An insight into how AI is likely to open up new opportunities for OEMs in the near future
Artificial intelligence (AI) will hold as a key enabler in transforming the automotive industry. Currently, the automotive industry is focusing on the integration of AI in self-driving cars, while other application areas include R&D, procurement, supply chain management, manufacturing, mobility services, and customer experience.
Automotive manufacturers are currently working on implementing a range of AI technologies to mimic, augment and support actions of humans, including voice controls, telematics, interior-facing cameras, touch-sensitive surfaces, and personalized platforms. In-car assistants powered by natural language processing (NLP) and machine enable vehicles to respond to voice commands and infer the actions to take, without human intervention. AI systems are also being implemented in vehicles to provide more safety, ensuring users to enjoy a glitch-free and smoother experience.
This presentation will touch on:
- Types of AI technologies deployed in vehicles
- Key application areas of AI within the automotive value chain - Use case examples
- Companies that are actively involved in the development and commercialization of automotive-based AI technology
- Highlight some of the key investments trends
- Key initiatives and regulations pertaining to AI in the automotive sector
Table of Contents
1.0 Executive Summary
1.1 Research Scope
1.2 Research Methodology
1.3 Research Methodology Explained
1.4 Key Findings
2.0 Overview - AI in the Automotive Industry
2.1 AI Application in the Automotive Industry
2.2 Market Size - Global AI in Automotive Market
2.3 The Global Automotive Production by Region
2.4 AI in Automotive - Technology Value Chain
2.5 AI Use Cases Across Automotive Value Chain
3.0 AI in Automotive Research & Development Process
3.1 AI Enables Automotive R&D Teams to Review Data Efficiently, Improve Analysis, and Prioritize the Innovations
3.2 Use Cases - Research & Development
4.0 AI in Automotive Supply Chain
4.1 AI Reduces the Automotive Supply Chain Complexities by Making Logistics Systems Transparent, Lean, and Flexible
4.2 Use Cases - Supply Chain
5.0 AI in Automotive Manufacturing
5.1 AI-based Cobots Work Along with Human Operators, Completing Repetitive Tasks More Quickly and Increasing the Overall Efficiency
5.2 Use Cases - Manufacturing
6.0 AI in Automotive Marketing and Sales
6.1 Automotive Companies are Continuing to Adopt Programmatic Automation Using AI/ML Capabilities
6.2 AI Systems are helping OEMs to Increase their Revenue through Sales and Service Recommendations to Customers at the Right Time
6.3 AI Use Cases - Marketing and Sales
7.0 AI in Automotive Enhancing Driver/Customer Experience
7.1 Automotive Manufacturers are focusing on Making Interaction with Cars' AI Systems More Intelligent
7.2 AI Use Cases - Enhancing Driver/Customer Experience
8.0 Key Investments and Partnerships in the Automotive Industry
8.1 Automotive Companies are Accelerating their Interest in AI-led Startups to Enhance their Capabilities and Stay Competitive
8.2 Automotive Manufacturers are Teaming up to Accelerate their AI Implementation
9.0 Regulatory Developments in the Automotive Industry
9.1 US, Singapore, and China are Accelerating their Efforts to Make Autonomous Driving a Reality
10.0 Patent Landscape
10.1 The US and China are the Leading Countries in AI-based Automotive Patent Registrations
10.2 Research Initiatives Around AI will Result in Exponential Rise of Patents in the Next 5 years
10.3 Strategic Insights
11.0 Industry Contacts
11.1 Key Contacts
