Could you share the solutions that IFS implements and the industries it serves?
We focus on capital-intensive, asset-heavy, and data-rich sectors. That includes construction and engineering, manufacturing, aerospace and defense, telecommunications, and energy, natural resources, and utilities.
Our customers often have thousands of engineers in the field. They are dealing with emergency responses, weather-related damage, or faults in infrastructure. Many still rely on spreadsheets or rigid on-premise tech that has not modernized. We provide state-of-the-art planning, scheduling, and optimization tools to manage the full lifecycle of an asset.
What are some case examples of challenges IFS has solved for its clients at scale by replacing legacy systems with a new digital solution?
Take a large oil company building a refinery. You have got capital allocation, execution, materials management, and once it is operational—maintaining safety and productivity with maybe 200 people. Our platform supports the entire chain, from spare parts to maintenance.
The same applies to manufacturing or aviation. We factor in every data point—fault criticality, customer priority, engineer skillsets, locations, parts, road conditions—to optimize daily schedules. An engineer wakes up to a traffic-optimized route, collects likely-needed parts based on historical data, and goes to work. All orchestrated through IFS. This typically cuts costs by 30–35% and reduces carbon intensity by up to 25% through more efficient fuel use and processes. We also offer a market-leading ERP that integrates tightly with this. For example, in aviation, when an engine is deconstructed, we generate a purchase order, track the part, and schedule its replacement—say, after 25,000 flying hours.
How is IFS integrating Gen AI technologies into its offering?
Most Gen AI use cases today are natural language driven. In our case, think about a field engineer repairing a telegraph pole— they are not typing into a device. They are using voice, video, and images. “This is what I am seeing—what should I do next?” That is Gen AI in action.
But Gen AI today largely targets the 20% of the global workforce behind desks. The other 80%—the field workers—need a different approach. We are focused on Industrial AI, embedding it within customers’ operations.
For example, with a global oil company, our system takes engineers’ inspection notes and analyzes them. Gen AI helps abstract the language, but the value lies in diagnosing root causes, referencing tens of thousands of previous cases, predicting needs, and automating procurement and work orders. Someone recently said, “Industrial AI is like AI with hard hats on”—which I really like.
With the demand for Gen AI solutions, what kind of new resources or capabilities does that require of IFS? Do you find yourself competing with standalone AI software companies or collaborating?
What we are seeing now is a lot of startups and vendors bringing point solutions to market that solve very narrow problems with big ROI—which is amazing. We invest in some and also make acquisitions. But our customers do not want to manage 600 startups. We give them deep industry understanding along with that kind of innovation. Earlier this year, we launched Nexus Black—a high-touch team of UX designers, AI engineers, data scientists, and product experts, many from places like Anthropic, OpenAI, and Grok. They work directly with customers—like in wildfire-prone North America—to build next-gen solutions, which we then integrate into our core offering for all customers to benefit.
There is a challenge though—people say systems are going to get deprecated, that companies like us will not exist anymore because of all the innovation out there. I do not think so. We serve mission-critical industries—aircraft carrying passengers, big refineries, nuclear plants—you cannot just throw Silicon Valley startups at those problems. You need rigour and end-to-end process expertise.
Which global markets do you perceive as the most fertile for software development and innovation and in terms of recruiting a top-tier team?
My view may not be what people want to hear, but I think Silicon Valley is still significantly ahead as a source of development, innovation, and talent globally. I travelled earlier this year with some of our board to Silicon Valley, and I was just blown away. It is a concentration of capital, experience, education—Stanford of course—success stories like Apple in Cupertino. And what really struck me was the intensity of the workforce there. It is not like Miami, London, or New York with distractions. People are there to work, to break barriers. There is a fizz in the air when you meet people.
I do think there is a job for Europe. Scandinavia, particularly Sweden, has historically been a great source of innovation. They invest more in R&D relative to GDP than any other continental European country, I believe. London is also recognised as a hotspot for AI talent—DeepMind came out of London, and even Mustafa, Microsoft’s Chief AI Officer, is a Brit. So there is incredible capability, but it does not feel the same as Silicon Valley. I think it comes down to capital availability, venture capital especially. That gets into broader economic, taxation, and fiscal policy challenges. Capital is more available in North America, and that is something Europe needs to fix.
As you travel various places and hear various perspectives on staying agile in the fast-moving tech space, what leadership advice do you think is especially powerful in 2025?
It is basic—be willing to disrupt everything. We have issued internal guidance I often share with other CEOs: challenge your own model. We have frozen hiring except for billable, revenue-driving roles. But teams can spend freely on new AI capabilities. Everyone at IFS has access to AI tools and support to get onboard. We are deliberately slowing headcount growth in favor of AI investment.
Also: use the tools yourself. Leaders have to walk the talk. I have seen the lightbulb moments in my team when they do. Mine happened on a delayed flight in Vietnam. I had never heard of VietJet, so I asked AI about the airline—20 planes, expanding rapidly, opening a facility in Laos. Then I asked for the email of their head of technical ops and had the AI draft a message: I am CEO of a world-class MRO provider, love what you are doing, would like a chat. I got a reply the next day and a meeting was set. That took 15 minutes. Normally, this cycle would have taken weeks. Now I use Grok 4, Perplexity, OpenAI, Claude—everything. I switch tools depending on the job, constantly learning. That is the skill. There is no substitute.
