EV automakers have doubled down on the use of advanced technologies and increasingly rely on AI and automation to address market volatility and production challenges.
In 2025, electric vehicle (EV) manufacturers face distinct market pressures and manufacturing challenges that set them apart from traditional internal combustion engine (ICE) automakers. While both types of manufacturers share common issues like global supply chain volatility and regulatory pressures, EV makers deal with unique hurdles tied to the nature of their technology and rapidly evolving market dynamics. Increasingly, EV makers are turning to AI and automation for help.
EV Market and Manufacturing Challenges
EV manufacturers must contend with a number of market and manufacturing issues, which require great efficiency and flexibility to successfully overcome.
On the market front, they face great price competition from traditional automakers that have entered the EV market, as well as pure EV startups. Additionally, there are great regulatory uncertainties, with many manufacturers finding that EV subsidies are being reduced or eliminated, impacting demand.
Additionally, consumers expect an EV to have a comparable or better price than an ICE equivalent. They also expect EVs to incorporate the latest innovations in auto safety, comfort, entertainment, and more.
On the manufacturing front, many EV platforms are still evolving, making it hard to lock in efficient, repeatable manufacturing processes. Manufacturers must also manage the integration of thermal management systems, high-voltage safety features, and more that are not found in ICE manufacturing.
Also, EV makers are increasingly moving toward the in-house development of motors, inverters, battery management systems, and software. That approach is unlike ICE production, where outsourcing is more common. It adds complexity and strains engineering teams.
See also: Electric Vehicle Innovation on Display at CES
The Need for AI and Automation
Given such market pressures and manufacturing challenges, EV manufacturers are turning to newer technologies. That might include making use of robotics and automation for repetitive tasks, using AI-driven quality control and process optimization, and employing digital twins to simulate and manage production in real time.
Simply put, EV manufacturers are increasingly leveraging automation and AI to optimize production operations across nearly every stage of the manufacturing lifecycle. Some of the specific actions being taken and technologies used include:
Smart Factory Automation
EV factories are adopting Industry 4.0 principles to automate and connect production lines. This includes:
- Robotic assembly for precise and repetitive tasks like welding, painting, and battery pack assembly.
- Automated guided vehicles (AGVs) and autonomous mobile robots (AMRs) to transport materials and parts within the factory.
- Digital twins to simulate and optimize production environments in real time.
AI for Predictive Maintenance
AI analyzes sensor data from machines to predict failures before they happen. This:
- Reduces unplanned downtime.
- Extends the lifespan of equipment.
- Improves overall equipment effectiveness (OEE).
Quality Control with Computer Vision
Machine learning and computer vision systems inspect parts and assemblies for defects far more accurately than humans. They’re used for:
- Surface inspection of vehicle bodies.
- Verifying weld quality.
- Ensuring battery cell alignment and integrity.
Process Optimization with AI Analytics
Manufacturers use AI to analyze production data and:
- Identify bottlenecks.
- Adjust workflows in real time.
- Reduce energy consumption, which is especially important in battery manufacturing.
Battery Production Enhancements
Battery production is a key differentiator in EVs. AI helps:
- Optimize chemical mixing and cell formation processes.
- Monitor thermal behavior during assembly.
- Detect potential safety issues early.
In addition to these areas, EV makers are using AI models to forecast demand, manage inventory levels, and optimize logistics. This is critical for EV manufacturing due to the complexity of battery and semiconductor supply chains.
They are also using AI to provide help with customization and flexibility. AI enables mass customization by dynamically adjusting production parameters based on customer specifications—supporting personalized EV features without major disruptions to workflow.
Some notable examples of putting these new technologies into practice include:
- Tesla uses a highly automated “Gigafactory” model, where AI and robotics handle everything from chassis assembly to battery module construction.
- Volkswagen has implemented AI-driven visual inspection systems and digital twins to boost factory efficiency.
- BMW uses AI in its EV plants to improve logistics and robot training, speeding up production while maintaining quality.
A Final Word
All automakers are using emerging technologies to speed the time from concept to production, improve operational efficiencies, and better meet changing customer demands.
EV automakers have doubled down on the use of advanced technologies and increasingly rely on AI and automation to address market and production issues.
