5: AI implementation for dealers
5a. Step 1: Audit Existing Systems

The first step in AI implementation is auditing your current systems to identify operational inefficiencies and areas where AI can add value. This audit will guide you in selecting the right AI tools to optimise processes across various departments.
Customer Service:
- Assess the volume and types of customer queries you receive.
- Identify gaps in response time or quality.
- Example: Are customers often waiting too long for service confirmations?
Inventory Management:
- Review current stock tracking systems and ordering workflows.
- Example: Are parts frequently overstocked or running out?
Operations:
- Evaluate how technicians are assigned tasks and routes.
- Example: Are there delays caused by poor scheduling or inefficient routes?
Sales and Marketing:
- Analyse lead generation, customer segmentation, and campaign effectiveness.
- Example: Are your marketing emails personalised, or do they follow a one-size-fits-all approach?
How to Perform an Audit:
- Gather data on key performance indicators (KPIs) across departments.
- Interview employees and customers to identify pain points.
- Document opportunities where AI could improve processes or outcomes, ensuring alignment with business goals.
5b. Step 2: Prioritise Focus Areas
Once you've completed the audit, the next step is to prioritise the areas where AI will have the most significant impact.
High-Impact Areas for dealers:
- Automating customer service responses to reduce wait times and improve satisfaction.
- Predictive inventory management to minimise downtime and optimise stock levels.
- Personalising marketing campaigns to increase conversion rates and customer engagement.
Prioritisation Criteria:
- Customer Impact: Will AI improve customer satisfaction or loyalty?
- Operational Efficiency: Does AI reduce costs or save time?
- Revenue Growth: Can AI create new sales opportunities?
Example Prioritisation for a dealer:
- Start by implementing predictive maintenance tools to prevent costly equipment downtime.
- Once successful, expand into AI-powered customer communication for streamlined booking and customer service.
5c. Step 3: Select the Right AI Tools

Now that you’ve identified the areas for AI application, the next step is to select the tools that best align with your dealership’s needs and budget.
Customer Service:
- Use tools like ChatGPT or Colossyan for chatbots and video tutorials to streamline customer interactions.
Inventory Management:
- Make can automate stock updates and order placements to optimise inventory tracking.
Operations:
- Use Perplexity to optimise route planning and scheduling for technicians.
Marketing:
- Simplified is great for automating campaign creation and personalising marketing messages.
Evaluation Checklist:
- Is the tool user-friendly and easy to integrate?
- Does it address the specific challenges identified in your audit?
- Is it scalable to grow with your dealership?
Pro Tip: Begin by trailing free or low-cost versions of these tools to evaluate their effectiveness before making a long-term investment.
5d. Step 4: Train Your Team
Effective AI implementation relies on empowering your team to use AI tools confidently and competently.
Training Methods:
- Host workshops on specific tools, such as Make or Polycam, to ensure employees are comfortable using them.
- Provide hands-on tutorials tailored for customer service teams, marketing teams, and technicians.
- Offer role-specific training to technicians on predictive maintenance systems to ensure they can leverage AI for more efficient service.
Onboarding Strategy:
- Appoint a ‘technology champion’ in each department to lead the adoption of AI tools.
- Start with simple tasks, like automating appointment reminders, and gradually scale to more complex processes.
Pro Tip: Use resources like Runway’s video tutorials to make training more engaging and effective.
5e. Step 5: Monitor and Measure Success

After implementing AI tools, it’s crucial to monitor their impact and refine your processes based on performance data.
Key Metrics to Monitor:
- Customer Satisfaction Scores: Look for improvements in response times or positive customer feedback.
- Operational Efficiency Metrics: Track faster job completion times or reductions in delays.
- Revenue Growth Indicators: Measure increases in service bookings or parts sales.
Example Metrics for dealers:
- Decrease in stockouts by 30%.
- Increase in customer retention by 15%.
Iterative Improvement:
- Regularly review performance data to assess the effectiveness of AI tools.
- Adjust AI tools and workflows based on feedback from employees and customers to improve outcomes.
Pro Tip: Schedule quarterly reviews to ensure that AI solutions continue to align with dealership goals and drive meaningful results.
5f. Step 6: Scale and Expand
Once initial successes have been achieved, scale your AI capabilities to other areas of the dealership.
Scaling Strategies:
- Integrate advanced tools like Polycam for 3D modeling or HeyGen for personalised video messages to enhance customer engagement.
- Expand automation beyond customer communication to include back-office processes like invoicing or parts procurement.
Continuous Learning:
- Stay updated with the latest AI advancements through resources like Maginative and The AI Breakdown podcast.
- Regularly test new tools or features to maintain a competitive edge and stay ahead of industry trends.
Pro Tip: Engage employees in brainstorming sessions to identify additional opportunities for AI adoption across the dealership.
Practical Example of AI Implementation for dealers
- Audit Finding: Customers frequently call to check appointment availability.
- Tool Selection: Deploy ChatGPT for a chatbot to handle booking queries.
- Implementation: Train the chatbot with FAQs and integrate it into your dealership’s website.
- Measure Success: Monitor call volume reduction and customer satisfaction post-implementation.
- Scale: Expand the chatbot’s capabilities to include troubleshooting tips and service reminders.
By following these steps, servicing dealers can successfully implement AI technologies, continuously improve processes, and scale their operations to meet the evolving demands of customers and the marketplace.