CFO Insights: AI in the Automotive Dealership BY FORVIS MAZARS In Forvis Mazars’ recent peer group for automotive dealership chief financial officers (CFOs), the group focused much of its discussion on artificial intelligence (AI). If you’re an automotive dealer owner, CFO or another leader in the dealership organization who is looking to hear best practices or lessons learned from other dealers, keep reading. The observations in this article reflect an anonymized discussion and are intended as practical discussion points rather than a statistical survey. How Should Auto Dealership CFOs Govern AI Before Scaling It? As dealership groups experiment with AI, CFOs are weighing how quickly to adopt new tools against the need for governance, privacy protection and consistent internal controls. The discussion began with questions about which AI platforms groups are using, whether those tools are protected within the organization, and what types of information employees are allowed to enter. One CFO said their organization began with an AI governance policy developed with outside counsel and then reviewed it against existing corporate, privacy and HR policies. Another CFO adopted Claude and said the IT team built restrictions to prevent certain sensitive information from being entered. Participants emphasized that governance is not just a legal exercise. It also shapes adoption, training and trust. Several CFOs discussed the importance of reviewing AI outputs, monitoring for hallucinations, avoiding hard-coded numbers in AI-generated spreadsheets, and ensuring employees retain the underlying math and process knowledge needed to validate AI-assisted work. Many organizations are using risk management frameworks, such as the NIST AI Risk Management Framework, as a reference point for AI governance, risk assessment, monitoring and oversight. How Many AI Licenses Should an Auto Dealership Start With? Rather than rolling AI out across the entire organization immediately, several CFOs described a more measured approach. One organization avoided an enterprise-wide deployment because a full rollout could have represented a significant annual investment, choosing instead to begin with a smaller controlled user group. Another group chose an enterprise agreement with Claude and limited initial access to about 50 internal users to maintain better control. Dealership groups choosing smaller control groups attested that this allowed leadership to test use cases, monitor costs, and identify where AI created meaningful productivity and efficiency gains. Examples included complex portfolio dashboards, dealership balance sheet analyses, executive summaries, valuation summaries, and legal or operational training materials that previously required substantially more time and manual effort. Which AI Tool Is Best for Dealership Finance, Operations and Workflows? CFOs compared Copilot, Gemini, ChatGPT and Claude, noting that different tools appear better suited to different types of work. The discussion suggested that Copilot was useful within Microsoft applications, while several CFOs felt that Claude was stronger for more complex projects, analysis and structured tasks. One CFO noted that Copilot had been enabled broadly for managers, while Gemini Enterprise (Google) was used by some IT team members. The broader takeaway was that dealership groups may need to match the tool to the use case rather than assume one platform will satisfy every department’s needs. Where Are Auto Dealerships Using AI Beyond the Accounting Office? The discussion highlighted that AI use is expanding beyond finance and accounting. One CFO said service departments are using Copilot to help diagnose vehicles and respond to customer questions based on diagnostic information and customer complaints. Another said a general manager uses Claude to create a daily morning briefing 16 UTAH AUTO DEALER
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