our agentic experience, and all of sudden, it starts to expose issues that you have with your data. Right? It starts to expose where you may be lacking context, and therefore, you're not quite getting the answers that match up in terms of what you should be getting.

[00:09:24] - [Speaker 1]
But I think the truth is when it comes to AgenTic, the good and bad news is I think everyone really envisions a bold future with AgenTic in terms of whether we're able to drive major productivity gains or an ROI to the business. And even though we can't prove that out right now, everybody's on board with driving it. From a leadership perspective, you know, costs are somewhat of a concern in terms of it's getting expensive, but then it goes down to the folks in the organization that need to do it. And you're trying to do do the best and be responsible with the investments that you've made with the use cases that you can identify. And I think it's just a matter of as I've was listening to our GM, Matt Hayes, talking, you know, we are in a massive we're still experimenting, all of us.

[00:10:12] - [Speaker 1]
We're still kinda figuring out what is it that we're gonna use, what kind of data does it need, what are the use cases we can do. Holy moly. Now that we're doing this, what are maybe some of the guardrails we need to put in place in terms of policy and compliance? We're going through this on our own journey at Click two in terms of as we roll out our enterprise AI assistance and we're hooking ClickUp. Right?

[00:10:34] - [Speaker 1]
How do you enable your people? So I also think it's you gotta turn on the tack and start playing with it, but there's a lot more to figure out. So I think we're still experimenting. And I do think, you know, everything we hear about, like, those pilots are getting more into production phase with our customers. You've got a lot of great things you can look to scale.

[00:10:53] - [Speaker 1]
Cost is going to become an issue, but I really do think we're to start seeing some more ROI here quickly.

[00:10:59] - [Speaker 0]
And I'm glad you mentioned guardrails there because there's also a clear emphasis on trusted data, governance, and context. Do do you find that that message also resonates immediately, or do customers only realize its importance after things go wrong?

[00:11:15] - [Speaker 1]
I think I you know, the message really is resonating. And I think we look at it a couple things, like, and we look at it also in terms of what does click do differently? What do we bring to the game? And how does that enable you in the new world of AI? And for us, that also comes down to, like, the three major things in terms of context.

[00:11:37] - [Speaker 1]
So that really comes down to our analytics engine because it was really designed to mimic how the human brain works in putting together pieces. Because we're messy thinkers in terms of how we associate data. It's not really like a linear thought, and our engine was designed to do that. And so it works particularly well with AI because you don't leave any data behind. So you bring that full context with you, and we bring that context, which we've always had in analytics.

[00:12:05] - [Speaker 1]
And we can also start to leverage that in the world of agentic and large language models as it's going through and doing its reasoning to keep everything in context, to keep multiple threads in context together. And the trust also becomes really important because maybe organizations you know, when it comes to data quality and governance, it's not like you know, it's just like, oh, the hottest of topics. But now it really is. And people are just like, yeah. Like, when you really start start thinking about how many people can be enabled now to take advantage of insights and prescriptive recommendations that they weren't able to do before.

[00:12:42] - [Speaker 1]
You know what? I'm a business user too. I I always say business users, we're a little bit more flippant, right, in terms of our, you know, it's just like our adherence to policies, how much we're just like, I just need an answer I can take to the board. That looks really good. Right?

[00:12:56] - [Speaker 1]
And you don't always take the time to really investigate that. So I think for the folks who are really making wanna make sure that those answers are right and correct, the trust thing really resonates quite a bit. So, yeah, those are all great. And then lastly for us, like, the third one is also just being able to do that in the environment that you're in with the stack that you have. A lot of our customers are big customers.

[00:13:17] - [Speaker 1]
They've got tech stacks that have, like, twenty, thirty different vendors and components in it. And just to be able to enable that with trusted intelligence as part of, like, the architecture and enable across that ecosystem versus ripping stuff out replacing something that resonates well.

[00:13:34] - [Speaker 0]
And you're bridging product marketing and customer reality, which must be an incredible balancing act on its own. But where do you see that biggest disconnect today between what vendors are building and and what customers actually need?

[00:13:47] - [Speaker 1]
It's a tough one. I you know, especially for us, I think one of the things or the misconceptions as we were talking about, I think, honestly, you know, you just wanna slap a large language bundle on it and you expect it to work. And it doesn't quite work like that. Even with I know a lot of folks are really excited about MCP, which is amazing if you've got the resources that you're actually building your own agents or customizing your agents. But you really do have to build it all.

[00:14:18] - [Speaker 1]
And that experience is gonna be different than, like, an out of the box experience you get from Answers where we've been able to, you know, train those agents so they really are specialized agents in data integration and analytics and, you know, all the predictive, the automations. There's specialized agents that are doing that work. We're able to look at which models do they take advantage of, how do you optimize them, how do you make sure that they're ranking and prioritizing enterprise information over external sources. So and I think too, it's just like and making sure it all works, making sure the analytics works. I think there's this expectations that we can just act like slap a slap an assistant on it, and it's just gonna work.

[00:15:01] - [Speaker 1]
And we're gonna get the same type of answers we'd get if someone went to a a dashboard, and it doesn't quite work that way. So I think that's one of the things. And you really do have to work on training and optimizing those agents. So it's a little bit of time. I think it's really gonna change.

[00:15:16] - [Speaker 1]
Once we get past that, I think we're really yeah. I think it's gonna be transformational, though.

[00:15:20] - [Speaker 0]
Yeah. And to echo what you said, though, I think a lot of organizations feel the pressure to move fast with AI and not get left behind. So how do you position Click's approach to to get that foundation right first without it sounding like it's slowing innovation down or you're trying to put the brakes on?

[00:15:38] - [Speaker 1]
Okay. This I have to admit. So I have a I come from a predictive AI background. What I find so interesting being at Qlik and it's, you know, the tribes of analytics, those who come from maybe visualization versus more advanced analytics. And, you know, there's a huge need when you come from a data side or even a business intelligence visualization side.

[00:16:00] - [Speaker 1]
It's just like the data has to be right, so high stakes, absolutely has to be perfect versus, honestly, on the predictive and the advanced analytics side, it's like, doesn't have to be perfect. You just have to get started. When you're doing the analytics, it will tell you what data is important for that outcome that you're trying to figure out. That's the data to invest in. And in terms of whether or not it's perfect, it's okay.

[00:16:26] - [Speaker 1]
So I think, you know, in terms of click and our customers here, I think, one, like, we do have a really strong heritage in in visualization, and that's amazing because I don't think visualizations will go away. They're there for a reason. It's really hard for humans to grasp data and a lot of data. So visualizations are important. It's really how we can enable that in a different way, in a different experience.

[00:16:51] - [Speaker 1]
But this event, I'm just really starting to hear more of that. People are just like, oh, like, I like, that's actually a reason to move to a cloud. Like, that's really a great reason to start exploring those capabilities and that I can that I can, you know, take advantage of it right away. And I think it's just like being open to do things differently. We're a couple years into the generative and agentic AI movement, and we definitely see, like, I think more people kinda coming around, which is which is really great and fantastic to see.

[00:17:21] - [Speaker 1]
I'm still like, it doesn't have to be perfect. Doesn't have to be perfect to start. But getting back to your question because I didn't answer it, doesn't have to be perfect to start. But once you start, just like our preview with Agentyx, you start to understand where your problems are that you need to go back to fix to make it lock solid based on the type of decision you wanna make on that data. Some some decisions really need 95% better quality data, accurate data if that's really the most important type of decision you make for your company.

[00:17:54] - [Speaker 1]
Other things, you know, can be directional. You just have to figure out what the right what your decisions are and what's the right quality of data that can get you there.

[00:18:04] - [Speaker 0]
Yeah. And cost is also becoming a big part of the conversation, especially when scaling AI. So how are your customers reacting when the conversation shifts from capability to cost and efficiency?

[00:18:17] - [Speaker 1]
You know what? You know, it's so funny because, you know, as a vendor software, it's like everybody would like to use your stuff for free. So I think even these capabilities aside, there's always going to be a healthy conversation regarding cost. I think for us, you know, there is a big concern. Like, what's the cost of turning this on?

[00:18:37] - [Speaker 1]
What's the cost of turning this on for my entire organization? So for us, we really have tried to make that easy and approachable. So we have baked in agentic capacities, if you will, for our cloud products. So if you have a Qlik Cloud Analytics, if you have Qlik Sense Enterprise SaaS, if you have Qlik Talend Cloud, you inherit those capabilities as part of your your plan today. So you can start playing around with it.

[00:19:07] - [Speaker 1]
And then based on the success that you're seeing, like, we can sell you additional capacities to make it right for you. But I do see and I say this as a team that, like, we're looking at the pricing and packaging. It is Wild West out there in terms of how these things are packaged and priced. So I would say, initially, we've rolled out with click answers. We had very much a ask a question kind of a capacity.

[00:19:34] - [Speaker 1]
A question's a question. And so to make it easy, that's really what we're rolling out here in terms of enabling these capabilities. You ask a question, and that's what it costs a question. It doesn't matter if that question is actually 10 questions or inquires requires, like, 20 different tasks or workflows underneath it right now. It's kinda simple.

[00:19:53] - [Speaker 1]
Question is a question. Let's get you using it. Let's see you seeing value out of it. I'm sure these models will pivot over time. And when they do, we're gonna do it in a way that is reasonable for our customers and it doesn't break the bank.

[00:20:05] - [Speaker 1]
Because if it breaks the business plan, you can't use it. If it breaks it in terms of cost, if it breaks in terms of compliance, it really does you no good. So it's something that will continue to evolve. But, yeah, when you start talking about AI, it's just, you know, the the dollar signs, the pound signs start dancing in front of everybody's eyes. Like, it sounds great, but how much is this gonna cost us?

[00:20:28] - [Speaker 1]
It's a big unknown. Yeah.

[00:20:29] - [Speaker 0]
And you're someone that's worked across multiple major tech companies. I'm curious. Are we seeing anything different with AI adoption this time, or are we maybe repeating patterns from previous waves like BI or or the cloud? Do you see any of the same kind of patterns?

[00:20:45] - [Speaker 1]
Yeah. I mean, you know, from an analytic side, and I think it had so many of the analytic techniques in for me, but BI was the most widely adopted, right, in terms of users. And even that hit a wall because at the end of the day, you know, even as a person who's held a role or had roll out, like, visualizations and dashboards to measure business performance, it turns out, surprisingly for someone like me, that not everybody really, like, grooves on data. Not everybody really wants to look at, like, how is my business doing? They wanna look at charts and graphs.

[00:21:19] - [Speaker 1]
So it's there's always been this big, I think, barrier to adoption for these types of things. Whereas AgenTic, I think we're seeing it really kinda take off in a new way. I was really worried when we launched our AgenTic experience in February, like, how many people would say, you know what? I'm not gonna turn it on because I could take my job. And that has not really we have not really hit that all.

[00:21:46] - [Speaker 1]
I think there's some concerns about, you know what? It's gonna transform how we all work. It's gonna transform our roles. It's gonna transform how we work. And I think we've are at that point in this journey where people are, like, maybe a at least in our customers, still early days, a little less like, hey.

[00:22:02] - [Speaker 1]
I don't wanna turn it on because this is gonna take my job. But it's like, how can I turn this on and figure out how to work with it to do more and to do differently?

[00:22:11] - [Speaker 0]
And when you think about the next twelve months, what do you think success will look like for customers that are adopting clicks approach? All the products and all the things announced are already live. So what should they realistically expect to achieve if they get it right?

[00:22:27] - [Speaker 1]
If they get it right. Hopefully, they do. I think there's a lot of experimentation. But what I am really excited about, I think when it comes to adopting, I think there's huge productivity gains in AgenTic AI a 100%. You and I are probably using AgenTic to do things, and we're like, that's amazing.

[00:22:47] - [Speaker 1]
And it is. So the productivity gains are there. But I really am looking forward to organizations starting to say, like, alright. We've gotten the productivity gains. How can we use this to do differently and betterly for the betterly, it's not even a word.

[00:23:02] - [Speaker 1]
How can we do things different for the business? And that's actually starting to look at how to use data and analytics to drive your business, to drive your outcomes. And that's use case focus in terms of what are the goals, what are the teams who are doing it, what are the systems, what are the processes, and how do we apply? Is it data integration? Is it analytics?

[00:23:23] - [Speaker 1]
Is it AI to do that differently to get to a better outcome? And I'm really excited to see how that gets broken open now that we're kinda doing some of the simpler stuff. Right? And and we're enhancing productivity. So now we can apply that to solving more and bigger kinda issues and challenges for the organization.

[00:23:45] - [Speaker 0]
And I would imagine this week has been a great opportunity for you as well. You've been back to back meeting, seeing the kind of reaction in

[00:23:51] - [Speaker 1]
real time. Incoherent. Yeah. Little long. The answers are a little long there.

[00:23:57] - [Speaker 1]
Sure are. I it is a lot to you know what? Exactly why we have data and analytics. It is a lot of data and a lot of information to process. And for me, in product go to market, I have to admit, like, people come to me with all the problems.

[00:24:12] - [Speaker 1]
Right? I work on the keynote product keynote, and, like, what I hear is the things that went wrong. Right? The analyst programs, the things that we could have done better. So for me, it's it's always you know what?

[00:24:23] - [Speaker 1]
For me, it's always taking the information. It's great. I think it's great that we have had favorable feedback on the product keynote, and I've had great conversations with analysts. I've had great conversations with social influencers and the media like yourself. And that's all good, but it's also about how do we continue to get better.

[00:24:44] - [Speaker 1]
And that's what I hear a lot about. So it's kinda going back and processing, like, where are the opportunities for us to do better with the product, with our go to market, and do things differently. So for me, that's the big action item coming out of this one.

[00:24:57] - [Speaker 0]
And I think that is a great moment too. And I appreciate just how busy you've been this week. And to take the time to sit down with me and have a conversation, really appreciate you. So thank you so much.

[00:25:06] - [Speaker 1]
Thank you so much. It's such a pleasure to be here. It's been a fun conversation.

[00:25:11] - [Speaker 0]
One of the things that came out of my conversation with Mary today is just how much of what we're talking about here comes down to translation. Not translation between languages, but translation between technology and business value. Because as Mary highlighted, the technology itself is moving incredibly fast. New capabilities, new models, new ways of interacting with data. But, of course, none of that matters if customers don't understand how to apply it or if it doesn't fit into actually how they work or if they fear that it's going to replace them.

[00:25:46] - [Speaker 0]
So I think there was also a real honest moment around expectations here. The idea that you can simply layer AI on top of existing systems and expect everything to just work because in reality, there's still a lot of work to be done around data quality, around context, and training systems so they deliver those meaningful results. There's also that balance between moving fast and getting it right. And Mary made a very strong case today for starting. Even if everything isn't perfect.

[00:26:17] - [Speaker 0]
Use AI to identify where the gaps are and then improving over time based on real usage and real outcomes. And to me, that is a very different mindset from traditional approaches to data and analytics. So as you think about your approach to AI, maybe the question is not just what can the technology do, but whether your organization is ready to translate that capability into something people can actually use trust and build on. But these are just a few takeaways of mine at the ClickConnect conference. I'd love to hear your thoughts on this and any conversation that I've had recently.

[00:26:58] - [Speaker 0]
Are you seeing that gap between technology and adoption in your own organization, or are you starting to close it? Whatever it is, please let me know. Techtalksnetwork.com. 4,000 interviews. You can leave me a voice message and so much more.

[00:27:13] - [Speaker 0]
But that is it for today. So thank you to Mary for taking the time out at the conference to sit down with me, and an even bigger thank you to each and every one of you, not only for listening, but listening to the end. And if you enjoyed yourself, I'll be back in your podcast feed same time, same place tomorrow. Hopefully, I'll speak with you all again then. Bye for now.