AI in dealerships: why access alone isn’t enough

AI is now part of everyday dealership activity

Helping teams work faster and influencing how they write and respond across the customer journey, the issue around AI is no longer about awareness but about how consistently and effectively AI is applied.

A recent article from AM Online explores the growing use of generic AI tools across UK dealer groups and the questions this creates around security, governance, data ownership and their suitability for more complex automotive retail applications. As adoption develops, the focus is increasingly shifting from simply using AI to understanding where it genuinely adds operational value.

Informal use is already happening

In many dealerships, AI use is already happening informally. Sales Executives may use it to draft follow-ups, Service Advisors to simplify technical notes and Managers to summarise feedback. These are practical use cases, but when individuals adopt AI tools without clear guidance or oversight, they can create inconsistent standards and potential data risks across the business.

And it’s this which creates a clear requirement for leadership.

Why structure and ownership matter

Use of AI needs ownership. Teams need a set of agreed tools and clear boundaries around security, data use and customer communication. Outputs should always be reviewed and managers need to coach good habits rather than rely on trial and error.

We focused on this in our recent webinar, The Dealership AI Reality Check: What’s Working, What’s Risky and What Comes Next and one of the key risks is assuming that access equals capability. In practical terms, teams need structured prompts, clear expectations and ongoing feedback to use AI effectively in a customer-facing environment.

The risk of unchecked outputs

Whilst AI can produce confident responses, they can often be inaccurate and use generic language that fails to resonate with the customer. In a dealership environment, where trust and accuracy are critical, this simply can’t be left unchecked.

At RTS we’ve talked a lot about the importance of human review at every stage, ensuring that AI supports communication rather than replacing critical review and human judgement.

Practical use over theory

Effective adoption starts with the problem AI needs to solve and focuses on practical use cases close to the role. AI can help draft and structure responses but people must check accuracy, add context and ensure the customer receives clear next steps. AI technology supports the process but judgement will always remain with the individual.

This aligns with the core principle from our recent webinar: AI should enhance clarity and consistency, not remove accountability.

Why coaching is now the missing link

This is why coaching is becoming central to AI adoption. Teams need to understand how to use AI effectively, how to review outputs and how to apply it consistently within their role. Without this, it won’t deliver value and could actually cause harm to reputation.

As AI becomes more visible across automotive retail, the question for dealerships is not whether to use it, but whether they have the structure, guidance and coaching in place to use it well.

What does this mean for you?

• Make AI use visible and consistent across your team, rather than leaving it to individual preference
• Define clear guidelines on approved tools, data use, security and customer communication standards
• Build structured prompts and examples that reflect real dealership scenarios
• Reinforce the importance of reviewing and refining AI outputs before sending
• Coach teams regularly so good habits become part of everyday activity

For further practical guidance, take a look at our free-to-access Essentials Guide, AI Fundamentals: What Every Professional Needs to Know