Artificial Intelligence in Automotive: Strategic Transformation in Non-Production Processes report has been published
The “Artificial Intelligence in Automotive: Strategic Transformation in Non-Production Processes” report, prepared in cooperation with Doğuş Otomotiv and Doğuş Technology within the scope of the Be Node Research project carried out by the Turkish Informatics Foundation (TBV) platform, Starting Point, has been published.
The Be Node Research program of the Turkish Informatics Foundation (TBV) shared with the public the results of its new research conducted with the support of Doğuş Otomotiv and Doğuş Technology. The report titled “Artificial Intelligence in Automotive: Strategic Transformation in Non-Production Processes”, written by Fatma Tarlacı from the University of Texas and Çağlar Üçler from Özyeğin University, examines the transformation created by artificial intelligence in processes such as sales, service, logistics and customer experience beyond the production line.
The report reveals that artificial intelligence in the automotive industry is no longer just a speed tool, but has become the building block of corporate culture and customer experience. By bringing together academic research, field data and corporate application examples, it offers a concrete transformation roadmap for the Turkish automotive ecosystem.
Highlights of the report
The use of artificial intelligence in the automotive industry is expanding from production to after-sales services. Efficiency increases are achieved through hyper-personalized experiences in showrooms, instant access to information in call centers, and predictive maintenance processes in service operations. In this new era, artificial intelligence agents position themselves as a second operator alongside employees, directing people to focus on exception management and strategic decisions. The report also analyzes the Doğuş Otomotiv example in the “single data infrastructure – multiple brand identity” equation, revealing how collective intelligence can maintain balance between brands. This structure preserves the uniqueness of brands with an artificial intelligence governance model that learns each brand’s tone of voice, customer expectations and communication style separately.
Policy and strategy recommendations
Infrastructure: The success of artificial intelligence starts with data integrity. Increasing data quality, ensuring integration between systems and creating central management architectures are among the critical steps.
Measurement: The five-dimensional KPI framework, which includes speed, quality, cost, satisfaction and usage rates, allows measuring the impact of artificial intelligence not only on efficiency but also on the level of trust and experience.
Competence: New skills such as agent orchestration, verification processes, ethical awareness and product-oriented thinking that will strengthen human-machine collaboration define the corporate transformation areas of the coming period.
Fatma Tarlacı, faculty member at the University of Texas, said: “Thanks to artificial intelligence, we are starting to understand the driver and the user better; we can personalize at a depth we could not do before. In this way, the vehicle turns into not just a machine, but a co-pilot that understands you and can determine your needs.”
Özyeğin University Faculty Member Çağlar Üçler said, “Artificial intelligence used to be inside the factory; it came out from there and became the connective tissue of the customer-touching experience in the automotive industry. From dynamic pricing to AR/VR-based experiences, we have become able to do things we could not do before.”
Doğuş Otomotiv New Business Development and Entrepreneurship Unit Manager Irmak Mutlu Ejder said, “We focused on cleaning and integration of data before artificial intelligence. Afterwards, we increase interaction at touch points such as the second-hand platform with personalized suggestions; we improve the buyer-seller experience with image processing. Predictive planning is critical for the management of ‘the right product/service at the right time’ in the supply chain.”
Doğuş Technology Data Science Manager Doğuş Kıdık said: “We are developing agent-based solutions in the call center, after-sales, data analysis and content production. Chatbots accelerate access to information; competency-assessment agents measure performance and suggest improvement. In the multi-brand structure, we use separate data sets and customized models for each brand; we test it in person with brand teams before going live.”
Starting Point Leader Cem Leon Menase said, “Railways looked like a transportation technology, but they transformed not only travel, but also the economy and daily life. Today, we see a similar thing in artificial intelligence; although the first effects appear on the internet infrastructure, the real big transformation will come with the establishment of artificial intelligence’s own ecosystem.”
The report emphasizes that artificial intelligence is no longer an “auxiliary technology” in the automotive industry, but has become the center of decision-making and customer experience management. The winning organizations will be those that position AI as a strategic tool not only for operational efficiency, but also for trust, quality and sustainability.
To review Be Node Research project reports click.
Automobile Magazine – English
