Cockpit Agent Engineering Research Report 2025: Exploring the Breakthrough from Digital AI to Physical AI - ResearchAndMarkets.com

DUBLIN--(BUSINESS WIRE)--The "Cockpit Agent Engineering Research Report, 2025" has been added to ResearchAndMarkets.com's offering.

The 2025 Cockpit Agent Engineering Research Report delves into the current and future landscape of cockpit agents, laying out the technical roadmap through R&D and engineering phases. The report reveals trends in AI assistants' evolution from mere assistants to proactive agents in vehicles, focusing on their ability to take actionable steps on behalf of users.

In 2025, cockpit AI assistants have transitioned to performing actions autonomously, enhancing user experiences by automating tasks like ordering food. Employing long-term memory, tool calling, and multi-agent collaboration, these AI systems offer seamless interactions.

A significant advancement is the adoption of tool calling technologies. The progression from OPEN AI's Function Calling to China's Anthropic MCP, and Google's A2A, highlights the increasing efficiency and integration in multi-agent systems, as showcased by Lixiang Tongxue's innovative MCP/A2A framework.

GUI agents are another forefront development, processing user commands via natural language and interfacing through software to simulate human actions. While the technology remains nascent, companies like Li Auto, Geely, and Xiaomi are paving the way for robust deployment, enhancing interaction accuracy and user engagement.

On the emotional front, NIO's Nomi sets the benchmark for achieving "emotional resonance" in AI assistants. Through dynamic expressions and a sophisticated "emotion engine" module, Nomi manages rich, human-like interactions and personalized experiences. This pushes toward the transformation from digital to physical AI, underscored by multi-agent collaborations facilitating complex task generalizations.

A pivotal shift from L2 to L3 agents is underway, with Chinese OEMs striving to achieve proactive prediction capabilities. This transition promises breakthroughs in generalization by learning directly in the real world, thereby developing physical AI that reacts and adapts to environmental changes.

Innovative approaches such as Fei-Fei Li's "augmented interactive agents" blend real-world data with expert behavior modeling, reinforcing the emergence of agents capable of envisioning environmental dynamics.

In 2025, multi-agent collaboration becomes integral to AI systems in vehicles. For instance, GAC's "Beibi" uses advanced intent recognition to streamline user operations across varied scenarios, improving efficiency by negating isolated agent management and fostering a cohesive and responsive cockpit ecosystem.

Key Topics Covered:

1 Status Quo and Trends of Cockpit Agents

• Overview of Cockpit Agents
• Overview of Cockpit Agent Scenarios
• Status Quo of Cockpit Agents
• Development Trends of Cockpit Agents

2 OEM Agent Solutions

• Lixiang Tongxue
• NIO
• Xpeng
• Geely
• Xiaomi
• Great Wall Motor
• BAIC
• SAIC
• Chery
• Others

3 Supplier Agent Solutions

• Huawei
• Alibaba Cloud
• Baidu Cloud
• Tencent Cloud
• ByteDance & Volcano Engine
• SenseTime
• Zhipu AI
• iFLYTEK
• Thundersoft
• Kotei Agent
• Lenovo
• TINNOVE

4 Agent Practical Technology

• Intent Recognition
• Knowledge Graph and Search
• Emotion Recognition
• Inference Acceleration
• Recommendation System
• Tool Calling
• MAS
• GUI Agent

5 Problems in Agent Application

• The Computing Power Balance Point of the "Edge-Cloud" Deployment
• Architecture Design of Multi-Agent Systems
• Business Model Design
• Effectiveness of Scenario Application
• Training Bias
• Data Privacy

For more information about this report visit https://www.researchandmarkets.com/r/roca7b

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