Software-Defined Vehicles Enter the Era of AI-Driven Value Creation

Key Terms

software-defined vehicle technical

A software-defined vehicle is a car whose capabilities, performance and user features are driven primarily by software running on its electronic systems rather than fixed mechanical parts, similar to how a smartphone gains new features through apps and updates. For investors this matters because revenue and value can shift from one-time hardware sales to ongoing software services, faster feature upgrades and broader aftermarket opportunities, while introducing dependencies on software development, cybersecurity and regulatory compliance.

adas technical

Advanced Driver Assistance Systems (ADAS) are electronic systems in vehicles that assist the driver with safety tasks. Examples include automatic emergency braking, lane keeping assist, and adaptive cruise control. These systems use sensors and cameras to improve vehicle safety.

oems technical

OEMs, or Original Equipment Manufacturers, are companies that produce the main components or products that other companies use to build finished goods. For investors, OEMs are important because their performance can influence the supply chain, manufacturing costs, and overall market trends in industries like technology, automotive, and electronics. Their success often reflects broader economic health and consumer demand.

predictive maintenance technical

Predictive maintenance involves using data and technology to monitor equipment or machinery in real time, identifying potential problems before they cause failures or breakdowns. By predicting when maintenance is needed, it helps prevent costly repairs and downtime. For investors, it highlights how companies can reduce expenses, improve efficiency, and maintain reliable operations, which can positively impact financial performance.

containerized applications technical

Containerized applications are software programs packaged with everything they need to run—code, settings and libraries—so they behave the same on any computer or cloud, like goods packed in standardized shipping containers that fit on any truck or ship. For investors, this matters because containerization can cut deployment time and hosting costs, improve reliability and make it easier for companies to scale and move services between providers, affecting margins and growth potential.

cloud-native software architectures technical

Software built for cloud-native architectures is designed to run and scale inside cloud computing environments using many small, independent parts that can be updated, restarted or expanded without taking the whole system offline. For investors, this matters because cloud-native systems usually let companies launch features faster, handle growth more cheaply and recover from problems more quickly—similar to replacing or upgrading individual parts of a car instead of rebuilding the entire vehicle.

automated driving technical

Automated driving is technology that lets a vehicle control steering, speed and braking and react to road conditions with little or no human input, using sensors, cameras, software and mapping data. For investors it matters because it can reshape costs, safety, insurance, regulation and new revenue models—think of cars operating like an autopilot or a robot taxi, which can change demand, profit margins and which companies win in the market.

Survey: Smart diagnostics and predictive maintenance emerging as top use case for AI in SDV

SUNNYVALE, Calif.--(BUSINESS WIRE)-- For years, the software-defined vehicle (SDV) promised to overturn a century-old truth: that cars depreciate from the moment they leave the factory. Today, that promise is becoming an operational reality.

According to The 2026 SDV Reality Check: The Great Recalibration, a report released today based on a global study conducted by Omdia and sponsored by Sonatus, the automotive industry has moved past the hype to tackle the complexities of real-world operationalization. The report reveals a significant strategic shift: rather than selling vehicle data to third parties, automakers are focusing on internal data utilization to create value-generating opportunities. From ADAS and diagnostics to predictive maintenance and new services, OEMs are using their data as the building blocks of intelligent, continuously improving vehicles.

Fast facts

• Smart Diagnostics and Predictive Maintenance are the “Killer Apps” for AI: Smart diagnostics and predictive maintenance have emerged as the top priorities for AI, cited by 34% of global respondents, underscoring the industry’s focus on AI applications that deliver measurable ROI.
• The Infrastructure Shift to Containerization: As automakers work to overcome legacy integration hurdles, respondents reporting already-deployed containerized applications increased 10% year-over-year between the 2025 and 2026 surveys; the only technology to see double-digit gains. This confirms the industry is moving toward flexible, cloud-native software architectures.
• The Data Monetization Pivot: The appeal of selling vehicle data to third parties is declining as OEMs recognize greater value in internal data utilization. Rather than pursuing direct revenue through data sales, automakers are adopting a more mature strategy: channeling data into capability-building applications such as ADAS improvements (41%), product development (38%), and diagnostics. This pivot signals a fundamental shift from external monetization to creating value within their own vehicle ecosystems.

“The data shows a decisive shift in how automakers are creating value with AI,” said Maité Bezerra, senior principal analyst at Omdia. “Predictive maintenance delivers vehicle-centric value that smartphones cannot replicate. It generates tangible value through an improved driving experience, enhanced reliability, and a better overall ownership experience, ultimately driving customer loyalty. OEMs are enhancing data with AI to make vehicles better over time.”

Regional Breakdown

The findings reveal sharp regional differences in how automakers plan to drive customer loyalty and after-sales revenue over the coming years:

• North America’s Service and Content Focus: When evaluating which features drive the most customer loyalty and after-sales revenue, North American automakers prioritize service and recurring revenue models. The market is anchored by predictive maintenance (48%), followed by a tie between automated driving and in-vehicle entertainment (41% each), with entertainment seeing the region’s largest year-over-year surge at +11%.
• Europe’s Vision-Execution Gap: As a whole, Europe is strongly aligned on services, tying North America in ranking predictive maintenance as the top feature for driving customer loyalty and revenue (48%). A deeper look, however, reveals a critical execution gap in the region’s largest market. German automakers rank predictive maintenance as a top revenue driver (47%), yet report the lowest AI deployment for it globally (just 18%), signaling the country remains in the planning phase while global competitors scale.
• Japan’s Quality-First Strategy: Japanese automakers are betting heavily on functional performance and quality to drive customer loyalty. Automated driving is their undisputed top priority (50%, a 10% increase from 2025), indicating growing confidence in autonomy as a safety differentiator. Notably, Japan also leads the world in prioritizing ride customization (37%), reflecting a unique cultural emphasis on driving dynamics and comfort over aesthetic personalization.
• China’s Dramatic Pivot: As the most advanced SDV market by deployment, China is experiencing a massive shift in how it drives customer loyalty. Traditional vehicle data monetization dropped 25% from 2025, as Chinese OEMs made aggressive pivots toward automated driving (54%) and enhanced personalization (53%) to create visible, experience-driven differentiation.

“What stands out in this year’s results is how quickly operational AI is maturing,” said John Heinlein, Ph.D, chief marketing officer, of Sonatus. “Automakers see value in strengthening diagnostics, reducing costs, and delivering a better service experience. Predictive maintenance is emerging as a strong proof point, supported by the industry’s move toward more flexible, software-driven architectures.”

The Omdia 2026 Software-Defined Vehicle (SDV) Survey analyzed the responses of 559 automotive professionals across seven major markets (U.S., Canada, U.K., Germany, France, Japan, and China) conducted in March-April 2026. To further explore the findings, including a deeper dive into regional execution gaps and the rise of operational AI, download the report at https://www.sonatus.com/resources/software-defined-vehicle-survey-2026-ebook/

About Omdia

Omdia, part of Informa TechTarget, Inc. d/b/a Informa TechTarget (Nasdaq: TTGT), is a technology research and advisory group. Our deep knowledge of tech markets grounded in real conversations with industry leaders and hundreds of thousands of data points, make our market intelligence our clients’ strategic advantage. From R&D to ROI, we identify the greatest opportunities and move the industry forward.

About Sonatus

Sonatus is a leading technology provider for intelligence-driven software-defined vehicles that are scalable and upgradable. Our AI solutions and software-defined technologies empower OEMs and suppliers to reduce costs, accelerate time-to-market, and deliver uncompromised quality. Founded in 2018, Sonatus is privately held, backed by leading investors spanning the automotive, semiconductor, and venture capital sectors, and its technology is in more than 7 million production vehicles from leading global automakers. Sonatus is headquartered in Sunnyvale, Calif. (Silicon Valley), with regional headquarters in Dublin, and offices in Bangalore, Detroit, Frankfurt, Kraków, Paris, Pune, Seoul, Shanghai, Taipei, and Tokyo. For more information, visit www.sonatus.com.

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MEDIA CONTACTS

Sonatus
Leslie Clavin
Head of Public Relations
leslie.clavin@sonatus.com

Omdia
Fasiha Khan
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Eric Thoo
eric.thoo@omdia.com

Source: Sonatus