Are Cars Becoming Computers? Inside India’s Next Big Tech Boom
The global automotive industry is entering a structural technology super-cycle. Cars are no longer differentiated only by mechanical engineering; software, electronics, AI and data are becoming central to performance, safety and customer experience. This is creating a large opportunity for India’s automotive Engineering Research & Development (ER&D) companies, which combine traditional engineering with embedded software and digital product development.
1. From Hardware-Defined Cars to Software-Defined Vehicles
A software-defined vehicle (SDV) is effectively a computing platform on wheels whose functionality can be improved through software throughout its life. IBM’s Automotive 2035 survey finds that 74% of automotive executives expect vehicles in 2035 to be software-defined and AI-powered. They also expect digital and software-related revenue to rise from about 15% today to 33% by 2030 and 51% by 2035.
The shift is equally visible in R&D allocation. IBM respondents expect the share of R&D budgets dedicated to SDV and software-defined products to rise from roughly 21% today to 40% by 2030 and 58% by 2035, redirecting engineering spend toward software architecture, electronics, connectivity, cybersecurity and lifecycle services.
PwC’s “eascy” framework—electrified, autonomous, shared, connected and yearly updated—captures this broader shift. The key implication is that vehicle innovation cycles are becoming shorter and increasingly software-led, expanding the addressable market for engineering partners beyond component design into embedded software, middleware, cloud connectivity and continuous upgrades.
2. ADAS, Autonomy and the Rise of AI-Native Vehicles
Advanced driver-assistance systems (ADAS) are among the fastest-growing automotive technology areas. McKinsey estimates that the global ADAS/autonomous driving software and electronics market could increase from about $36 billion in 2025 to roughly $160 billion by 2035, implying around 16% annual growth. Software and domain control units are expected to account for the largest share of this value pool.
Full autonomy is likely to evolve gradually. IBM expects Level 2 and Level 3 systems to remain far more prevalent than Level 4 and Level 5 through 2035. Therefore, the ER&D opportunity does not depend on fully driverless cars; OEMs will spend for years on driver assistance, sensor fusion, functional safety and validation as automation progresses.
At the same time, the underlying architecture is changing. McKinsey describes a transition from traditional rule-based ADAS stacks toward AI-native end-to-end systems trained on large multimodal datasets. These systems demand significantly more compute, memory bandwidth, data infrastructure and simulation. The ADAS/AD processing semiconductor market itself is projected to rise from roughly $5.6 billion in 2025 to more than $46 billion by 2035.
For OEMs, this requires centralized computing, zonal architectures, standardized hardware-software interfaces, secure OTA updates, data governance and virtual validation. For ER&D providers, value increasingly lies in integrating mechanical systems, electronics, embedded software, cloud and AI at the vehicle level.
3. Electrification and Connected Mobility Expand the Engineering Stack
Electrification adds another layer of structural demand. The IEA estimates that electric car sales exceeded 20 million units globally in 2025, representing about one-quarter of new car sales, and could reach around 23 million in 2026. Under its exploratory scenarios, the global EV fleet could grow more than sixfold from 2025 levels to as many as 510 million vehicles by 2035, excluding electric two- and three-wheelers.
This creates engineering demand across battery management, motor controls, power electronics, thermal systems, charging and vehicle-to-grid integration. Deloitte also shows that customers value connected safety features and OTA upgrades while remaining concerned about privacy and cybersecurity. Vehicle value is therefore shifting toward a lifecycle of software updates, diagnostics and digital services.
4. Why India’s Auto ER&D Opportunity Is Expanding
India is well positioned because it already has a large engineering-services ecosystem and deep automotive talent. NASSCOM estimates the Indian-headquartered ER&D service-provider market at about $19–20 billion in FY2025, while the broader global engineering-services market could grow from roughly $82 billion in 2024 to around $135 billion by 2030.
NASSCOM-BCG also projects India’s share of global ER&D sourcing to rise from about 17% in 2023 to around 22% by FY2030. Automotive, software and semiconductors are expected to be among the largest contributors. Importantly, automotive software content can grow much faster than global vehicle volumes, allowing ER&D demand to expand even if overall auto unit growth remains moderate.
Outsourced work is also moving up the value chain. SDVs require deeper ownership across software architecture, embedded platforms, vehicle integration, AI, cybersecurity and virtual validation, favouring providers with genuine domain depth rather than generic software manpower.
India’s expanding Global Capability Centre ecosystem is both an advantage and a risk. OEMs are bringing more product R&D and engineering ownership into India, strengthening the talent ecosystem but also increasing insourcing. Service providers therefore need differentiated expertise, reusable platforms and system-level integration rather than labour-cost arbitrage.
5. Where the Future Revenue Pools Will Form
The most attractive automotive ER&D opportunities are likely to emerge in five areas: SDV architecture and middleware; ADAS, AI and virtual validation; EV powertrain, battery and charging software; connected vehicles, OTA diagnostics and cybersecurity; and digital twins, simulation and AI-assisted engineering.
The winners should move from selling engineer-hours toward owning larger pieces of the vehicle-development stack. Domain knowledge in functional safety, vehicle physics and real-time systems will remain critical, while reusable software and test frameworks can convert AI-led productivity gains into faster delivery and stronger margins.
Risks remain. OEM GCCs may insource some work, GenAI can reduce effort required for coding and testing, and customer concentration can create volatility when vehicle programs are delayed. Therefore, the key differentiator will be the ability to move up from execution-led outsourcing to architecture, platforms and strategic product-development ownership.
Conclusion
The automobile is becoming a software-and-electronics platform with mechanical systems at its core. SDVs, ADAS, AI-native architectures, electrification and connectivity are forcing OEMs to redirect R&D budgets toward areas blending physical engineering with digital capability.
This is the central opportunity for India’s automotive ER&D industry. India has the engineering scale, automotive ecosystem and software capabilities to gain share, but the opportunity will not be distributed evenly. Companies that combine deep automotive domain expertise with software, AI, system integration and reusable platforms should be best placed to capture the next decade of the auto technology transformation.
Sources Referenced
IBM Institute for Business Value; McKinsey & Company; International Energy Agency; Deloitte; KPMG; PwC; and NASSCOM / BCG ER&D studies referenced in the earlier sector draft.
Thank you for joining us in this special edition of the Financial Chronicle! We hope you're as excited about these changes as we are. Until next time, Happy investing!
