Summary
Experts at Auto-ISAC’s conference warned that the rapid adoption of connected-vehicle software and dealership AI tools is outpacing basic safeguards. API-driven integrations across vehicles, dealers and third parties are expanding the attack surface, while many retailers lack governance, visibility and data hygiene to manage the resulting risk and compliance obligations.
Key risks identified
- API sprawl: Hundreds of third-party-managed interfaces create entry points that are hard to inventory and monitor.
- AI governance gaps: Tools are deployed for efficiency and ROI without clear policies, oversight or controls on data use and model outputs.
- Data quality: Incomplete or inconsistent data undermines detection, vulnerability analysis and AI effectiveness.
- Compliance fragmentation: Varying rules across jurisdictions complicate scaling AI and data sharing.
- Adversary advantage: Attackers leverage automation and AI while defenders rely on manual processes.
Immediate actions for dealers
- Establish a cross-functional AI governance board and adopt a recognized framework (e.g., seven pillars: fairness, accountability, responsibility, transparency, security, privacy, reliability).
- Map your API environment: inventory connections, data flows, privileges and third-party ownership; segment high-risk interfaces and enable continuous monitoring.
- Strengthen vendor diligence: request security documentation, integration diagrams, data collection scope, storage/processing locations, authentication methods and logging practices; validate before production.
- Invest in data hygiene: allocate time for cleansing, normalization and testing; ensure logging supports audits and forensics.
- Train staff and set policy: define acceptable AI use, data-handling rules and an approved tools list with review/exception processes.
- Automate detection and response: deploy tooling that correlates signals across systems and vendors to match attacker speed.
- Measure progress with audits and KPIs (e.g., API inventory coverage, vendor attestation rates, mean time to detect/respond, policy training completion).
Operational guardrails before go-live
- Scope narrowly: limit initial AI use cases and required permissions.
- Perform security and privacy reviews of models, prompts and data pipelines.
- Confirm data minimization, retention, encryption and locale-specific compliance requirements.
- Run pilots with synthetic or masked data; define rollback plans and success criteria.
Why it matters
Connected vehicles generate massive data that flows through third-party APIs; layering AI into dealership operations increases connections and potential misconfigurations. Dealers can’t control the full ecosystem, but they can set vendor expectations, demand transparency, and build internal structures that prioritize responsible AI and security without stalling innovation.
Outlook
The industry is shifting from experimentation to consolidation: scaling what works while standardizing governance and controls. Dealers that catalog APIs, formalize AI governance, vet vendors rigorously and improve data quality will have clearer risk visibility and be better positioned to keep pace with AI-enabled adversaries.
