Over half of automotive revenue will come from technology-driven services by 2035, not from making cars. That is not a prediction. It is what the industry's own executives are planning for, according to IBM's Automotive State of the Industry report. Software-defined vehicles, AI-powered services, and digital subscriptions are rewriting what it means to compete. C-suite executives who still measure success by units shipped are using the wrong scorecard. The ones moving fastest have already figured out that the vehicle is now the platform, and the business model is what needs to be built around it.
74%
Of automotive executives say vehicles will be software-defined and AI-powered by 2035, per IBM Institute for Business Value.
82%
Of new cars are expected to be electrified in some form by 2035, including full EVs and hybrids.
68%
Of automotive CEOs say the productivity gains from automation are so significant they must accept substantial risk to stay competitive.
72%
Of automotive CEOs say competitive advantage will depend on who has the most advanced generative AI, not who builds the best engine.
Software-defined vehicles demand a software-defined organization
48% of automotive OEMs and suppliers say separating software from hardware layers is one of their biggest SDV challenges. But the technical problem is often not the hardest one. 74% of executives say their mechanical-driven culture is deeply entrenched and hard to shift. C-suite executives cannot buy their way to a software-first business. It requires changing how teams are structured, how decisions get made, and what gets measured. The organizations moving fastest have treated this as a leadership problem first and a technology problem second.
Digital revenue models are being tested but clear winners have not emerged
By 2028, automotive executives see monetization potential in voice and virtual assistants (77%), vehicle subscriptions (70%), and fleet management (69%). Customers are expected to pay meaningful monthly fees for autonomous driving and in-car entertainment by 2035. But here's the problem: 62% of executives say designing viable business models for these services is their biggest hurdle. The infrastructure for direct-to-consumer relationships, OTA delivery, and recurring billing is still being built. C-suite executives who start building that infrastructure now will have a structural advantage over those who wait.
Supply chain resilience is now an AI problem as much as a logistics one
Global trade tensions rank as the second biggest challenge for supply chain leaders in 2025. AI-powered supply chain and logistics management is projected to deliver a 36% ROI by 2027. But only 24% of organizations report high maturity in this area. The gap between what AI can do for supply chain visibility and scenario planning and what most automotive companies are actually doing is significant. C-suite executives with the right data platforms and agentic AI in their supply chains will respond to disruption faster than those still working from spreadsheets.
Security is a brand attribute now, not just a compliance requirement
86% of automotive leaders agree that security, assurance, and trust now directly differentiate their brand. 53% of consumers say they prefer brands with superior privacy and cybersecurity in autonomous and shared mobility. But only 32% of organizations are implementing security by design across their products and operations. As vehicles become connected endpoints with V2X communication, OTA updates, and edge computing, the attack surface grows with every new feature. C-suite executives who treat security as a product investment rather than a compliance checkbox are building long-term brand trust.
At Marchcroft
Innovating Today,
Shaping Tomorrow
74%
Software-Defined Vehicles
Of automotive executives say vehicles will be software-defined and AI-powered by 2035. The shift from mechanical to digital is the defining challenge for current C-suite leadership.
82%
Electrification Mix
Eighty-two percent of new cars are expected to be electrified by 2035. Managing this transition requires a fundamental overhaul of supply chains, manufacturing, and aftersales services.
72%
GenAI Advantage
Seventy-two percent of automotive CEOs say competitive advantage will depend on who has the most advanced generative AI, reflecting a pivot from physical engineering to digital intelligence.
01. Map where your revenue will actually come from in 2035
Automotive executives expect R&D spend on software-defined programs to increase by 47% by 2035. Software's share of total vehicle cost will grow from 16% today to 24%. If your five-year plan does not account for that shift in where value gets created and captured, it is already out of date. C-suite executives need to be specific about which parts of the digital mobility value chain they will lead, and where they will partner. Vehicle hardware, user experience platforms, applications, and data are all contestable. You cannot win all of them.
02. Build the operational foundation for AI before you need it
Automotive organizations expect 30% of their workforce to be AI-enabled by 2026, up from 8% in 2024. 70% say agentic AI is critical to their future. But most have not yet built the data infrastructure, hybrid cloud architecture, and governance frameworks that make AI trustworthy at scale. Only 23% of automotive organizations have established clear guidelines for AI in automated decision-making. The C-suite executives who do this foundational work now will deploy AI faster and more reliably than those who try to shortcut it.
03. Treat aftersales as a primary revenue channel, not a support function
Most recurring digital revenue in automotive happens after the vehicle leaves the lot. Fleet customers need clear ROI. Individual drivers need solutions to real problems. EVs already carry 50% lower scheduled maintenance costs than ICE vehicles, which puts pressure on traditional aftersales revenue. The organizations that build AI-powered aftersales capabilities, bundled service offerings, and agentic customer engagement tools are the ones that turn a one-time sale into a decade-long revenue stream.
Honda needed a way to transfer deep engineering knowledge from senior staff to younger engineers, starting with collision-safety vehicle development. Manual documentation was slow and inefficient.
- 67% reduction in documentation modeling time using generative AI
- 30% to 50% savings in development and planning work
- AI-powered knowledge extraction now runs across Honda's development documentation
IBM applied large multimodal and language models to Honda's knowledge modeling challenge, with a watsonx.ai pilot validating the approach before full rollout.
"IBM's innovative solutions and the platform that securely uses our vast development information are contributing to our dream of delivering more value to our customers." - Senior Chief Engineer, BEV Development Division, Honda
Q: How do we build recurring digital revenue when the business model is still unclear?
Q:
Q: When does quantum computing actually matter for us?
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