The industry is undergoing a shift of its own, as vehicles are increasingly becoming software-defined, with new developments and differentiation led by AI-powered digital experiences, rather than just mechanical engineering. Forrester’s mobility commentary has emphasized that many established automakers are still working through the organizational reality of becoming digital engineering companies (not just manufacturing leaders).
At the same time, the industry is entering a “prove it” phase for AI. Gartner recently predicted that by 2029, only ~5% of automakers will maintain strong AI investment growth, down from >95% today, as experimentation gives way to foundation-building, consolidation, and ROI scrutiny.
When it comes to AI in mobility, the signal is clear: AI isn’t optional, “random AI projects” won’t survive budget reviews. In this blog, we’ll address:
- Digital twins are no longer a buzzword
- Driver assistance: autonomous mobility
- Predictive maintenance
- AI-led cabin experiences and infotainment
- Optimizing supply chains
- AI trends in mobility for 2026 and beyond
Connecting product engineering, operations and CX into one feedback loop is where AI’s impact is clearly seen.
Engineering enhancements via digital twins
Digital twins are no longer a buzzword, but a backbone for empowering virtual validation, performance simulation, durability testing and swifter design phases prior to creating physical prototypes. MovateAI-powered digital twins create real-time simulations of vehicles, analyzing performance, durability, and efficiency against market conditions.
Client impact? Reduced late-stage defects and development times through swifter program cycles; optimized quality via real-time monitoring; and enhanced production/ cost control across vehicle variants.
Driver assistance with autonomous mobility: sensor fusion, real-time decisioning, safety
Today’s Advanced Driver Assistance Systems (ADAS) are AI-led and entail perception, prediction, planning and continual learning; by continuously processing data from sensors, cameras, LIDAR, and radar.
MovateAI ensures precise navigation, seamless traffic adaptation, and superior obstacle detection: bringing safety, trust and confidence to autonomous mobility.
Client impact? Enhanced safety performance, improved feature reliability, and a clearer path to assist, hands-free, and higher autonomy roadmaps.
Predictive maintenance becomes “self-healing” operations
Predictive maintenance is shifting from alerts to orchestration, which includes: diagnosing early, recommending fixes, scheduling service, and reducing breakdowns.
Client impact? Slashed costs of warranty; increased uptime; boosted CSATs; and enhanced efficiency in dealer/service networks.
MovateAI analyzes real-time vehicle performance, detects early signs of wear and tear, and proactively recommends and schedules service and maintenance appointments.
AI-driven in-cabin experiences and personalized infotainment
Through in-cabin personalization and AI-driven infotainment, connected vehicles offer adaptive, driver- and user-focused experiences via cloud AI, biometrics, and sensors. Features include AI-led seating adjustments, user profile adaptability via voice recognition and biometrics, climate control, and mood lighting.
Personalized interactions via AR visualizations (transparent hood views) and emotionally intelligent avatars. Infotainment aspects include natural language voice agents offering multilingual commands with gesture controls for navigation and media controls; AR HUDs (Head-up Displays) for displaying real-time data, such as hazards, routes, and speed limits, with driver monitoring for fatigue indicators; child detection via multi-sensor fusion, and analyzing media via predictive personalization for media suggestions and maintenance.
MovateAI transforms infotainment by integrating predictive conversational assistants, real-time navigation, and personalized en route experience recommendations.
Client impact? Unique top-notch experiences, deep integration of digital services that power identity management with improved customer retention and loyalty through ‘vehicle-as-a-platform’ engagement strategies.
AI across the logistics/supply chain
Automotive supply chains are global, complex and prone to disruptions; every delay impacts production and delivery. MovateAI optimizes this ecosystem by predicting demand, enhancing fleet efficiency, and minimizing disruptions before they occur. Services include: Demand forecasting & inventory optimization, route optimization & logistics planning, supplier risk assessment.
Client impact? Improved ‘On-Time, In Full’ performance, slashed inventory pressure, and agility in response to disruptions (ports, chips, geopolitics).
2026 trends in automotive
Here are the trends most likely to influence budgets, programs, and partner selection in 2026.
“AI foundations first” (data readiness, model governance, measurable ROI)
Gartner’s warning about an AI investment slowdown is, in fact, a call for operational maturity, encompassing data pipelines, evaluation, safety, security, and scalable delivery.
What clients will demand: business cases, KPI baselines, and production-grade AI operations (going beyond just pilot projects.).
Central compute + zonal architectures power the SDVs
Centralized compute stacks and zonal networks are being increasingly used to build SDVs (Software-Defined Vehicles); IDTechEx forecasts approximately USD 755 billion in hardware revenue by 2029, linked to these next-generation architectures.
What clients will demand – Platform engineering, OTA (Over the Air) updates/readiness, validation automation, and lifecycle cost reduction.
GenAI for automotive software development scales when paired with disciplined QE
GenAI is increasingly used to accelerate software development (from requirements to code, test generation, and defect triage), but it must be tied to strong engineering governance. McKinsey has highlighted the role of GenAI in transforming automotive software development.
What clients will demand? AI-guided engineering, autonomous QE with traceability and auditability.
Automotive cybersecurity
The cybersecurity of connected vehicles becomes indispensable for compliance and brand protection as they expand the attack surface, and regulators are mandating a structured approach. Countering rising cyberattacks is possible through layered defenses, such as secure-by-design architecture, real-time monitoring, and continuous updates.
- ISO/SAE 21434:2021 defines cybersecurity engineering requirements across the whole vehicle lifecycle; and,
- UNECE WP.29 regulations (notably UN R155 for CSMS and UN R156 for software updates) have been in force since January 2021, and continue to evolve in a consolidated legal text.
What clients will demand? Continual monitoring and compliance, wireless or OTA (Over the Air) security, supply chain security, SBOM (Software Bill of Materials), and secure-by-design engineering.
Operationalizing AI for driving customer value and trust: Leaders integrating AI across end-to-end vehicle experience design, automotive security, and platform-led engineering for variants and models will lead the pack in 2026 and beyond. The opportunity lies in crafting innovative mobility solutions where every mile, interaction, and update strengthens the product and customer bond.
References
- Movate automotive offerings and solutions.
- Forrester. “Predictions 2025: Smart Manufacturing And Mobility Firms Adapt.”
- Gartner. “Gartner Predicts Only 5% of Automakers Will Keep Investing Heavily in Artificial Intelligence by 2029.”
- Gartnerr. “Gartner Forecasts Global Information Security Spending to Grow 15% in 2025.”
- ISO “ISO/SAE 21434:2021 — Road vehicles — Cybersecurity engineering.”
- McKinsey & Company. “From Engines to Algorithms: Gen AI in Automotive Software Development.”
- Reuters. “Only a Few Automakers to Keep Up AI Push, Gartner Says.”
- EUR-Lex UNECE / EU. “UN Regulation No. 155… Approval of Vehicles with Regards to Cyber Security and Cyber Security Management System.”
- Rivian unveils custom AI chip and next level of automated driving – electrive.com
- Applus Laboratories. “UNECE WP.29 R155/R156: New Cybersecurity Regulations for Vehicles.” January 2021 (noted). Accessed December 15, 2025.
- IDTechEx. Software-Defined Vehicles, Connected Cars, and AI in Cars 2026–2036: Markets, Trends, and Forecasts. Cambridge, UK: IDTechEx, 2024. Accessed December 18, 2025.