Qlik recently secured new investors at a time when interest in AI is accelerating across various industries. What, in concrete terms, has changed for the company?
We’re still grounded in the same mission — using data analytics and AI to help our customers become better, stronger, and faster. What’s changed is the environment. There’s unprecedented attention on AI, and that’s attracted renewed interest from investors. One in particular — the Abu Dhabi Investment Authority (ADIA) — stood out for its deep commitment to AI’s global potential.
We recapitalized with them as a significant minority investor, which has energized the company. And with one of our major competitors about to be acquired by Salesforce, we now stand as the largest independent provider of data integration, analytics and AI.
While Qlik doesn’t produce green technologies directly, you play a role in enabling the transition to a greener future through data. Can you share some recent examples of Qlik’s role in climate action?
One strong public sector example is our work with C40 Cities. Despite the name, the network now includes around 17,000 cities worldwide. These cities wanted to move faster than some national governments on climate action, so they took independent steps, and we support them by powering their emissions tracking with our dashboards and AI capabilities.
Our platform helps them monitor progress and share best practices to reduce emissions more effectively.
In the private sector, Schneider Electric uses Qlik across its operations, including tracking 800 million tons of CO₂ savings. They’ve committed to cutting emissions by 50% across their entire supplier network, and we provide the infrastructure to support that. Food Bank Victoria is another example — they use our technology to coordinate food distribution across NGOs and government systems, helping reduce emissions tied to transportation and logistics.
You’ve advised the White House on AI policy. With AI evolving faster than regulation, what’s one concrete step governments or companies should take to ensure responsible AI use?
Governance and intent are critical. Under the prior U.S. administration, we focused on democratizing AI — making sure the benefits didn’t just go to large companies. That effort has unfortunately been abandoned, but in the private sector, we’re still working to ensure AI is accessible to all. Since governments can’t always keep up, we’re making commitments ourselves.
The key is making AI available and beneficial to the many, not just the economically powerful few. Patterns shift, and AI models must adapt in real time. Sophisticated companies don’t measure carbon once a year — they do it hourly. Our technology helps detect model drift, alerting users when data inputs begin to shift and potentially invalidate previous assumptions. Constant monitoring and real-time machine learning are essential to staying accurate.
Despite being in nascent stages, you’ve been optimistic about carbon capture technology and its role in cutting emissions. What data trends give you hope now when it comes to sustainability?
When a problem becomes dire enough, I believe technology can solve it — if we’re willing to invest consistently. Unfortunately, we often abandon new tech too quickly. In the U.S., we’re already seeing wind projects off the East Coast being scrapped. Carbon capture remains high on my list.
It’s like water: desalination exists — it’s just expensive. But countries like Israel and the UAE do it routinely. We have the technology to solve climate change, and AI will help bring down costs and make it viable. So, I’m optimistic.
Projects like offshore wind farms have faced delays or withdrawals due to economic and supply chain hurdles. How could a better use of data at the planning stage have helped anticipate and avoid such setbacks?
Sustainability used to be treated like an annual checkbox — a glossy report to make things look good. But it wasn’t always backed by real action. Now, sustainability has to be embedded into everything. Wind projects often fail due to supply chain issues — geopolitical conflicts, tariffs, canal closures.
That’s why sustainability needs a resilience strategy too. We help by using data to reroute shipping, navigate supply disruptions, and build plans that can adapt to change.
What do you see as the most legitimate concerns around AI right now, and how is Qlik tackling them?
In the wrong hands, AI is dangerous. Privacy is a very real concern. The use of AI in facial recognition and profiling is just wrong — it’s not good for society. We don’t allow Qlik to be used for those purposes. That’s a firm stance for us, and probably my biggest concern with AI.
We’re not waiting for regulation to catch up — we’re proactive. We formed an AI Council made up of experts outside our industry — from academia and public policy — to advise us on societal trends and concerns. They help guide how we behave in the market, how we build products, and how we embed ethics into our development process. At the same time, we’re seeing exponential advances in the technology itself. The availability of computing power — especially through cloud infrastructure — has blown the doors open. Some AI companies are even buying and reactivating nuclear power plants just to run their systems. But the real challenge isn’t power — it’s data. Governance, cleansing, and harnessing the right data is what’s lagging. Once we get that right, AI is going to take a quantum leap forward.
As technology evolves rapidly, how are your conversations with potential clients changing — especially in sectors like energy storage that may be newer to data-driven decision making?
The encouraging thing is that every sector now recognizes the need for data integration, analytics and AI — no executive or government official isn’t thinking about it. We’re especially active in healthcare, finance, manufacturing, retail, and the public sector, where demand is accelerating. But in emerging sectors like energy storage, there’s often a gap in awareness. These companies may not realize what’s already possible with real-time data streaming and analytics — or even where to begin.
Part of the challenge is communication: big players with large marketing budgets often dominate the AI narrative, even if their capabilities are limited, which creates confusion. In newer industries, the competitive pressure to adopt data tools might not be there yet, and advisory firms sometimes treat analytics, integration, and governance as separate pieces — whereas we see them as one connected ecosystem. Helping clients understand the bigger picture is a key part of what we do.
