IBM and Riyadh Air: How AI-Native Design Is Redefining Global Aviation

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IBM and Riyadh Air formalized their partnership in February 2025. The aim wasn’t to modernize old infrastructure; it was to avoid it altogether. There’s no legacy code here, no patchwork systems to untangle. Riyadh Air is making early choices that most airlines never get to. With no legacy systems to manage, it can build core operations with AI and automation where they matter, rather than forcing them in after the fact.

The announcement comes at a time when legacy carriers are bogged down by brittle integrations and fragmented digital strategies. In contrast, Riyadh Air has no such historical baggage; its IT stack is being purpose-built from the ground up to support AI-driven workflows, data-centric operations, and hyper-personalized guest experiences.

IBM is leading integration across more than 50 core airline systems. That includes everything from flight ops to guest experience, built to work together from day one, not layered on later. These will be orchestrated using IBM Cloud Pak for Integration and Red Hat OpenShift and will feature watsonx as the AI backbone. IBM’s dual-operating model, Garage for innovation and Consulting Advantage for scale, ensures the architecture is both visionary and executable.

Greyhound Fieldnotes from engagements with global aviation CIOs reveal mounting frustration with patchwork digital retrofits. CIOs across EMEA and Asia-Pacific cite the rising cost of modernising legacy infrastructure without meaningful ROI. Against that backdrop, IBM and Riyadh Air’s clean-slate approach is both rare and enviable.

Greyhound Research views this not just as an IT rollout; it’s a rethink of how digital infrastructure gets built when you don’t have to work around legacy baggage. That’s rare in aviation, and even rarer at this scale.

Turbulence in the Market: The Case for a Clean-Slate Airline

Airlines across the world are accelerating digital transformation, not just to optimize cost, but to survive in a market where agility is becoming a precondition. From Lufthansa’s AI-enabled ops to Emirates’ cloud-native backend upgrades, carriers are no longer only competing on route networks and loyalty programs. They’re building smarter platforms, ones that learn, adapt, and help respond faster to market conditions.

But progress isn’t even. Many traditional carriers are still working around infrastructure that was never designed for the velocity or volatility of modern aviation. Systems have been layered, patched, and retrofitted over time. In some cases, the tech stack spans four generations of tools and contractors. The outcome? High operational friction, inconsistent data access, and growing vulnerability to disruption, whether it’s from geopolitical events, regulatory changes, or weather-driven irregular ops.

That’s what makes Riyadh Air an outlier. Unlike most, it’s starting fresh. There’s no legacy stack to stabilize. No brittle integrations to preserve. It’s being designed for data flow, automation, and real-time responsiveness from the first line of code. And that, in the context of Saudi Arabia’s broader Vision 2030, gives the airline both operational flexibility and national strategic relevance.

According to Greyhound CIO Pulse 2025, 67% of global transportation CIOs now identify AI orchestration as the next big lever, not just for efficiency, but for responsiveness. On the financial side, CFOs are growing increasingly uneasy with sunk-cost infrastructure that can’t adjust to market signals in real time. Visibility alone doesn’t cut it anymore. Operators want early warnings, scenario planning, and systems that adapt without manual handoffs.

Greyhound Fieldnotes from airport operations leaders across Europe and Asia point to familiar barriers: latency across systems, unclear compliance boundaries, and costly integration projects that never really deliver scale. Without a modern cloud-native backbone, many digital efforts still stop short of real transformation.

That’s where Riyadh Air’s architecture, built on watsonx and Red Hat OpenShift, stands out. watsonx is being used not in isolated pilots, but across guest journeys, predictive ops, and staff enablement. Red Hat OpenShift ensures consistency in how apps run, whether in an airport data room, on edge infrastructure inside the aircraft, or in public cloud regions.

Greyhound Research believes this alignment between national ambition, technical readiness, and execution headroom rarely comes together in one place. Riyadh Air has the unusual opportunity to build not just a modern airline but a platform that reflects where digital aviation is headed next.

Co-Design at Altitude: How IBM and Riyadh Air Are Building Together

This isn’t a standard vendor-client arrangement. Riyadh Air and IBM are co-building the airline’s digital foundation, every layer of it. IBM Consulting is leading integration across more than 50 enterprise systems, from passenger experience to core operations. It’s not just coordinating vendors; it’s shaping the execution itself.

At the center is IBM Garage, which combines design thinking, agile delivery, and co-creation rituals. It’s not a one-size-fits-all model. The delivery plan has been tailored to fit the moving target of building a new airline, where regulations are still being interpreted, team roles are evolving, and core tech components are being rolled out in parallel. It’s not just about delivery velocity; it’s about keeping both architecture and people in sync as they scale.

IBM’s watsonx platform sits underneath all of it. It’s used to power guest personalization, predictive ops, and internal knowledge tools. ModelOps governs the AI lifecycle, so models aren’t just launched; they’re monitored, retrained, and replaced. DataOps ensures clean pipelines across structured and unstructured sources, reducing lag and redundancy.

IBM Cloud Pak for Integration is being used to wire the core, connecting flight ops, ground handling, loyalty systems, crew schedules, and more. On top of that sits Red Hat OpenShift, which ensures that services can run consistently, whether in a public cloud region, an on-prem airport server, or on edge hardware aboard the aircraft.

Greyhound CIO Pulse 2025 data shows that 64% of global enterprises believe shared ownership models accelerate time-to-value in complex platform deployments. Riyadh Air is already reflecting that pattern. Integration here isn’t a technical afterthought; it’s been treated as a design constraint from the outset.

Greyhound Research believes this is the right model for high-stakes transformation: shared execution, cross-embedded teams, and operational capability transfer baked into the build. It’s not just an implementation method. It’s the foundation for long-term independence.

Beyond Efficiency: The Commercial Upside of AI-Native Aviation

Most aviation technology projects are designed to trim costs or improve efficiency around the edges. This one wasn’t. The Riyadh Air and IBM partnership is structured to create entirely new revenue behaviors, ones that emerge from orchestrated, AI-enabled systems working in real time across the airline.

Early implementations already show traction. The teams have built out use cases for dynamic pricing, AI-assisted upselling, and real-time route profitability, all tied into operational data streams. watsonx sits at the core of this architecture, enabling intelligent personalization across the entire customer journey, from pre-booking nudges to onboard experience. According to Greyhound Fieldnotes from CXOs at regional carriers, this style of monetization is fast becoming a priority, particularly for premium-heavy business models that can’t rely on volume alone.

From a financial operations view, the bigger signal is cycle compression. IBM’s use of Garage delivery and a fully modular design has reduced typical deployment timelines by several months. Greyhound CIO Pulse 2025 confirms that 58% of CFOs in transport and logistics now expect AI projects to yield hard ROI inside a two-year window. Riyadh Air appears on track to outperform that benchmark, thanks to reusable components, short feedback loops, and pre-baked model governance.

But the real benefit isn’t faster rollouts. It’s a shift from reactive workflows to anticipatory ones. Predictive maintenance is already projected to reduce aircraft downtime by up to 30%. Crew scheduling systems, fed by real-time weather, flight status, and workforce data, are being tuned to adapt automatically. And on the guest side, conversational interfaces and intent prediction tools are being used to lower call center volume while improving resolution quality.

These aren’t one-off improvements. They’re stitched together across the stack, data from operations informs marketing, guest engagement shapes workforce planning, and everything feeds back into the next round of decisions. The result is a system that adjusts to change instead of requiring manual coordination to keep up with it.

Greyhound Fieldnotes from transformation leaders at large regional carriers suggest that this kind of integrated, closed-loop feedback system is what separates future-ready platforms from overbuilt pilots. It’s not just about doing more with data; it’s about ensuring each layer of the organization sees and reacts to the same signals.

Greyhound Research believes the real breakthrough isn’t reduction in time-to-deploy. It’s that Riyadh Air now has the infrastructure to turn every AI capability it builds into a monetizable service, internally and externally. That’s the move from running systems to running intelligence.

The Hidden Friction: What Riyadh Air and IBM Had to Untangle

Even with a greenfield build, things rarely go smoothly. For Riyadh Air and IBM, the challenge wasn’t replacing legacy; it was working out how fast to move, how much to build in parallel, and how to get alignment when the end-state was still forming.

The first bump usually comes from within. Greyhound Fieldnotes from other large transformation programs show that mid-level managers often hesitate early. At Riyadh Air, the story is no different. The pace of agile sprints and the unfamiliar territory of AI-driven design raised questions about job security, unclear responsibilities, and how existing experience would fit into the new ways of working. To address these, most programs use a “change mesh,” a distributed group of functional champions embedded across departments. These aren’t external consultants or internal cheerleaders. They are hands-on contributors who can decode strategy, handle objections, and spot resistance early.

Integration is usually the next stress point. With multiple systems going live at once, including crew scheduling, HR, finance, and ops, the sequence of delivery matters. Dependencies shift. Priorities compete. IBM’s use of ModelOps and DataOps gave the team at Riyadh Air better visibility across moving parts. OpenShift helped keep things modular so individual components could scale independently, rather than waiting on everything to stabilize at once.

Compliance is a quiet, but real, complexity. Operating across jurisdictions meant explainability cannot be optional. Audit trails have to be designed in from day one. watsonx’s tooling helps accelerate that process, but the work still needs time and local context to get right.

Greyhound CIO Pulse 2025 shows that 48% of aviation CIOs rank “change fatigue” among middle management as their top transformation barrier. Riyadh Air didn’t eliminate that risk; it built systems to listen for it. By combining design rhythm with operational empathy, the team was able to keep momentum without leaving people behind.

Greyhound Research believes pushback isn’t a red flag; it’s a data point. How organizations use those early signals to adapt the model often determines whether the transformation sticks or eventually stalls.

The CXO Playbook – Ten Replicable Strategic Takeaways

Designing an AI-native airline used to sound like an ambition. Now it’s becoming a reference point. For CIOs, CTOs, and enterprise transformation leaders looking to apply lessons from Riyadh Air’s build, here are ten takeaways rooted in experience, not just strategy decks.

1/ Don’t bolt AI on. Build with it from the start. Most enterprises add AI to legacy environments and wonder why it stalls. Riyadh Air did the opposite. AI was part of the first technical decision, not the last. watsonx isn’t sitting in a lab; it’s inside processes, ops, and interactions from day one.

2/ Treat models like living things. Once deployed, models change. Riyadh Air was built for that. ModelOps wasn’t an afterthought; it’s part of the rhythm. Models are retrained, adjusted, and retired like products, not assets. If your operating model doesn’t expect drift, it won’t manage it.

3/ Hybrid cloud isn’t a compromise; it’s control. Compliance and agility don’t naturally get along. But they can coexist if architecture allows it. By using IBM Cloud Pak for Integration and Red Hat OpenShift, Riyadh Air separated control layers from velocity, giving both regulators and developers what they need.

4/ Break the org chart to build the architecture. Agile means little if tech, ops, HR, and finance are solving for different outcomes. Riyadh Air brought them into shared sprints. Governance was horizontal, not vertical. That’s how alignment was built, through doing, not dashboards.

5/ Train for fluency, not just skill. Riyadh Air didn’t limit AI education to data teams. They trained crew schedulers, guest service reps, and line managers. AI isn’t a department; it’s a literacy. Organizations that silo it will underuse it.

6/ Prioritize orchestration over experimentation. Most pilots fail because they sit outside operations. Riyadh Air didn’t run lab experiments; they built platforms. watsonx and OpenShift aren’t showcases; they’re how work gets done across functions.

7/ Modularity is risk insurance. Microservices weren’t a trend here; they were a requirement. Red Hat OpenShift gave teams the ability to change pieces without disrupting the whole. In high-change environments, architecture that can’t flex will break.

8/ Trust is human before it’s digital. Governance didn’t come from dashboards. It came from embedded leaders inside teams who clarified, enforced, and escalated. GRC tools help, but trust comes from people who carry both tech and business credibility.

9/ Explainability isn’t optional when real people are affected. Especially in aviation, models must be interpretable. watsonx came prebuilt with audit trails, escalation points, and override logic. That’s not extra; it’s minimum viable compliance.

10/ Measure outcomes by what your teams now do differently. Forget dashboards. Riyadh Air looked at whether people changed how they made decisions. Could they forecast independently? Handle queries faster? Spot issues without escalation? That’s the real measure of transformation, not just whether the system is live.

CIOs and CTOs need to stop looking at transformation as a phase. As Riyadh Air shows, it’s a system that matures by being used, not just deployed. The architecture matters. The team matters more.

Greyhound Research believes that scale only happens when technical design, executive alignment, and workforce readiness move together. It’s not a digital layer; it’s a deep reset.

Still Taxiing for Takeoff: Where This Partnership Heads Next

The Riyadh Air and IBM alliance isn’t built for a single milestone. It was never just about launch day. It’s designed to shift and grow across geographies, systems, and functions. As commercial operations ramp up in 2025, the real measure of success won’t be whether systems go live. It’ll depend on whether they hold up and keep improving under real-world pressure.

The next phase will be about refinement. AI models will train on live data from real flights and passengers. Autonomous workflows will need to adapt to everyday unpredictability, weather delays, crew changes, and maintenance issues. And the architecture will be tested for elasticity as the airline expands routes and partnerships.

Greyhound Fieldnotes suggest that the governance and orchestration framework put in place here is likely to extend beyond aviation. It could become a reference model for how national-scale digital infrastructure is built, especially in logistics, tourism, and public-sector mobility under Saudi Arabia’s broader Vision 2030.

Greyhound Research believes transformation isn’t complete at launch. It’s proven over time when systems don’t just run but evolve. The real test isn’t whether the first implementation succeeds. It’s whether the fiftieth holds up under change.

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