1. Prioritize AI transparency: Build consumer trust by creating systems that allow for detailed, accurate analysis of decision-making processes.

2. Align innovation with compliance: Partner with regulators to establish clear liability standards and adapt to jurisdiction-specific AI regulations.

3. Test beyond expectations: Conduct advanced testing to ensure system reliability under real-world conditions.

Putting algorithms behind the wheel has introduced transformative possibilities to the automotive industry, but it’s also created new legal and regulatory challenges. This year’s survey highlights a significant concern: 78% of respondents identified assigning responsibility in AI-driven vehicle accidents as a top issue.

Compliance with jurisdiction-specific AI regulations also looms large, with 55% of respondents identifying it as a key challenge. The patchwork of state-level legislation, combined with international frameworks like GDPR and emerging federal guidelines, creates a complex maze for companies deploying AI-driven technologies.

Beyond these challenges, automotive companies are leveraging AI to optimize manufacturing processes (25%), enable predictive diagnostics for vehicle maintenance (21%), and enhance customer interactions through AI-driven cockpit features (27%). These applications offer significant potential to improve efficiency, reduce costs, and elevate the driving experience. However, they also may result in greater legal oversight to ensure compliance with emerging standards.

With 78% of survey respondents identifying responsibility in AI-powered accidents as their primary concern, the challenge is clear: How is fault determined when the driver is no longer in total control? 

Emerging regulations, like the Automated Vehicles Act, begin to address this complexity by assigning responsibility across a chain of stakeholders—drivers, insurers, manufacturers, and operators. For the industry, this may mean meeting new standards for algorithmic transparency and other testing.

These liability concerns also have broader implications for AI development. Automotive industry companies must now weigh the legal risks of deploying advanced AI systems against the competitive pressures to innovate.