In this interview from Qlik Connect 2026, Christopher Powell, chief marketing officer of Qlik, joins theCUBE Research's Rebecca Knight and Rob Strechay to discuss how enterprises are moving past AI experimentation toward operational dependence — and what foundational work that shift demands. Powell argues the AI inflection point is less about whether the technology works and more about whether the data does. He outlines three prerequisites for enterprises ready to operationalize AI: a trusted data foundation, deep contextual understanding of proprietary environments and architectural flexibility to adapt as innovation accelerates. To address the trust dimension, Powell highlights Qlik's trust score for AI, which evaluates data lineage, provenance and access history to give AI systems confidence in the inputs they're acting on.
The conversation also explores how leading organizations are building human expertise into agentic systems before removing humans from the loop — a model demonstrated on stage with UPS, where domain knowledge defines the boundaries of autonomous action. Powell breaks down the evolution from standalone AI tools to agents to fully agentic workflows, noting how this progression is dissolving organizational silos and forcing companies to build shared data foundations across marketing, sales and customer success. He underscores cost management as a strategic imperative, warning that AI environments built without embedded cost controls will fail to scale. From emerging efficiency stories — including customers spending a few hundred thousand dollars to save $15 million annually — to the broader organizational rethinking required to lead in the AI era, Powell outlines why companies that ask not how AI can improve existing processes, but how it will fundamentally transform them, are the ones best positioned to win.
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Roberto Sigona, Qlik
In this interview from Qlik Connect 2026, Christopher Powell, chief marketing officer of Qlik, joins theCUBE Research's Rebecca Knight and Rob Strechay to discuss how enterprises are moving past AI experimentation toward operational dependence — and what foundational work that shift demands. Powell argues the AI inflection point is less about whether the technology works and more about whether the data does. He outlines three prerequisites for enterprises ready to operationalize AI: a trusted data foundation, deep contextual understanding of proprietary environments and architectural flexibility to adapt as innovation accelerates. To address the trust dimension, Powell highlights Qlik's trust score for AI, which evaluates data lineage, provenance and access history to give AI systems confidence in the inputs they're acting on.
The conversation also explores how leading organizations are building human expertise into agentic systems before removing humans from the loop — a model demonstrated on stage with UPS, where domain knowledge defines the boundaries of autonomous action. Powell breaks down the evolution from standalone AI tools to agents to fully agentic workflows, noting how this progression is dissolving organizational silos and forcing companies to build shared data foundations across marketing, sales and customer success. He underscores cost management as a strategic imperative, warning that AI environments built without embedded cost controls will fail to scale. From emerging efficiency stories — including customers spending a few hundred thousand dollars to save $15 million annually — to the broader organizational rethinking required to lead in the AI era, Powell outlines why companies that ask not how AI can improve existing processes, but how it will fundamentally transform them, are the ones best positioned to win.
In this interview from Qlik Connect 2026 in Orlando, Roberto Sigona, chief operating officer of Qlik, joins theCUBE's Rebecca Knight to discuss why the biggest obstacle to enterprise AI adoption is rarely the technology itself — and what it takes to move from data collection to real, measurable business impact. Speaking from Qlik's Sports Pavilion, where live dashboards track athlete performance in real time, Sigona argues that the harder challenge is process change and human habit. He notes that AI requires enterprises to fundamentally reinvent workflows, no...Read more
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Where do companies and organizations most often stall when adopting new technologies (for example, AI)?add
What do you see as the next developments in AI adoption—moving from dashboards to agentic systems and agent-to-agent interactions—and what will the role of humans in the loop be?add
>> Hello, everyone, and welcome to theCUBE's live coverage of Qlik Connect 2026 here in Orlando, Florida. I'm your host, Rebecca Knight, and we are here at the Sports Pavilion, which is part of Qlik Connect 2026. I'm standing next to Robert Sigona. He is the COO of Qlik.
Welcome.
Roberto Sigona
>> Thank you. Thank you for having me.
Rebecca Knight
>> This is really exciting because it looks like-
Roberto Sigona
>> It is exciting.
Rebecca Knight
>> It looks like we're here with a lot of fun and it looks like sports and fun and games, but actually, it's data.
Roberto Sigona
>> It is data. Sports is like everything else we do in life now. You want to optimize your performance by measuring everything you do. So we see golf, we see hockey. Every single athlete right now measures as sensors on their shoes here on the golf club, on the swing, to measure and optimize what you can do. And we create a live dashboard that shows your performance and maybe tells you a couple of things to improve.
Rebecca Knight
>> Well, exactly. So speaking of data, and this is where customers can really stall out because it's not necessarily the technology that trips them up. It's often the capability, the confidence, the mindset that they're in. What do you see most often in terms of where companies and organizations stall?
Roberto Sigona
>> Well, revolutions in technologies, that's not the first one we have. AI is probably fastest that we've seen. But I guess the technology is part of it. You have to adopt the technology. You have to learn about the new technology. The issues tend to be around the process changes you have to make and the people. The people and the habits. We are creature of habits. We used to do things a certain way, and you have to reinvent yourself. Doing AI, for example, is not doing the same things you were doing before, just faster. You have to reinvent the process. Not everybody's ready to do that.
Rebecca Knight
>> So it's really change management-
Roberto Sigona
>> Change management....
Rebecca Knight
>> and winning hearts and minds and helping workers understand what they need to embrace in terms of new skills, new ways of thinking, new ways of doing things.
Roberto Sigona
>> That's exactly right.
Rebecca Knight
>> So tell me a little bit about ROI and about how you are measuring success across very different and varied customer environments.
Roberto Sigona
>> Well, ROI is measured always in terms of what the customer's outcome are. It's not always true, though. We tend to measure what we can measure, and not everything we can measure matters. And not everything we need to measure is measurable. So that ROI needs to be defined clearly in terms of outcomes for the end users, for the business, for the customer. So then in terms of measuring it afterwards and achieving it, I think it is about also breaking things down into manageable chance. I think what I see a lot when I travel is people being too enthusiastic about the technology and trying to do too much. I want to get from zero to 100 in five seconds. Technologies and improvements happen every day a little bit, so today needs to be better than yesterday. And I have to have a plan to make better tomorrow. So AI and all the new technology is the same. The data foundation takes time, as you heard today, but in terms of delivering the goods, just deliver chunk-wise so people are getting engaged, they see things moving, and then you get the change management going. People get excited when they see success.
Rebecca Knight
>> But I think to bring it back to what we're seeing here today at the Sports Pavilion is we are swimming in data. And it's really about paying attention to the signals that matter to your performance, your organization's performance, and being able to separate the signal from the noise, because not all of it does matter.
Roberto Sigona
>> No, it doesn't. It's true. Here, certainly we seeing golf, I'm not golf expert, but I'm sure the wind doesn't affect. I'm sure how fast you swing and the angle at which we swing. So there are each specific activities. Like any sports, you have specific characteristics you're looking for to optimize. So you need to know that. You have to have the right signals to be able to act upon, and then when you know what the signals you want, you have to just gather the data that gives you that signal.
Rebecca Knight
>> Roberto, you have made data literacy a key part of your strategy.
Roberto Sigona
>> Yes.
Rebecca Knight
>> How do you think it changes or affects the customer experience?
Roberto Sigona
>> Well, we're just talking about not everything that matters is measurable and you have to be key with your KPIs. Data literacy is... And in the switch with the AI we're seeing right now, it's becoming even more important. You cannot believe everything ChatGPT tells you. So this critical thinking, being able to understand what you see, be able to check the source, being able to understand and argue with data is becoming more and more important. So we used to talk about data literacy. Now, we're going to talk about AI literacy, which is data literacy plus the fact that you have artificial intelligence maybe being too creative, and you have to harness that power to just control it.
Rebecca Knight
>> Right. So if education is part of a growth strategy then, how do you measure success and how do you know what good looks like?
Roberto Sigona
>> It's a good question. So I don't think I have a perfect answer to this, but I think, as I said, improvements happens over time. You have to freeze the frame to understand if you're making progress, otherwise you just don't know because some of the change and improvements you make might be small increments every day, so you never reach a goal, a big flag. So you have to just be realistic and have mid and long-term objectives. So there's no magic answer other than in my career, doing IT for many years, it's always about continuous improvement and do not change direction. Keep it steady with your belief. And then again, very steady progress every day.
Rebecca Knight
>> Last question. Where do you think this is all going? You're a technology veteran. What are we going to be talking about at next year's Qlik Connect? What is your biggest prediction for the future?
Roberto Sigona
>> Well, I think we can see it already. Right now, we're talking about moving from dashboards into AI, AI prints, and then we're starting to do agentic. Most of our customers are doing that. I think next year, we're going to be talking about agents talking to agents. And I think we're going to start talking a lot more about what does the human in the loop mean? When do we need to have the people who have the skills who understand how good looks like, just monitoring the process, because I think we can be a little bit too fast in rushing. Is AI going to take over and becoming independent? It might one day. The technology is evolving very fast. But I think we're going to be talking about this balance of how fast the AI is going, the agent-to-agent conversation, and the role of the human being, not just technology.
Rebecca Knight
>> I am glad to hear the role of the human being. And maybe you're going to try out a little golf and a little hockey. I know you're Swiss, so you will-
Roberto Sigona
>> I could try, yeah. I'm definitely better at hockey than I am at golf.
Rebecca Knight
>> You were skating before you could walk.
Roberto Sigona
>> Yes, exactly.
Rebecca Knight
>> Well, it was a pleasure having you on. Thank you so much.
Roberto Sigona
>> Thank you so much for having me. Thank you.
Rebecca Knight
>> I'm Rebecca Knight. Stay tuned for more of theCUBE's coverage of Qlik Connect 2026. You're watching theCUBE, the leader in enterprise tech news and analysis.
Rebecca Knight