Overview
Saudi Arabia’s startup flag carrier Riyadh Air has positioned itself as what IBM and the airline call the world’s first “AI-native” airline—an enterprise designed from day one around AI-driven, cloud-based systems rather than retrofitted legacy IT. Launched in March 2023 as part of the Kingdom’s Vision 2030 strategy, Riyadh Air has ordered large fleets from Boeing and Airbus and aims to connect over 100 destinations by 2030, serving millions of travelers through Riyadh’s planned mega-hub.
From early 2024 onward, Riyadh Air and IBM have progressively built an AI-centered operating stack on IBM’s watsonx platform, integrating 59 workstreams and more than 60 technology partners to support employee workflows, crew enablement, customer service, and enterprise performance management. With initial proving flights underway and full commercial service expected in early 2026, the Dec. 8, 2025 announcement at IBM Think Riyadh 2025 marks a key inflection point—not only for Saudi aviation ambitions, but for the broader question of whether agentic AI can safely and profitably orchestrate core airline operations in a heavily regulated, safety-critical industry.
Key Indicators
People Involved
Organizations Involved
Riyadh Air is a full-service, digitally led airline owned by Saudi Arabia’s Public Investment Fund (PIF). Announced in March 2023, it is designed to support Vision 2030 by turning Riyadh into a global aviation hub and connecting over 100 destinations by 2030.
IBM is a global technology and consulting company focusing on hybrid cloud, AI, and enterprise services. Through IBM Consulting and its watsonx AI platform, it is the principal architect of Riyadh Air’s AI-native operating model.
PIF is Saudi Arabia’s sovereign wealth fund, tasked with deploying capital domestically and abroad to support Vision 2030. It fully owns Riyadh Air and is a major investor across the Kingdom’s aviation ecosystem.
GACA is Saudi Arabia’s civil aviation regulator, responsible for safety oversight, economic licensing, and implementation of the Saudi Aviation Strategy that underpins Riyadh Air’s growth plans.
Sabre is a global travel technology provider supplying distribution, retailing, and revenue optimization tools to airlines. With Riyadh Air, it is co-developing SabreMosaic, an AI-native, offer- and order-based retailing platform including Continuous Revenue Optimizer.
Timeline
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IBM and Riyadh Air Unveil ‘World’s First AI-Native Airline’
Public StatementAt IBM Think Riyadh 2025, IBM and Riyadh Air announce that the airline is operating as the world’s first AI-native airline, with AI agents embedded in employee digital workplaces, crew enablement apps, customer-care bots, and enterprise performance management systems built on IBM’s watsonx platform and a 60+ partner ecosystem.
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Sabre Launches AI-Native Continuous Revenue Optimizer with Riyadh Air
Technology LaunchSabre unveils its SabreMosaic Continuous Revenue Optimizer (CRO), an AI-native, classless revenue engine that provides continuous pricing recommendations. The solution is built in partnership with Riyadh Air, further embedding AI into the airline’s commercial operations.
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Riyadh Air Sets Inaugural Proving Flight to London
Operational MilestoneRiyadh Air announces it will commence its inaugural flight to London Heathrow on October 26, 2025, using a leased Boeing 787‑9 as a proving flight with limited access before opening to the general public.
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Riyadh Air Orders 25 Airbus A350-1000s
Commercial DealAt the Paris Air Show, Riyadh Air confirms an order for 25 Airbus A350‑1000 aircraft, supplementing its Boeing 787 order and underscoring plans for a large, modern long-haul fleet.
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GACA Approves Riyadh Air to Commence Operations
RegulatoryRiyadh Air receives regulatory approval from Saudi Arabia’s GACA to commence flight operations, a prerequisite for proving flights and the later commercial launch.
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IBM and Riyadh Air Announce AI-Driven Enterprise Agreement
Technology PartnershipIBM and Riyadh Air unveil an agreement to build an AI-driven enterprise that uses IBM’s watsonx portfolio as the foundation for mission-critical functions and agentic AI-based automation in customer interactions and internal workflows, with IBM Consulting as lead systems integrator.
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Riyadh Air Selects SabreMosaic AI Platform
Technology PartnershipRiyadh Air signs a strategic agreement with Sabre to deploy its SabreMosaic Offer Optimization technology and AI-powered tools such as Air Price IQ, Ancillary IQ, Bundle IQ, and Upgrade IQ, aiming to become the first airline to operate entirely on offer- and order-based retailing from day one.
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IBM and Riyadh Air Highlight Collaboration at LEAP 2024
PartnershipAt the LEAP 2024 technology conference in Riyadh, IBM and Riyadh Air announce next steps in their collaboration to build next-generation, channel-fluid guest and traveler interactions, positioning the airline as a digital-native carrier scheduled to commence operations in early 2025.
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Riyadh Air Secures Economic License from GACA
RegulatorySaudi regulator GACA grants Riyadh Air its Passenger Air Transport Economic License, enabling the airline to move toward operational readiness.
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Riyadh Air Orders Up to 72 Boeing 787-9s
Commercial DealRiyadh Air announces an agreement to purchase 39 Boeing 787‑9 Dreamliners with options for 33 more, contributing to a combined Saudi order of up to 121 Dreamliners and signaling the scale of its long-haul ambitions.
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Saudi Crown Prince Announces Creation of Riyadh Air
Strategic AnnouncementCrown Prince Mohammed bin Salman formally announces the establishment of Riyadh Air, a new national carrier fully owned by the Public Investment Fund, as part of Vision 2030’s push to make Saudi Arabia a global aviation and logistics hub.
Scenarios
AI-Native Blueprint Proves Out and Becomes the New Industry Standard
Discussed by: IBM, Sabre, aviation technology vendors, and strategy consultancies covering airline digital transformation
In this scenario, Riyadh Air’s AI-native architecture delivers measurable gains in reliability, customer satisfaction, and unit costs without major safety or reputational incidents. IBM and Sabre publish case studies showing double-digit productivity improvements and 2–4% revenue uplift from continuous pricing, dynamic offers, and integrated performance management. Regulators accept that agentic AI can manage many back-office and real-time operational decisions under appropriate governance. Established carriers begin adopting similar patterns—moving core operations, crew management, and retailing to AI-native platforms—using Riyadh Air as a benchmark. Saudi Arabia touts the airline as evidence that Vision 2030 is producing globally competitive, tech-forward national champions, attracting further investment and partnerships.
Partial Success: Hybrid Human–AI Model Emerges After Growing Pains
Discussed by: Aviation analysts, safety experts, and specialized trade media skeptical of full automation
Here, Riyadh Air’s AI systems deliver benefits but also face friction—such as employee pushback, integration challenges with partners and legacy airport systems, and periods where AI recommendations conflict with operational judgment. Similar patterns have been seen at European carriers that introduced AI tools for operations and pricing but still rely heavily on human oversight. Regulators may require more explicit human-in-the-loop controls for certain use cases (e.g., disruption management, crew planning), slowing full automation. Riyadh Air retains its AI-native branding but settles into a pragmatic hybrid model where AI agents support rather than replace many decision-makers. The project remains a success, but the step-change vs. best-in-class legacy carriers narrows.
Safety or Service Incident Triggers AI Backlash and Regulatory Clampdown
Discussed by: Risk-focused commentators, some labor groups, and cautious regulators observing AI deployments across airlines and airports
In a more adverse scenario, an AI-enabled system at Riyadh Air—or at another early adopter airline—contributes to a major disruption, safety incident, or serious customer-service failure. Even if human errors are also involved, media and regulators focus on the role of opaque AI decision-making. Given aviation’s low risk tolerance, authorities could respond with strict limitations on agentic AI in operations control, crew scheduling, or customer handling until new standards and certification regimes are in place. This would echo broader concerns seen in other industries where AI deployments led to job cuts or controversial decisions, prompting political and regulatory scrutiny. Riyadh Air might then have to roll back or heavily modify certain AI-driven workflows, increasing costs and diminishing the distinctiveness of its AI-native claim.
Geopolitical or Macroeconomic Shocks Slow Vision 2030 and Strand Investments
Discussed by: Macro and political risk analysts following Gulf aviation strategies
This scenario assumes that broader shocks—regional tensions, global recessions, oil price swings, or tourism setbacks—cause Saudi Arabia to scale back or delay aviation growth targets of 330 million passengers and 250+ destinations by 2030. Riyadh Air’s growth plan and AI-native investments depend on rapid traffic expansion and high aircraft utilization. If passenger volumes or tourism flows undershoot forecasts, the airline could face overcapacity and underutilized digital infrastructure. IBM and Sabre would still reuse the technology stack with other clients, but Riyadh Air might become a slower-growing, regionally focused carrier rather than the global disruptor envisioned.
Labor and Skills Tensions Reshape AI Deployment Pace
Discussed by: Aviation unions, workforce researchers, and observers of AI-led restructuring at European carriers
As airlines like Lufthansa use AI and digitalization to cut thousands of administrative jobs while modernizing operations, workforce tensions grow over displacement and job quality. Riyadh Air starts with a smaller legacy workforce, but as it expands and doubles its staff, employees may resist further automation if they see AI-native systems as a threat to career paths. Saudi labor markets and social expectations could influence how quickly the airline replaces or redefines roles with AI agents. If labor concerns intensify globally, regulators may tie approvals for certain AI deployments to worker consultation, training, or job guarantees, affecting how far Riyadh Air and its peers can push full automation.
Historical Context
KLM–BCG Digital Airline Operations Program
2018–2024What Happened
Starting in 2018, KLM Royal Dutch Airlines partnered with Boston Consulting Group (BCG) to develop a suite of AI-based tools for integrated airline operations planning and control. These tools applied machine learning and optimization to fleet, crew, ground, and hub operations, reducing delays and improving efficiency. The partnership was extended in 2021 and again in 2024 as other airlines adopted the platform.
Outcome
Short term: KLM and partner airlines reported better on-time performance, more resilient operations during disruptions, and higher utilization, demonstrating that AI-enhanced operations can work within legacy carriers.
Long term: The KLM–BCG work helped normalize AI-assisted operations control, but most deployments remained layered on top of legacy architectures rather than replacing them, illustrating the difficulty of fully replatforming established airlines.
Why It's Relevant
KLM’s experience shows that AI can drive measurable performance gains even in complex, legacy environments, but also that deep transformation is slow and incremental. Riyadh Air’s claim to be AI-native from the outset is, in part, a bet that starting from a greenfield avoids the integration and change-management burdens that constrained KLM and its peers.
Air France–KLM Generative AI Factory with Accenture and Google Cloud
2024–2025What Happened
In 2025, Air France–KLM, Accenture, and Google Cloud launched a "generative AI factory"—a cloud-based framework and set of tools to scale gen AI, agentic AI, and machine-learning models across the airline group. The initiative, built on a modernized digital core, supports use cases from maintenance diagnostics to customer service assistants and aims to accelerate AI development cycles by more than 35%.
Outcome
Short term: The AI factory enabled Air France–KLM to roll out internal gen AI assistants and RPA-to-agentic AI upgrades, saving hundreds of thousands of hours of manual work and strengthening the business case for AI at scale.
Long term: Over time, the project is expected to embed AI capabilities across many functions, but within an existing multi-brand airline group structure. It illustrates a parallel path to Riyadh Air: using a common AI platform to retrofit a large carrier rather than building one from scratch around AI.
Why It's Relevant
Air France–KLM’s gen AI factory shows how incumbent airline groups are moving toward AI platforms similar in spirit to Riyadh Air’s watsonx-based approach. The comparison highlights the strategic question: is it more effective to retrofit a fleet of legacy processes and systems, or, as Riyadh Air is attempting, to design the airline itself as an AI-native enterprise from day one?
Lufthansa Group and Eurowings: AI-Driven Efficiency and Job Cuts
2023–2030 (planned)What Happened
Lufthansa Systems and Eurowings deployed an AI-powered operations control assistant (NetLine/Ops++ aiOCC) to help controllers anticipate disruptions and manage daily operations, while the broader Lufthansa Group announced plans in 2025 to cut about 4,000 administrative jobs by 2030 through AI and digitalization. AI is also used for dynamic pricing and airport turnaround monitoring, contributing to a wider European push to use AI for efficiency and profitability gains.
Outcome
Short term: AI tools improved operations insight and commercial agility but triggered debates about workforce impacts as Lufthansa tied AI and automation directly to job reductions.
Long term: By 2030, Lufthansa expects significantly higher profitability and a more integrated group structure, but with a leaner administrative workforce. The case has become emblematic of how AI in aviation can reshape labor relations and cost structures as much as technology stacks.
Why It's Relevant
Lufthansa and Eurowings illustrate a path where AI is layered onto legacy airlines primarily as an efficiency and cost-cutting tool. Riyadh Air’s AI-native narrative is more focused on reimagining experiences and architectures, but as its workforce grows, similar labor and cost pressures may arise. The European experience offers clues about how regulators, unions, and the public may react if AI-native airlines begin to use automation aggressively to reshape jobs.