In a recent conversation with CIO&Leader, Sandeep Kumar Jain, Managing Director of CDK Global India, offered insights on how automotive technology is evolving toward a more intelligent and connected future.
Jain, a seasoned technology leader with a proven track record in building and scaling complex software products, has extensive experience managing large global teams, fostering high-performance cultures, and steering strategic initiatives. Edited excerpts from the interview follow.
MD, CDK Global
CIO&Leader: What key advancements or milestones in automotive technology do you foresee making the biggest impact in 2025?
Sandeep Kumar Jain: In 2025, automotive technology will continue its rapid transformation, driven by connected, data-driven vehicles and AI-powered insights. Cars are evolving beyond mere transportation tools, becoming intelligent systems that enhance safety, efficiency, and user experience. Predictive maintenance, real-time diagnostics, and over-the-air (OTA) software updates will minimize unplanned repairs, keeping vehicles on the road longer. Vehicle-to-everything (V2X) communication will further revolutionize mobility, allowing cars to interact with infrastructure, other vehicles, and cloud-based systems, enhancing road safety and traffic management.
As automotive technology advances, automotive retail technology must evolve alongside it to meet changing consumer expectations. Predictive analytics in inventory management will help dealers stock the right vehicles, optimize pricing strategies, and reduce carrying costs. AI-powered merchandising tools will generate instant vehicle descriptions, high-quality images, and automated valuations, accelerating sales cycles.
The retail experience itself is becoming more immersive and digital-first. Video walkthroughs and virtual showrooms will provide customers with interactive, personalized buying and vehicle servicing journeys, bridging the gap between online research and in-store visits. Service scheduling is also undergoing a transformation, with AI-driven automation ensuring seamless appointment bookings, personalized service reminders, and proactive customer engagement.
Beyond sales and service, integrated payment solutions and seamless financing workflows will reduce friction in transactions, making car buying and ownership more convenient than ever. In 2025, the industry isn’t just selling cars—it’s delivering smarter, faster, and more connected automotive experiences, where both vehicles and dealerships leverage technology to drive the future forward.
CIO&Leader: How are automotive players adopting emerging tech—such as AI—to streamline production, enhance in-vehicle experiences, or optimize dealership operations, and how is this influencing strategic objectives?
Sandeep Kumar Jain: Automotive players are increasingly using AI-powered insights and Hybrid Intelligence to enhance production, optimize in-vehicle experience, and streamline dealership operations. Advanced insights based on data along with predictive AI to ensure a smooth consumer experience. Real-time, tailored, conversational text and email replies are provided by AI-powered virtual chatbots for dealers. These chatbots answer all queries and set up appointments with ease in more than 50 languages, understanding the goals and preferences of their clients. These chatbots provide chatGPT like experience where users can ask basic questions and get answers.
Connected cars are further enhancing in-vehicle experiences by integrating predictive maintenance alerts, AI-driven virtual assistants, and intuitive voice-based controls. Consumers expect their vehicles to function like smart devices, and automotive brands are meeting this expectation by embedding conversational AI, seamless infotainment integration, and real-time connectivity.
CIO&Leader: With the rapid rise of connected and data-driven solutions, what major shifts do you anticipate in dealership transformation and digital retail by 2025?
Sandeep Kumar Jain: In 2025, the transformation of the dealership will be defined with hyper-personalization, automation, and predictive intelligence, ensuring seamless, data-driven retail journeys for customers.
As I’ve said before, one of the biggest shifts will introduce real-time analytics into dealership workflows. With data driven solutions, sales efficiency will rise, all while the customer-centric inventory strategy unfolds. One of the most transformative applications is to anticipate buying patterns and market demand. AI models analyze vast datasets such as historical sales trends, economic indicators, and regional preferences to forecast which vehicle models will see the highest demand. This helps reduce inventory shortages, and long waiting periods and guarantees that the right vehicles are available at dealerships in the right quantities.
Within the dealership operations, Hybrid Intelligence is revolutionizing customer engagement and service. AI-powered tools within sales and service platforms combine to help dealerships identify buyers most likely to purchase, present targeted trade-in and financing opportunities and forecast service needs based on real-time vehicle diagnostics. This is manifesting into a more personalized, effective, and proactive customer experience.
Post-sales experience will be more focused on proactivity than reactivity. Connected cars would communicate with dealerships directly to send service alerts before the issue arises. Higher customer retention and trust will be ensured as dealership profitability increases with smooth service operations.
The showroom experience will become very much digital and immersive. Consumers will explore vehicles via AI-driven virtual assistants, augmented reality configurators, and personalized video walk-throughs during servicing. Finance and insurance deals will move towards a more digitized approval process, and dealers will minimize the paperwork.
CIO&Leader: What does the strategic roadmap entail for automotive companies aiming to stay competitive, particularly in digital retail and emerging tech adoption?
Sandeep Kumar Jain: The key digital retail experience boils down to practicable AI-driven virtual showrooms, on-the-spot financing arrangements, and personalized vehicle recommendations. Buyers will begin to dictate a seamless online-to-offline journey where, with AI-based assistance, they may explore, configure, and buy vehicles remotely.
Predictive intelligence and automation will modify inventory and service operations for the good. Edge computing and real-time decision-making will be essential. By performing processing locally inside vehicles, firms will improve the aspects of safety, efficiency, and user experience without having to deal with cloud latency.
The automotive industry is being revolutionized by Hybrid Intelligence-AI-powered insights that are enhancing manufacturing, in-vehicle experiences, and dealership operations. The showroom experience is transforming into one led by digital with AI-powered virtual assistants, augmented reality configurators, and video walkthroughs enabling seamless exploration. Digitized financing and insurance approvals minimize paper-trail requirements and expedite the closing process.
CIO&Leader: What are the major challenges in driving the adoption of technologies like AI & ML?
Sandeep Kumar Jain: The adoption of AI and ML in businesses and industries faces several critical challenges that hinder large-scale implementation and efficiency.
One of the biggest hurdles faced is the shortage of skilled talent. Implementing AI and ML requires data scientists, software engineers, model trainers, and many more, but currently but there is a significant gap in the availability of professionals with the right skill set. This limits the ability of companies to scale AI-driven solutions effectively.
Data quality and integration is another major issue. AI systems depend on clean, structured, and well-integrated datasets from which the standards for high performance are set. But many organizations still have their data housed in silos with inconsistent and incomplete datasets. Lacking high-quality data means AI models are left speculating, thereby producing inaccurate predictions and unreliable insights that ultimately undermine their utility.
The concerns about the privacy and security of data are additional risks. Because AI systems deal with massive amounts of sensitive information, organizations have been preparing for cyber defense and have to comply with strict regulations such as GDPR and CCPA. Otherwise, they risk data breaches, regulatory violations, and such losses of consumer trust.
Integrating AI with the existing infrastructure is yet another challenge. Many companies run legacy systems that do not reasonably operate AI systems; thus, they will require investment for possible upgrades on reengineering. This makes the cost of application very resource-intensive.
Addressing these challenges calls for strategic planning, investment in training of the staff and strong data governance, and phased integration of AI into existing business models. The quicker the dealerships adapt to these technological transformations, the quicker they will be in the forefront of their business.