Reconstructing Automotive R&D: IAT and CAAM Co-Release Preview of Intelligent Agent White Paper

Source: Author: Date:2026-05-28 Read:106

On May 11, the White Paper on Intelligent Agent Empowered Automotive R&D and Design: From Tool Assistance to AI-Native (2026) was officially previewed at the China Association of Automobile Manufacturers (CAAM) May Information Conference. Jointly edited by CAAM and IAT Automobile Technology, and compiled with participation from FAW, Changan, BAIC, Chery, Great Wall Motors, Li Auto, NIO and other automakers, the white paper is grounded in new quality productive forces and the national strategy of “Artificial Intelligence Plus”. 

It systematically addresses three core issues: how intelligent agents reconstruct automotive R&D paradigms, how they achieve effective implementation, and how they support high-quality industrial development. 

As a co-editor-in-chief, IAT contributed its experience, technical methodology, and core technology product system in AI-empowered automotive R&D, providing engineering verification and industry examples for the “large model + industrial software + cloud-native + intelligent agent” technology foundation and six application scenarios. The official version of the white paper will be released at the China Auto Forum 2026 in July.

Over 20 Years of Expertise in Full-Vehicle R&D, Pioneering AI-Empowered Product Matrix

Founded in 2007, IAT is the first independent automotive R&D company listed on China’s A-share market and a leading independent automotive R&D enterprise in Asia. Its business covers full-process vehicle R&D, core component development, and new energy intelligent platforms, and it pioneered full-vehicle turnkey services for independent automotive R&D firms in China. To date, IAT has developed nearly 500 vehicle models for more than 80 customers.

In AI-empowered automotive R&D, IAT has made it a core strategy and launched the “AI + Digital Intelligent Creation” product system at the end of 2025, featuring three core modules: Yuanfang (R&D Knowledge LLM): Enables drawing analysis, solution generation and intelligent review, shortening R&D cycles. Its Fangcun product integrates AI and digital prototypes for automatic gap and interference detection. 

Yufeng (AI Aerodynamic System): Predicts aerodynamic drag and generates compliant profiles at the early development stage, cutting aerodynamic R&D time by two months. TAI Styling AI 3.0: Upgraded from a single design tool to a comprehensive R&D AI platform, supporting 3D generation, video generation, model training and cross-role, cross-region real-time collaboration, with capabilities extended to intelligent vehicles such as aircraft and robots.

Highlights and Significance: Paradigm Reconstruction, Six Scenarios, Three-Stage Path

The white paper covers four core achievements:

1. Clear value positioning: Realizes full-link efficiency improvement, knowledge capitalization, paradigm reconstruction and independent software control, targeting to shorten vehicle R&D cycles from 36–48 months to 18–24 months.

2. Technology foundation construction: Proposes a four-in-one foundation of “large model + industrial software + cloud-native + intelligent agent” and a four-layer architecture, solving reliability and engineering constraints of general AI in automotive industry. IAT’s product matrix consisting of Yuanfang, Fangcun, Yufeng and TAI serves as the engineering validation of this foundation across the entire R&D workflow.

3. Six application scenarios: Covers knowledge engineering, multimodal generation, scientific computing simulation, 3D geometry, R&D collaboration and engineering automation, empowering enterprises to improve quality and reduce costs.

4. Implementation Roadmap: The implementation is structured into three phases: capability building, scenario scaling, and platform ecosystem development. Clear milestones and product priorities are defined for the 2025–2029 period, along with a comprehensive enabling framework covering organization, talent, funding, data governance, and security to ensure systematic execution and sustainable development.

The white paper also calls on the industry to uphold engineering credibility and security, advance data governance, advocate open collaboration, and accelerate the development of independent toolchains and standards.

As co-editor-in-chief, IAT translated its over 20 years of full-vehicle R&D experience and industrial data into industry consensus, laying a solid practical foundation for the white paper. 

This preview marks a key leap for IAT from a “full-vehicle R&D service provider” to an “industry definer of AI-native R&D standards”. Going forward, IAT will work with CAAM and industrial partners to promote the pilot and application of intelligent agent technology, accelerate China’s automotive R&D from tool assistance to AI-native, and support the building of an automotive powerhouse.

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