Accelerating the Software-Defined Automotive Industry with AI-Powered Enterprise Search and AI Agents

Automotive is no longer just about cars, it’s about software, AI, and digital ecosystems. According to the Infosys Automotive Industry Outlook 2025, the sector faces two dual imperatives: the electrification of mobility and the rise of software-defined vehicles (SDVs). Together, they represent both the greatest opportunity and the greatest challenge for OEMs and suppliers.

Electric vehicles (EVs) are essential to decarbonization, yet adoption is slower than expected. At the same time, SDVs are set to dominate manufacturing, growing from just 3.4% of production in 2021 to nearly 90% by 2029.

This transformation makes one thing clear: knowledge, how it’s accessed, applied, and shared, is becoming mission critical.

The Automotive Industry at a Crossroads

The industry is under pressure from all sides:

• Electrification plateau: Despite EVs reaching 20% of new U.S. vehicle sales in 2024, demand is slowing due to high costs, insufficient charging infrastructure, and supply chain constraints. Profit margins remain thin compared to internal combustion engines (ICE).
• Rise of SDVs: The market for automotive software and electronics is projected to hit $462 billion by 2030. OEMs must adapt to shorter innovation cycles and continuous over-the-air software updates.
• Digital-first product cycles: Digital twins, generative AI in design, and modular software-hardware integration are reshaping how vehicles are engineered and brought to market.

The shift is not just technological, it’s cultural. Automakers must operate like agile tech companies while managing the safety and regulatory complexity of traditional manufacturing.

The Knowledge Bottleneck

If the future is software-defined, then knowledge is the fuel that powers it. Yet the automotive sector faces persistent challenges:

• Fragmented data: Information is scattered across R&D silos, CAD systems, regulatory documents, supplier records, and aftersales data. This fragmentation slows decision-making.
• Pressure to innovate: Companies must release new features faster, while ensuring compliance with safety, emissions, and cybersecurity standards.
• Talent shortages: The Future of Jobs 2025 study highlights a growing skills gap in EV and software engineering. Reskilling is slowed by siloed knowledge systems.

Even with advanced tools like digital twins or AI-assisted design, organizations often struggle to connect the right data to the right person at the right time.

How AI-Powered Enterprise Search Unlocks Transformation

This is where enterprise search becomes essential. AI-powered search platforms unify access to structured and unstructured data, accelerating innovation and execution:

• Unified data access: Engineers and designers can instantly find CAD files, technical manuals, standards, code repositories, and supplier records.
• Strengthening digital twins: Context-aware retrieval feeds digital twin simulations with accurate, real-time data from across the value chain.
• Software + hardware integration: Enterprise search bridges DevOps pipelines with hardware engineering, supporting agile collaboration and ASPICE compliance.
• Faster onboarding: Natural language search enables engineers and technicians to find expertise quickly, reducing ramp-up time.

The result is not only efficiency, but also innovation, giving automotive leaders the ability to anticipate problems and design proactively.

Enter AI Agents and Retrieval-Augmented Generation (RAG)

The next frontier goes beyond search. Enterprises are now deploying AI Agents, specialized assistants that don’t just retrieve information, but take action based on it. When combined with retrieval-augmented generation (RAG), these agents can:

• Contextualize answers: AI Agents powered by RAG pull verified information from enterprise data, reducing hallucinations and ensuring compliance.
• Assist in decision-making: Engineers can query complex design trade-offs or regulatory requirements in natural language, and agents provide concise, evidence-backed answers.
• Automate workflows: From generating compliance reports to summarizing supplier contracts, AI Agents streamline repetitive but knowledge-intensive tasks.
• Scale expertise: RAG-enabled agents extend the reach of scarce experts, making critical know-how accessible across global teams.

For automakers building SDVs, this means development cycles that are faster, safer, and more aligned with both innovation goals and compliance standards.

From SDVs to SDx: The Software-Defined Enterprise

The logic of SDVs doesn’t stop at the vehicle. Infosys highlights the rise of Software-Defined Everything (SDx), where modular, software-first architectures extend across the enterprise.

With AI-powered search and AI Agents, organizations can:

• Deploy new processes faster.
• Ensure resilience against supply disruptions.
• Adapt quickly to shifting consumer demands.

In this context, enterprise search and AI Agents form the connective tissue of the SDx enterprise, enabling collaboration, innovation, and agility at scale.

Sinequa by ChapsVision: Powering Automotive Transformation with Enterprise AI

At Sinequa by ChapsVision, we provide the AI-powered search and knowledge backbone that the automotive industry needs to thrive in the era of SDVs and SDx.

Our platform combines:

• Enterprise Search that unifies all types of data (structured + unstructured) such engineering content, CRM, ECM, ERP and multiple PLM systems..
• AI Agents that leverage retrieval-augmented generation (RAG) for accurate, contextual answers.
• Generative AI that accelerates digital twin initiatives, regulatory compliance, and workforce reskilling.

By connecting people with the knowledge they need, instantly, securely, and in context, Sinequa empowers manufacturers to innovate faster, operate smarter, and redefine mobility for the software-first era.

Conclusion

The future of mobility is electric, autonomous, and software-defined. But none of it can be achieved without solving the knowledge bottleneck.

Enterprise search, AI Agents, and RAG are no longer optional, they are the backbone of innovation for the automotive industry. Companies that master knowledge discovery will not only overcome today’s EV and SDV challenges but also unlock the full potential of the software-defined enterprise.