See all Dez Blanchfield, Founder & CEO Sociaall Inc. transcripts on Youtube

I have the pleasure of being joined today by Mike Capone, Chief Executive Officer at Click. Mike, great to see you. Thank you so much for making time to catch up with me.

My pleasure, Dan. It's great to see you again.

So for our audience, I wanted to catch up with you today to have a brief chat about the impact of generative AI in the market and specifically around some of the bigger points such as the need for organizations to be able to work with it, trust it, particularly the data that they're either loading to it or importing to it or generating with it, and to work with that data as trusted, clean data, and particularly from the point of view of data governance and so forth that's related to that. But maybe if you could just summarize the impact of AI you're seeing and particularly generative AI on the market currently, across what you're seeing in the market and your customers and what it means from a competitive landscape.

Sure, Des. So we're talking because it's all the radio trade, the generative AI is everywhere. Everywhere I go, every customer re-interview I give is about this topic. The reality is Qlik has been getting ready for this moment for the last 5 years, probably the last 30 years, and certainly in the last 5. It's not new.

Generative AI, it's the next evolution of AI, large language models of AI. But AI in and of itself and pattern recognition, the underlying technology has been around. In fact, it's been in our platform for quite some time. It is nothing more than pattern recognition. It's just the fact that compute has gotten cheaper and more powerful and the algorithms are getting better.

It's no surprise that we've arrived here. And the questions that we need to ask ourselves now are, how do we harness this capability, as you pointed out, in a safe, trusted way, just given the awesome power and potential of the technology?

More than ever, we find, you know, everything's always on, always connected, increasingly digital. I don't think there are many parts of our lives, privately, professionally, in work and so forth, that hasn't been touched by something that's been digitized and digital transformation of some form. And that's underpinned by this, I guess, critical need to have trust in the data. I wonder if you could just briefly talk about the importance of data governance around that space. And I guess, you know, the challenges that come with the need to have data organized and trusted and in turn be used as a source for some of these AI tools.

Yeah, it's super critical. And the technology is advancing faster than governments and corporations and schools. My daughter's high school band, ChatGPT, so did some of my largest financial services customers. That tells you that people are struggling with this topic. The reason is the data.

All of these things are underpinned by data. Without quality data, they're not going to make sense and you're introducing a lot of risk. You and I have talked very recently about the poisoning of data and bad actors actually interjecting fake malicious data into the underlying systems that feed these models. And that's already happening. Like, we think that's not happening today.

We're sadly mistaken. And you can see some of the terrible false positives and awful outcomes that you can sometimes get out of these tools. So at Qlik, and quite frankly, when I talk to other executives inside of our ecosystem, the data analytics ecosystem, we have this awesome obligation actually to make this better, to solve this problem. And the way we're going to solve this problem is by building technology to surround this capability that does generate trust, veracity of data, lineage of data so you really understand where it comes from and to really white label a lot of these things. So yes, the AI will give you interesting conclusions and powerful conclusions, but you really need to understand why, you know, why that happened.

You know, blind trust in anything will get you killed. And, you know, AI is no different. It's just something that we have to contend with. And we think at Qlik, we're in a very, very unique position to not only help this, but actually shape the future of how companies use this technology.

Indeed, and it's very much been built into the DNA of your entire platform from the on-prem through to third-party data center hosted and service provider provided platforms through to now the Click Cloud, you've been able to take all forms of data, particularly now with your various offerings to interconnect APIs, with the connected factory, you've had a long history of taking data of various forms and checking fundamental things like formats of date, the context of the data, the placement of the data, the field sensibility, and so forth, that I imagine that fundamental DNA now would then translate directly into how you're treating data that comes into whether you're building models or processing models, or even the output of models. I wonder if you could just briefly touch on that.

Sure, sure. Well, you know, I'm headed to Sweden in a couple of days. It's Qlik's 30th anniversary. And we were founded on the premise that there has to be a better way to analyze data, you know, in-memory technology, as well as our associative engine, being able to bring disparate data sources together and make sense of them without having predetermined SQL databases or having to know what questions you want to ask underneath. So That's been our lineage.

Over the last 5 years, we've invested heavily in data integration technology. As you said, the vectors of data, the amount of data is just growing exponentially. So now we have customers, you're not only taking data from their operational systems, like SAP or mainframes, but from sensors, right? From consumer sources, they're bringing it all together and more and more they're bringing it all together in real time, it's massive. I mean, the amount of data people are processing is massive and handling that in real time requires powerful tools to be able to do that.

We've invested both organically in our R&D capabilities, but also inorganically. As you know, we've done

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acquisitions culminating with Talend recently to actually get at the underlying management of the data that feed our analytics and these models. And we're just something we're really excited about. And what, you know, Talon, which is the latest 1 brings, which is our largest acquisition by far is, you know, that not only data transformation, but the ability to build trust and quality in your data. We're really excited about it and couldn't have come at a better time.

Well, indeed, and congratulations on that acquisition. I wonder if we could just circle back to that and particularly some of the strengths that the talent acquisition brings to your already phenomenal capability across the entire Click ecosystem. I wonder if you can sort of just quickly touch on what it means now in the process of this acquisition and the combining of both the human resource capability, the technology capability, I guess the overall business capability that both companies strengths now bring to the Click offering in this space.

Sure it does. So Talon has been on my mind since the day I joined Click 5 and a half years ago. It's a terrific company, very complimentary capabilities to Click. So what we had originally with our analytics platform, and then what we've built since then with the attunity acquisition and some of the R&D we've done around automation and things has been great. But the thing that we were missing was this data transformation, data quality, data governance capability.

Talon has all that and it's a leading platform in the market today. So we're really excited to bring these 2 companies together. And now When you take a step back and you look at our platform, we've got the data integration capabilities, our change data capture, our data lake management products. But with Talend now we get data transformation, not just traditional kind of ETL capabilities, but the more modern ELT ability to actually do push down transformations into kind of modern cloud data lake platforms, the ability to actually look at the data, the quality of the data, build trust in the data. We have data lineage capabilities.

And then of course, our traditional analytics platform. And finally, the abilities we built around automation and alerting, but being able to get insights that are trusted, proven, and then take action on them. And we do all that in a cloud agnostic way, which you alluded to earlier, we are very unique in that we are not dependent on any 1 platform. We work with every hyperscaler, GCP, Azure, AWS, we work with Snowflake and Databricks and you name it. We have a completely open ecosystem.

And what that allows us to do is harness data from anywhere, leverage the capabilities of our platform, and generate that trust that allows our customers to act on data because they now believe in it.

Yeah, and depending on all of that, when we touched on it earlier, I wonder if you could just maybe circle back to this. When we think about what you now have as an end-to-end journey for workloads, business processes and data, it seems to me that you now have, as you said, the ability to do even more substantial data transformation and then the analytics and insights at the other end that Click's been known for for some time. But you also now have, and you did a live, well, your team did a live demo recently that I had the pleasure of seeing on stage on public wifi, no less, of this entire end-to-end capability, taking data from a significant number of sources, transforming that data, putting it into the Click Cloud, and then building tools from that. And 1 of the things that was demonstrated was live production of effectively board-level PowerPoint presentations, And it wasn't producing PDFs or PowerPoint documents. It was producing the look and feel of a PowerPoint, but with real-time data.

So every time the page went backwards and forwards, that data was real, it was real-time. But what was interesting was that there was a lot of discussion around the control of the data, the access to the data, the security of it, particularly the governance. This has to be something that you're seeing more and more, not just at board level now, but operationally, that with all the challenges we're seeing around the world now, whether it's geopolitical, whether it's economic, whether it's still the continued recovery from the last 3 and a half years, the data governance and the security and the control around the data is ever more present. What are you seeing with regard to that from your customer base? I mean, is it a fair thing to say that this is probably a top 3 to 5 challenge for them now that you can now address?

Absolutely. Look, Des, there's no C-level executive on the planet right now that's not wanting to have a conversation about real-time data and analytics can make their company better, compete more effectively. And that's what's happening right now. But really, we're having to educate our customers on the art of the possible, what can happen. And what you saw in Las Vegas, the clip roll was a great example.

We're working with customers right now. Think about it, supply chain. So you've got all this data about your inventory, about your customer orders, about what you need to fulfill. That's 1 vector of data that's typically trusted. It's in your SAP system.

But now you want to figure out, okay, how does my supply chain stay intact so I could fulfill all these orders. So now that's where kind of the LLMs and generative AI comes in. So now you can start pulling external data out of, so weather, great example, weather can really mess up your supply chain if shipping gets disrupted, right? So pulling that in. And what we're seeing is real-time in meetings, customers are actually pulling all this data together in real-time, leveraging our tools to be able to draw conclusions about where they should be thinking about maybe adjusting, you know, supply chain, suppliers, countries they're sourcing parts from.

And then when C-level executives have questions, like, well, I don't believe that data or where'd that come from? We can build all that lineage behind it and put a trust score, which is what you saw in Vegas on top of it. Here's how much we trust this data. Then we've got all of our AutoML AI capabilities. What you saw was all the statistical analysis is underneath that.

So you can actually then, you know, actually get back it up with true data science capabilities. It really is something incredibly unique out in the market. You can tell I'm getting really excited about it as we talk about it, because I don't think anybody can do what we can do.

1 of the things that really jumped out at me as well, just to pivot onto this whole governance and I guess compliance and regulatory requirement, was a couple of the demos touched on the capacity you have now with the talent and click capability, which I know we'll talk about in a second with regard to your overall roadmap and where it's going, is the need to be able to actually, as you said, wind back that data and not just validate the sources of it and the veracity of that data, but to actually provide that in some form of reporting form to potentially third parties, whether it's law enforcement for legal reasons or whether it's just something to do with a merger and acquisition or some other thing, that must be an increasingly large area of demand that you can now meet where organizers are saying, well, it's not just internally, we now need to address this challenge, but we need to do it all, as you said, supply chain, business partners, whether it's transport, logistics, aviation, commercial finance, whatever it takes me, people are going to say, well, not just prove where that data came from, but what's the validity of the data?

How current is it? Is it real?

Well, I would even posit that the problem is even more deep than that. You probably saw in the news, company got a really, really big fine because they moved data that they shouldn't have moved out of Europe, out of the EU, to the US. It's pretty public knowledge. The problem is it's great to go look and say, hey, we just did an audit and we found out that you moved some data, but it's too late. Somebody's already drawn up the fine that you're going to pay for doing that.

So with our technology, you actually see it while it's happening and you can stop it. You can stop it before it happens or when it happens. You can say, hey, you just moved a piece of data that's GDPR sensitive. You need to not do that. And you can stop it.

You can alert somebody. But you can head off that whole problem. And what we're working with some large global financial services customers on exactly that, which is whether it's GDPR specific, whether it's KYC, your client and financial services, we're able to build real-time monitoring around these problems, which is really the way the world has to go. Because otherwise, you want to find out about it when it's too late. You want to find out about it either before it happens or as it happens, and that's what we can do.

Indeed, and certainly the key industries that you play in, the likes of what has for now 5 years of its life being teased as a toothless tiger, the EU is certainly unleashing the GDPR regulatory capabilities on some very big names. I wonder if we could kind of look at, you know, what's next for AI in your view, and maybe just give us a little bit of a look ahead with regard to what the future holds, not just for the market overall and how generative AI potentially can act as a major vector to fuel growth in your customer base and their capabilities, but also where the click and tell on product and services are going to in the short to medium term and those capabilities. What does that roadmap look like as far as you're concerned and what's next for AI in that space?

Yeah, so AI is gonna continue, but the question is how do companies create competitive separation? Because a lot of these LLMs and generative AI, now in the public domain, like if you're using it and somebody else is using it, there's not really going to be separation there. So for us, it's about helping our customers create that separation. And how do you do that? Well, you do that by harnessing the data that's at your disposal, your unique intellectual property built into your data and governing that and getting it ready to be consumed by these new techniques, large numbers models and generative AI.

And then being open to be able to pull in other sources they leverage some of these kind of open source or third-party tools. Lots of companies are now building governance and platforms around this. So we'll work with all of them. Our goal is not to corner the market on AI. Our goal is to corner the market on the ability to actually work with AI in a safe, governed, trusted way and generate conclusions that help you create competitive separation, but also make sure that you don't have any kind of false positives that end up, you know, creating a problem for your business.

And again, with everything that you and I have just talked about, we think we've got the capabilities to do just that.

A lot of organizations are looking at this from a 30, 000 foot point of view, wondering what kind of guardrails they can put around this. What sort of advice would you give from board level down for them to start having conversations with yourself and your team within the Click and Now Talent combination to start to consider some of the guardrails that you should be putting in place in an organizational structure or format, whether it's an AI ethics committee or some sort of operational capability you can bring to the table, to put those guardrails in place so that they do have those controls and measures in place beforehand, as you said earlier, as opposed to then trying to catch the, you know, when the cat's out of the bag. What are some of the key things you're talking about currently with your customers, maybe even putting examples you put in place so far where key decision makers can sort of take some takeaways from this and say, okay, this is a conversation we should be having with the team at Qlik about how we put these guardrails in place with the tools I can bring to the table to ensure that we are leveraging AI and the capabilities it has to not just generate data, but also inject and process data, but with some sort of sensible controls around it.

Yeah, yeah. It's an awesome question, Dennis. So first, the first thing I always tell the executives is, you know, history is littered with attempts to try to stop technological innovation, right? And advancement. You maybe can slow it down a bit, but ultimately it's here.

And so just putting your head in the sand or just putting a wall up and saying, not here, is ultimately a failed strategy. That's not going to do it. So you do have to govern it. And I do think that the 2 dimensions are the ones you kind of alluded to. 1 is you have to have people inside your company who are actually thinking about this, looking at it.

AI governance committees are great. But the reality is this has to become ingrained in the fabric of your organization. Data is at the disposal of everybody. So the people who govern data today, your data architects, your analytics users, you're going to have to raise their level of comprehension about the advantages and the risks of this technology. And then you need to make the appropriate investments in terms of data governance tools and other ways to actually monitor what's happening.

And you wanna move as fast as you can, but wanna make sure you get both eyes open as you do that.

Just to wrap us up very, very briefly, if you were to share 2 or 3 key thoughts around the normal sort of approach that organizations have when they come to you, they want to start a conversation, what's the best way to approach you and your team as far as click goes to start that conversation? And what sort of things should they be asking knowing that your core strengths are these capabilities and if they are an airline or bank or transport organization they should probably stay true to their core business. What kinds of things should they think about when they come to have their first couple of conversations with you if they're not already a customer, or even for existing customers who are looking to leverage some of the new capabilities with the talent acquisition. What would you like them to approach you with and sort of come to you and say, look, we need some help in this space?

Yeah, well, the good news is, Des, we've got existing relationships with most of the Fortune 1000 companies around the world. So we're well placed. So obviously, those conversations can start with our normal cadence. We're also running a series of educational webinars. You just go to our website, and you can sign up for them.

And we talk a lot, a great deal about, all right, how you get started, how you set these things up. And then the other thing that we do is we are really good at having customer forums. We connect customers with other customers and we let them share ideas, but we moderate those discussions. And we do have a whole now setup around, how you start thinking about AI, data quality, and how you have to think about an end to end forum versus just looking at, okay, here's a cool new shiny object, which is chat GPT, and let's start using it. So lots of different ways to get to us.

When in doubt, go to click.com and we'll get you started.

Fantastic, Michael. Thank you so much for sharing all your insights on that. And for our audience tuning in, we will definitely have a number of resources, including links to all the things you just mentioned and a number of others. We would love them to consume those and ensure that they bookmark the click.com website and follow the organization and yourself on LinkedIn and Twitter and reach out sooner than later and start those conversations, whether you're an existing customer already, whether you've got a Click partner or a Talent partner working with you, because I don't think there's time to get left behind on this 1. This is such a disruption across all industries, across all segments, all markets, that my biggest concern for a lot of organizations now is if they move slowly, their competitors may get such a lead on them that may never actually catch up.

And I think Click and now with the talent acquisition is so well placed for that conversation that now's the time to do it, not later. Mike, thank you so much. It's been an absolute pleasure to catch up with you. And thank you very much again for having me at Click World recently. That was an absolutely amazing event and we'll definitely have links to the replay for that as well.

And I very much hope we will catch up again with you soon and maybe get a take on it in the next few months and see how some of these predictions have turned out.

Thanks, that's great, as always speaking, and I look forward to future opportunities as well.

Thanks so much, Mike, take care.