5 key technological skills for IT in the automotive industry
The automotive industry is undergoing rapid digital transformation, with software becoming a core driver of innovation, competitiveness, and customer value. As vehicles become increasingly connected and intelligent, organisations require new IT capabilities to accelerate innovation, strengthen resilience, and support long-term business growth.
Software-defined vehicle (SDV)
Software-Defined Vehicles (SDVs) are key as software increasingly controls functions like steering, braking, infotainment, connectivity, and Advanced Driver Assistance Systems (ADAS). Unlike traditional cars, SDVs get new features via Over-the-Air (OTA) updates after delivery, enhancing performance, cybersecurity, and services remotely (Cubic3, 2026). McKinsey forecasts the automotive software and electronics market to hit about US$519 billion by 2035 with 4.5% CAGR, outpacing the 1% vehicle market growth. Makers are moving to zonal and central computing architectures for scalable SDVs with better connectivity, generative AI, and digital services.
SDVs’ strategic importance is reflected in global investment. Kia delayed its first SDV launch from 2027 to 2028 but increased investment by 30% to 41.4 trillion won (US$28 billion) for 2026–2029 to strengthen software and AI capabilities (Reuters, 2026). Companies lacking expertise in embedded software, cloud computing, DevOps, cybersecurity, systems integration, and OTA infrastructure face slower development, higher costs, security risks, and fewer digital revenue opportunities.
Artificial intelligence (AI) and data analytics
Artificial Intelligence (AI) and data analytics are critical IT capabilities for automakers, supporting enterprise-wide decision-making, predictive analytics, and autonomous driving. Predictive analytics enables manufacturers to anticipate equipment failures, optimise operations, and reduce downtime, while AI is increasingly central to the development of autonomous driving systems. Research shows that predictive maintenance can reduce maintenance costs by 40% and downtime by 70% (AlZohbi & Alradhi, 2026).
The value of these technologies depends on an organisation’s ability to manage and analyse large volumes of data. Volkswagen, for example, uses more than 1,200 AI applications in production and plans to invest up to €1 billion by 2030 in AI for vehicle development, industry, and IT (Forbes Technology Council, 2026). Companies lacking expertise in machine learning, data analytics, AI implementation, and data governance may struggle to scale AI across the enterprise, resulting in fragmented applications, slower decision-making, and weaker returns from digital transformation.
Connected vehicle and cloud connectivity
The rise of connected vehicles makes skills in cloud computing, IoT, cybersecurity, and connectivity crucial. These vehicles share data with cloud platforms and infrastructure for services like navigation, maintenance, diagnostics, infotainment, and driver aid. The market will grow from US$115.8 billion in 2023 to US$501.8 billion by 2033, with 95% of new vehicles connected by 2030 (Gestão & Produção, 2026). Digital connectivity is key for future mobility.
Connected mobility requires secure cloud infrastructure, reliable OTA updates, and global connectivity (Cubic3, 2026). Manufacturers must integrate new digital ecosystems and partners (Gestão & Produção, 2026). Without expertise in cloud architecture, IoT, cybersecurity, network engineering, and systems integration, companies risk security issues, unreliable services, compliance problems, and reduced customer trust.
Electric mobility and energy management
Electric mobility is reshaping automotive IT expertise, with modern EVs increasingly dependent on software to optimise battery performance, powertrain efficiency, thermal management, and charging. This requires specialised expertise in embedded energy management software, powertrain algorithms, and smart charging infrastructure. AI-driven energy systems can reduce peak electricity demand by 34% and improve battery life, demonstrating the value of intelligent energy optimisation (AlZohbi & Alradhi, 2026).
Although EV demand has slowed in some markets, electrification investment remains a priority. Reuters reported that Kia reduced its EV sales targets while increasing investment in electrification, software, and AI, reflecting the industry’s growing integration of electric mobility and digital technologies (Reuters, 2026). Companies lacking expertise in battery management software, powertrain algorithms, embedded systems, energy optimisation, and smart charging risk higher operating costs, reduced vehicle efficiency, shorter battery life, and slower deployment of new electric mobility technologies.
Digital manufacturing and systems integration
As vehicles grow more software-driven, manufacturing must become smarter and data-driven. Modern factories produce vast data from sensors, robotics, and systems. Turning this into real-time insights needs expertise in systems integration, industrial data platforms, cloud and edge computing, and enterprise architecture. Manufacturers use private 5G, event streaming, and industrial foundation models to boost visibility, cut downtime, and speed decisions (Forbes Technology Council, 2026). These tools enable continuous data analysis, spotting quality and equipment issues earlier.
Advanced computing and software integration support connected vehicles, AI, and increasingly complex electronics (McKinsey & Company, 2026). Legacy systems create fragmented data, slower decisions, duplicated work, and higher costs. Developing expertise in digital manufacturing, enterprise architecture, cloud platforms, industrial AI, and systems integration improves resilience, efficiency, and future innovation.
Next steps
As the automotive industry becomes increasingly software-driven, organisations should invest in Software-Defined Vehicles, AI, cloud connectivity, electrification, and digital manufacturing while building the skills to support them. Strengthening these capabilities will improve innovation, cybersecurity, efficiency, and long-term competitiveness.
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