Chief digital and information officer Robert Oh discusses the truck and engine manufacturer’s four-pillar digital strategy, 2030 vision for a digital enabled business, and driving stakeholder engagement across the $11 billion business.
Illinois-based International Motors faces a familiar challenge for legacy manufacturers: integrating AI capabilities while maintaining operations that have sustained the business for two centuries. With a track record of heading tech across a range of companies and industries, CDIO Robert Oh is facing the issue head on by incorporating a comprehensive digital strategy based on key strategic pillars and new cross-functional co-innovation labs.
What’s the overall transformation currently underway at International?
International was founded nearly 200 years ago, so transforming business models, products, and how we service our customers is core to what we do. With this transformational DNA in our culture, we’re very intentional about our AI and digital transformation journey by dividing it into four building blocks: next-generation cybersecurity, ways of working, integrated digital platforms, and new and emerging technologies.
Next-generation cybersecurity includes IT, operational technology (OT), and connected products. Now in my fourth CIO role, I know we can’t undertake a digital transformation unless the board and executive team prioritize ongoing security investments.
We’re working in a two-speed operating model where we use both traditional IT delivery methods for our corporate functions while applying agility and design thinking in our digital product organizations. As an established enterprise, we need to balance risk and innovation, and manage our legacy environment. Also, budget, resources, and priorities must be thoughtfully aligned, and managing tech debt and other foundational aspects can be methodical, while innovation, AI, and customer-facing capabilities must move faster.
Our integrated digital platforms will connect six core enterprise systems into a digital backbone, while new and emerging technologies prioritize things like AI and development of software-defined vehicles, for example.
How are you working AI capabilities into your overall business strategy?
We organize our AI initiative into multiple pillars: strategy and roadmap, portfolio management, talent development, and the AI technology stack.
Imagine a Venn diagram with three circles: the top is the outside-in perspective where we look at how leading companies, including our competitors, leverage AI and the winning use cases that get published.
In the second circle are our business process areas such as finance, commercial operations and aftersales, procurement, R&D, production and logistics, and more. These are the mature domains where AI will provide the most business value. Data liquidity is the third circle. What available data sets do we have now that don’t need transformation? The overlapping area is where we have immediate value creation opportunities.
What’s been the early output of your approach to baking AI into your transformation?
In March, we were initiating AI within certain functions, and today we have more than 50 cross-domain, enterprise-wide business ideas in backlog, and we’re kicking off three beta use cases now. By clearly weighing business value alongside our ability to act and execute, rather than relying on generic decision criteria, we’re able to select lead management for our commercial business, spend analytics for procurement, and dealer-network customer service for aftersales. Using this lens, we also brought in tech, product, operations, and external partners into a co-innovation lab with pods for each business area. The goal of the lab is to develop an agile use-case delivery model, which we’ll fine-tune and scale beginning in 2026.
How did you get everyone aligned around the vision for an AI enabled business?
We engaged each executive leader to appoint strategic and experienced domain leads to join the AI co-innovation team, with representation from every function. These leaders bring a deep understanding of their respective domains and priorities, and through their involvement, they’re also developing a stronger perspective on how AI can advance their business goals.
To inspire the new group, I used something I learned from an Amazon leadership strategy, which is to work backward. So in our first meeting, I asked them what do we want to be known for when it comes to AI in 2030? They started to think less about current operational issues and more about future vision. They wrote a visionary two-page press release designed for 2030 that outlined the aspirations, achievements, and approaches to get us there.
This press release became our cornerstone, so when challenges come up, we can reflect on them and ask if we’re deviating or slowing down. The answer is always to re-commit to our vision, and through this collective exercise, we sparked the light to guide our future.
How are you transforming your senior team for this transformation?
Over the years, I established five guiding principles, or five As, for my leadership team, the first being to maintain big and bold aspirations. When we approach AI and digital initiatives, we don’t limit ourselves to incremental process improvements. We envision transformational possibilities five years into the future and work backward from those ambitious goals.
The second is embracing ambiguity. Bold aspirations naturally create uncertainty, which is not something to fear since it’s an inevitable part of breakthrough innovation. Third is focusing on building strategic alliances. Co-innovation and co-creation are essential both internally across our organization, and externally with our ecosystem of technology partners, startups, and universities that may have solved similar challenges.
The fourth is moving with agility. Rather than lengthy development cycles, we operate in six- to eight-week experimental sprints where we can test concepts, gather insights, and demonstrate business value quickly.
Finally, we continuously assess and iterate, refining our approach until we achieve optimal outcomes. This framework guides how I expect our entire organization to operate.
What are you doing architecturally to support the 2030 vision?
With innovations dating back to the early 1800s, our organization doesn’t have greenfield IT, which creates system complexities, but we’re making fundamental architectural changes. First, we’re modernizing our integration layer, and instead of maintaining one-off, point-to-point interfaces, we’re shifting to an API reuse model called “collect, curate, and consume” rather than rebuilding everything from scratch.
We’re also tackling data liquidity. We currently have multiple sources of truth across the organization, so we’re building gateways to connect to our data securely, and investing to ensure it’s accurate, clean, and ready. And third, we’re transitioning to a multi-cloud environment, building capabilities to be more agile and to avoid redundant functionalities across platforms.
For a traditional manufacturing company like ours, the real measure of digital transformation success isn’t architectural, but cultural. When product development discussions include AI, data, and UI/UX experts alongside mechanical, software, and electrical engineers from day one, we’ll know we have transformed. We’re working toward that as it’s our guiding star.
Throughout your many transformational leadership roles, what advice would you give regarding stakeholder management?
I like the lighthouse concept, which is taking a traditional manufacturing process, for example, applying AI algorithms to it, and showing your stakeholders a very tangible business result. These examples show what’s possible through AI, and allow us to drive curiosity and ongoing engagement. Lighthouses illuminate what’s possible, and they give people hope.
But more broadly in stakeholder management, pay attention to how well potential business partners embrace ambiguity. Operational leaders aren’t always comfortable with it and may shy away from innovation and change. Over my career, I’ve learned to manage stakeholders based on their tolerance for ambiguity and their technical acumen. As a technology executive, I could assume everyone understands that the technical landscape changes daily, but I need to take everyone, regardless of where they are, along the transformation journey. This is probably my most valuable lesson, yet it’s also one where I remain a student and continue to grow each day.
