Qlik Connect: James Fisher On Turning AI Into a Business Strategy

[00:00:03] - [Speaker 0]
Welcome back to the tech talks daily podcast recording at ClickConnect, where I'm seeing a very clear shift in tone compared to previous years because the conversation is moving from what AI can do to what it actually takes to make it work inside a business. Because after a period of rapid experimentation, many organizations are now facing somewhat of a reality check. Yep. They've built the pilots, tick. They've explored the use cases, another tick, and tested the limits of the technology.

[00:00:38] - [Speaker 0]
But turning that into something operational, something scalable, something that delivers real value has proved far more complex. So where are companies getting this wrong? And more importantly, what needs to change? And to explore this topic, I'm joined by James Fisher, chief strategy officer at Qlik. I last spoke to James in a remote interview, but today, we get to sit face to face in real life.

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And James has been at the heart of Qlik's evolution for over a decade, helping guide everything from product strategy through to how the company is positioning itself in this AI driven world. So today, we will go beyond the surface level discussion, try and dig a little bit deeper into the strategic realities that are shaping enterprise AI today. And we'll discuss everything from chasing AI use cases with without a clear business objective, why that often leads to wasted effort, to the idea of having a standalone AI strategy could be fundamentally flawed. I wanna also explore the growing tension between openness and control and the increasing importance of governance, cost, and sustainability, and why many of the same patterns we've seen in previous technology waves are starting to repeat themselves once again. This month, I'm partnering with NordLayer, and it's support like this that allows me to keep bringing you conversations from across the global tech community.

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And if you are running a business right now, you may have noticed there's a quiet shift happening, one that most people are still underestimating. And that is your company doesn't live inside your network anymore. It lives inside the browser. That's where your SaaS apps sit. That's where your data moves.

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And increasingly, that's where attackers are focusing their attention. So NordLayer has just launched its new business browser, and it's designed specifically for small and medium sized companies that need visibility and control without the overhead of enterprise security tools. What I like here is the balance. You get advanced protection, better compliance, and full visibility into how your team is working online, but without slowing anyone down or forcing them to learn anything new. Feels like a practical step forward rather than another security layer that adds friction.

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So if you wanna see more about how it works, please head over to nordlayer.com/browser and check it out, and let me know your thoughts. But now, let me introduce you to James. So thanks for joining me here at ClickConnect, James. We last spoke remotely, I think, about two and a half years ago. But for anyone that missed that, can you remind everyone listening with a little about who you are and what you do?

[00:03:32] - [Speaker 1]
Yeah. Well, it's great to catch up again and and do that in real life. It makes a change. So, you know, I've been with Cloak since 2014. I joined to help lead the transformation of our product strategy and the organic expansion of the portfolio as we moved to cloud and ultimately got ourselves ready for the AI opportunity.

[00:03:54] - [Speaker 1]
So I served as our chief product officer to lead that strategy, and a few years ago moved into the chief strategy officer role to, you know, really guide the the continued evolution of everything we're doing from customer engagement through to our own internal use of of AI and and how we set ourselves up for this brave new world which we all find ourselves in.

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And two and a half years in tech terms is like a lifetime with the speed of change at the moment, and since we last spoke, we've seen this shift from AI experimentation to operational reality. From a strategy perspective, what have you seen change inside organizations when AI moves from pilot purgatory to something the business depends on?

[00:04:37] - [Speaker 1]
Well, I think I think we've seen a a a critical milestone get passed. Right? We've got passed a little bit of the madness, I think. You know? And look.

[00:04:45] - [Speaker 1]
It's great. You got new pieces of technology that comes in, a new way to to operate and run your business, and everyone tries to figure out what to to do with it first. Everyone tries to get first mover advantage from it, but we saw a lot of wasted effort. You know, people chasing AI use cases, everything started to look like a nail that could be hit by AI, and, you know, AI is the answer before we even finish asking the the the question. And I think what we've seen is folks move beyond that.

[00:05:14] - [Speaker 1]
And I think we talked about this a little bit before, but but, you know, really moving towards defined use cases where you can start to understand who's using it, who's engaging, what data is required to support that, what velocity of data is needed to support it. And that gives folks focus. It gives gives a way to to prove value and deliver value quickly, and then, you know, learn from that, move on to the next thing. And I think that's been the big the big shift in terms of the mindset behind behind where things are.

[00:05:47] - [Speaker 0]
And I'm curious. When you look at the market right now, where do you think the most strategies or some AI strategies that you may have come across are still misaligned with business reality? Do you still see a lot of that?

[00:05:58] - [Speaker 1]
I don't know if I think I'd I'd see AI strategies being misaligned with with business strategy. I mean, I've I've got asked the question a lot, you know, should we have an AI strategy? And, you know, perhaps the the the slightly contrarian view is no. You you you you don't need an AI strategy. You have to have a business strategy that fully encompasses AI.

[00:06:21] - [Speaker 1]
I'm sure there are plenty of people that would argue against the fact that that, you know, saying no, don't need an AI strategy is not a wise thing to do, but, you know, unless it's grounded in everything you're doing, unless it's grounded in the realities of of your your your business, you're not gonna get the results that you you want.

[00:06:37] - [Speaker 0]
And when moving from experimentation to execution, what are the the hardest decisions organizations need to make to actually shift from one to the other? You must have seen a lot of this as well.

[00:06:49] - [Speaker 1]
Yeah. There's a there's a load of considerations that that that sit in there. There's obviously the the sort of the technical architectural conversation that has to happen around the availability of of data. When you start to open the aperture with AI, do all of the folks that you're you're you're giving access to these AI tools have access and rights to all of the the data there? So there's a bunch of sort of technical things that I think sit there, but I don't I I don't think we should forget the the need for good governance, the need for good internal policy, the need for good enablement around AI, And I think, you know, a good understanding of of what is driving cost, other downstream impacts of that in terms of your sustainability metrics, in terms of energy consumption.

[00:07:36] - [Speaker 1]
So there's a whole host of different things that start to come into into play that that really start to manifest themselves when you you start making this very real.

[00:07:46] - [Speaker 0]
Yeah. And I think there's also a clear tension between the openness and control in AI, especially with data models, data sovereignty, ecosystems. How how is CLICK thinking about that balance at a strategic level?

[00:07:59] - [Speaker 1]
Yeah. Look. I I've often said that that our job is not to own our customers' data. You know, we want to be neutral but but deeply integrated. And I think that what we're doing with our tech ecosystems, the announcements this week around ServiceNow, but everything we then back that up with our MCP capabilities and the agents that we brought out is all about exposing and being part of a broader a broader ecosystem, a broader set of technologies that come together to help solve enterprise use cases.

[00:08:32] - [Speaker 1]
And I think that's an important mindset shift that we have to make in terms of, yeah. Look. We can try and grab everything and get a quick win by putting it all in one place, but sustainably, long term, I'm I'm convinced that's not gonna be the right the right model. Right? We've gotta work across the board ecosystem, and I think that means that end user, consumers, and enterprises are gonna have to think think about things differently.

[00:08:55] - [Speaker 1]
It means folks like ourselves, vendors, and technology companies are gonna have to think about things differently. That that the ecosystem is gonna, you know, dramatically change around AI and and and agents, and I think we can play a key role in helping our customers navigate an ever changing field. Know, you talked about two years is a lifetime. You know, what's this gonna look like in in two years? Well, you know, I I'm not sure I can answer that that question.

[00:09:24] - [Speaker 1]
What I do know is that that flexibility, that openness to work across an ever changing landscape is something that we've helped our customers do right from the very outset of click thirty years ago, and that still maintains itself today in how we think about AI and and the agentic world we play in.

[00:09:40] - [Speaker 0]
And throughout your career, you've seen multiple ways of enterprise technology from BI to cloud to now AI. Are there any patterns that you see repeating themselves, and where where do you see this wave being genuinely different?

[00:09:53] - [Speaker 1]
I think they're all all these patterns are are repeating themselves. Right? I I you know, I'm I'm old enough to remember, and I spent some time working at a company that would certainly not describe itself as an ERP provider, but that's really what it was back in the back in the day. And, you know, there was there was a whole notion that we're gonna cram everything into a single instance of our ERP. And for a whole host of reasons, the enterprises generally didn't didn't get there.

[00:10:18] - [Speaker 1]
Then everybody's gonna put all of their data into one data warehouse, and that's gonna solve all of their their problems. And invariably, not everybody managed to to achieve that. And we're gonna see the same thing with, you know, reliance on one LLM, one model. You know? So there's this continued cycle of of things that continue to be true, and I think back to the previous conversation around, you know, openness and and flexibility, I think that's still gonna define where we are long term.

[00:10:48] - [Speaker 1]
You know? So sharing assets across that that ecosystem are gonna keep coming up. You know? We're gonna keep making mistakes of of not understanding the implications of what it means for our teams, our people, and how we enable them. Right?

[00:11:02] - [Speaker 1]
That started with data literacy and started with AI literacy. We're gonna see that continue to evolve in the AI and agentic world between those that can derive productivity for their own function in their job or or their personal lives between those that that don't. So there's this sort of thematic theme of that that keeps coming around, and, you know, maybe, hopefully, this time we we learn from that and get it right.

[00:11:27] - [Speaker 0]
And a lot of vendors are pushing consolidation into single platforms. And one of the things that stands out at ClickConnect is you're emphasizing interoperability and flexibility. Is that a strategic bet? And and any risks that come with that, do you think?

[00:11:41] - [Speaker 1]
Look. I I think it is a strategic bet, and I think it reflects how we we we we think that this is gonna evolve. And and as I was just saying, I think think there's lots of proof points that could suggest that, you know, directionally, we're we're we're right. The risk is that we stop listening to our customers. Yeah.

[00:12:01] - [Speaker 1]
And that's something that we're not gonna do. Whether it's our customers or our partners, you know, this is our best ear to the ground. We can invest in research. We can understand the technology, but actually understanding what our customers are doing, I come to you here today straight from our executive advisory board meeting where we're debating and getting feedback from customers around a whole host of different topics that relates to AI, and that's something we do with them four times a year. We do that with our partner community four times a year.

[00:12:28] - [Speaker 1]
You know, we've got a whole host of announcements we'll be making about how we continue to figure out and learn from customers. So the risk is we we don't do that. So we have to keep listening. We have to keep responding and then prioritizing and focusing on the the the right areas.

[00:12:45] - [Speaker 0]
And if you were to take all those conversations you've had today and throughout the year, put them into a a big LLM and ask it, what are the trends from these conversations? Is there a particular repeating topic or anything that keeps coming up? The same questions?

[00:12:58] - [Speaker 1]
Yeah. Yeah. I think people are generally concerned around cost, and they're generally concerned around lock in. That comes up a lot back to the the, you know, the topic of of openness and interoperability. The importance of being able to navigate and work in a in a broader ecosystem.

[00:13:15] - [Speaker 1]
You know, people are trying to put and build solutions and put things together, and and again, that ecosystem that comes up a lot. How how do we support them in that? What is it all that we play? Well, that's alongside our partners like AWS or Snowflake, all the new announcements we made yesterday around around ServiceNow. That ecosystem piece, you know, keeps keeps coming up and is another in important part of the discussion.

[00:13:43] - [Speaker 1]
And then the final one, you know, is something that we talked a little bit about today in in the the keynotes around, you know, data sovereignty and and where this workload where these workloads are are are run and how that data is is protected as as part of, you know, what is an ever increasingly complex geopolitical landscape. You know? And that's the other big question I think people are trying to wrap their heads around and and frankly, another reason why I think the the openness and flexibility point is so important.

[00:14:13] - [Speaker 0]
Yeah. Completely agree. And when you look at the global markets, much is AI strategy now being shaped by regulation, sovereignty, and regional differences rather than just technical capability? Is there a big difference there, do you think?

[00:14:28] - [Speaker 1]
I think that that there should be. Yeah. I think I think that as we think about regulations, we think about policy, these are critically important important components. The conversation goes much more beyond that. You know, you we start to think about and it's been a very prevalent conversation around cost versus is compute that's been sort of, you know, going around for for a long time, and how do you manage that?

[00:14:52] - [Speaker 1]
You think about FinOps in the context of managing, you know, your AI infrastructure. The other big piece that really starts to come into play then is the energy that's needed to support that, what that means in terms of of of sustainability, and and what it means in terms of your supply of of of energy, which is we know in the the current times is a, you know, a a huge topic. And so when you've got energy scarcity, how's that navigate between those that have access to it and those that that don't? How does that play in into how you think about building AI in your organization? You know, do you optimize for cost?

[00:15:33] - [Speaker 1]
Do you optimize for efficiency? Do you optimize for sustainability? And these are all the sort of starts of of questions that I think will start to play big a part of the conversation, and frankly, I think should be a big part of the conversation.

[00:15:45] - [Speaker 0]
It's such an important topic because there is an increasing conversation around AI cost, not just capability. So how do you see economic pressure shaping how enterprises adopt and both scale AI over the next few years? How do you see that evolving? I know you haven't got a virtual crystal ball here, but do you see any signals?

[00:16:04] - [Speaker 1]
No. I I think I think that that we've we've gotta give ourselves the room to to invest. Mhmm. We've gotta give ourselves the the capability to to to perhaps avoid going for the the the quick win. There are plenty of quick wins in the AI space, but circumventing that data foundation is is definitely not one of them.

[00:16:24] - [Speaker 1]
So I think we've gotta be able to give ourselves the capacity and the space to invest, but I think over time, as we think about cost models in organizations, whether that's a tech company like ourselves or, you know, a services organization, we're gonna start building in the efficiencies we should be able to get, the productivity efficiencies that we should be able to get from AI and agentic deployments, and sort of resetting how we think about the COGS or the OpEx that's associated with delivering a a product or a service. So there's actually, I think, a really important window that we have right now to sort of invest and double down before the finance and the accountants catch up and work out that actually we should be running different functions of the business at more efficient levels. And you oversee corporate development and m

[00:17:16] - [Speaker 0]
and a. So as the AI market evolves, any kind of capabilities or gaps that interest you most in addressing maybe through partnerships or acquisitions? I know you can't reveal any any spoilers, but anything that particularly interests you?

[00:17:30] - [Speaker 1]
No. Look. There's a there's a lot of innovation that's going on out there there right now, and I am absolutely gonna dodge your question. You know, I I'm I'm gonna I'm gonna effectively say to you, look, there's so much innovation out there. Our job is, again, to listen to our customers, to listen to our partners, and we will talk to anybody that thinks they've got great a idea, and we'll see how it fits into to our vision and our and our strategy.

[00:17:55] - [Speaker 1]
And and look, one of the great things that we're seeing right now is not only the the evolution of of innovation within AI itself, but actually what that enables in terms of broader innovation across a whole host of of business domains. And I think that's one of the things that gets me most excited is that we don't quite know what conversations we'll be having and who we'll be we'll be having them with. But certainly, organic and inorganic together are a big part of how we've built what we can bring to our customers today.

[00:18:26] - [Speaker 0]
And continuing on that strategic vision, internally, how do you align product marketing and customer success around a strategy that is still evolving as quickly as AI is today?

[00:18:38] - [Speaker 1]
Look, our long term goal has always been very simple. Right? To be the best at helping our customers take advantage of of data analytics and AI to solve their all the world's biggest problems. Right? That's been the goal, the mission statement.

[00:18:51] - [Speaker 1]
That north star hasn't changed, you know, but what has changed is how we think about who we are as an organization, how we think about our role and our place in in in supporting our customers on this this AI journey. You know, when I don't think of Qlik as a data and analytics company with some AI. I think about us as being the organization that makes data work for AI at our customers because we've got these rich data management, quality integration, movement, and advanced analytic capabilities, because we're able to create those platinum level data models. And so the North Star vision, everybody at CLIC's been rowing in that direction for thirty plus years. How we get there has changed slightly.

[00:19:37] - [Speaker 1]
How we row the boat has changed slightly, but we're very focused on it, and and and we know where the direction we wanna go and and how we wanna we wanna get there.

[00:19:47] - [Speaker 0]
And when you step back from all of the announcements this week, is there a particular strategic shift that you think will matter most to customers and people listening over the next twelve to twenty four months? Is there any particularly anything that really stands out to you that businesses should be aware of and preparing for?

[00:20:03] - [Speaker 1]
Look, I think that what I would expect to see if we're talking again in a ClickConnect in a year's time, Neil, is customers deploying and working and using our technologies, but actually, folks realizing that the as Mike talked about today, they're closer to an agentic world than than perhaps people think. In Click, they built these platinum, these diamond level data models that are extremely useful and represent huge amounts of value to to AI and energetic initiatives in their organizations. And for folks that are starting from scratch, building that out is is not a trivial task. So for our 38 plus thousand customers that have built these models in Qlik over the last thirty three years, I think they've got a unique advantage, you know, and a head start, and that for me is exciting. That's what I wanna see evolve and be brought to life, and I think we'll see a realization of of that get turned into real value and real advantage for customers that are here with us this week in Orlando.

[00:21:08] - [Speaker 0]
And I think that is a powerful moment to end on. I'll have links to all the Clinc Connect footage and indeed your LinkedIn for anybody that wants to connect, but just thank you for stopping by today.

[00:21:17] - [Speaker 1]
Great. Neil, nice to talk

[00:21:18] - [Speaker 0]
to you. There's a very clear acknowledgment here that the industry has been through a phase of excitement, experimentation, and in many cases, wasted effort. But what comes next is far more demanding. As James pointed out today, success with AI is no longer just about chasing use cases or deploying the latest model. It's about aligning everything back to the business, the strategy, the data, the governance, and the outcomes that you're actually trying to achieve.

[00:21:50] - [Speaker 0]
And there was a moment that really stood out to me in the interview today, and that is this idea that you don't need an AI strategy at all. You actually need a business strategy that fully incorporates AI. Very subtle shift in language, but a significant shift in mindset there. And then there's the even bigger picture, cost control, data sovereignty, energy consumption. These are not edge considerations anymore.

[00:22:17] - [Speaker 0]
They are becoming central to how organizations think about scaling AI responsibly. So as we look ahead, the question is no longer who can adopt AI the fastest. It's who can operationalize it in a way that's sustainable, governed, and aligned with real business value. Yeah. We're getting back to the belts and braces of IT inside businesses, and I'd be really interested to hear your perspective on this.

[00:22:44] - [Speaker 0]
Are you still experimenting with AI? Are you starting to see it embedded into very real workflows across your organization? What has succeeded? What would you do differently? And what did you take away from this conversation?

[00:22:56] - [Speaker 0]
Please head over to techtalksnetwork.com. You'll find seven interviews from ClickConnect and 4,000 other interviews with so many other experts in their field across multiple industries. But that's it for today. I'll be back again tomorrow with another guest, but big thank you to James for meeting me in person today and recording this great conversation, and an even bigger thank you to you for listening right to the end. So I'll speak with you all again tomorrow.

[00:23:25] - [Speaker 0]
Bye for now.