The motor trade is undergoing a technological revolution, with artificial intelligence (AI) now integral to a wide range of sector-specific applications. These include AI-driven customer recommendation engines for vehicle sales, automated finance and credit decisioning, predictive maintenance for vehicles, dynamic inventory management, and AI-powered chatbots supporting after sales and service enquiries. As the Government’s AI Opportunities Action Plan highlights, the sector’s reliance on AI is set to increase. However, with innovation comes risk, and businesses must ensure that their adoption of AI is both ethical and compliant.
Here are some key considerations for motor trade businesses to manage risk while implementing AI ethically and compliantly.
1. Contractual Agreements
Licensing agreements are crucial for any technology rollout in the motor trade. These agreements should clearly outline the scope of use, including specific dealership or workshop applications, and address sector-specific risks such as errors in vehicle pricing or finance offers, licensing fees, duration, termination conditions, and obligations clearly. Motor trade businesses should pay special attention to clauses related to updates, maintenance and support, ensuring robust service levels are in place. AI evolves, and updates (and bugs) are inevitable, making it essential to define responsibilities in the agreement.
2. Data Privacy and Protection
The accelerated adoption of any new technology brings challenges, with data privacy being a significant one in AI. Data protection compliance and the use of AI are not automatically mutually exclusive. Motor trade businesses should verify that third-party AI providers comply with data protection laws such as the UK GDPR, especially given the sensitive nature of data typically handled in this sector, like customer contact details, driving licence information, and financial data collected during vehicle purchases or servicing. Data processing agreements should specifically address how this information is used, stored, and deleted. Adopting a data minimisation approach – sharing only what is strictly necessary – can further reduce risk.
3. Transparency and Explainability
Choose AI solutions that offer transparency and explainability in their decision-making processes, particularly for automated decisions that directly affect customers, such as finance application outcomes, insurance quotes, or service recommendations. Motor trade businesses must be able to explain AI-driven decisions to customers, especially where these impact creditworthiness or eligibility for offers. A recent study in America showed 62% of consumers would trust brands more if they were transparent about AI use, and 84% would have more trust in AI demonstrating explainability. Transparency is not only a regulatory expectation but also a commercial imperative. Businesses must be able to explain AI-driven decisions in the event of a customer complaint or regulatory investigation.
4. Ethical Use of AI
Ethics is a crucial topic in AI. More than two in five consumers (43 percent) are concerned about the ethical use of AI by companies. It is important for motor trade businesses to ensure their AI providers adhere to ethical guidelines, avoid biases, and ensure fair treatment of all users. This is particularly critical in vehicle finance approvals and insurance pricing, where regular audits and bias testing should be conducted to ensure compliance with the Equality Act and to prevent discrimination based on protected characteristics. This includes understanding how the AI algorithms are trained and tested. Regular audits and bias testing should be conducted to ensure that AI systems do not inadvertently discriminate against certain groups, maintaining both legal compliance and customer trust.
5. Regulatory Compliance
While the law around AI is constantly evolving, there is currently no specific UK AI-focused legislation. Instead, the UK’s regulatory landscape for AI use is centred around a pro-innovation approach, based on sector-specific guidance and generally adopts a tech-agnostic stance. Users in the motor trade must confirm that the AI solution complies with relevant regulations, including automotive-specific laws and general AI regulations such as FCA rules for motor finance, and consumer protection laws relevant to vehicle sales, advertising and servicing. Businesses must ensure that their AI solutions do not inadvertently breach these requirements.
6. Cybersecurity Measures
Like any software, AI systems are vulnerable to hacking and data breaches. The latest Government figures show that half of UK businesses have experienced cyber security breaches or attacks in the last 12 months. Assess AI providers’ cybersecurity protocols to protect against data breaches and cyber threats, with particular attention to the unique risks associated with dealership management systems, and customer databases. Ensure that any integrations with dealership IT infrastructure are secure and regularly audited. This includes regular security audits and compliance with cybersecurity standards, along with a clear incident response plan for potential data breaches or cyber-attacks involving AI systems.
7. Liability and Risk Management
It is important to clearly define liability in the licensing agreement, especially in cases where the AI system causes sector-specific issues such as incorrect vehicle valuations, mispriced finance offers, or errors in service scheduling. Contracts should address these scenarios explicitly, and businesses should consider insurance products tailored to the automotive sector to cover AI-related risks. Licensing agreements should include clear indemnity clauses and consider whether additional insurance is required to cover AI-related risks.
8. Intellectual Property Rights
It is advisable to understand the intellectual property rights associated with the AI solution, including the ownership of data generated by AI systems. Contracts should clarify who owns this data and how it can be used, especially if it holds value for aftersales or marketing purposes. This should be addressed explicitly in the contract to avoid future disputes. Ensure expert guidance is sought in this specialist field.
9. Vendor Reliability and Reputation
Conducting thorough due diligence on AI providers before implementation is crucial. Motor trade businesses should prioritise vendors with proven experience in the automotive sector, requesting case studies or references from other dealerships, manufacturers, or finance providers to ensure the vendor understands the unique challenges of the industry.
10. Ongoing Monitoring and Evaluation
Finally, it is important to establish processes for continuous monitoring and evaluation of the AI system’s performance using KPIs relevant to the motor trade, such as increased sales conversion rates, improved service booking efficiency, or reduced finance application and vehicle repair cost assessment processing times. Regularly review outputs, compliance with regulations, and alignment with business goals. Agreements should stipulate the ability to exit if these are not met. Set clear KPIs for the AI system and review them regularly to ensure continued alignment with business objectives and regulatory requirements.
AI presents significant opportunities for the motor trade, but its adoption must be underpinned by robust legal, ethical, and operational safeguards. By taking a proactive and informed approach, businesses can harness the benefits of AI while minimising risk.
