Top of Mind From Automotive Dealership CFOs
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 below 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 started with an AI governance policy developed with outside counsel, then reviewed the policy 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, watching for hallucinations, avoiding hard-coded numbers in AI-generated spreadsheets, and making sure 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 enterprisewide 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, & Workflows?
CFOs compared Copilot, Gemini, ChatGPT, and Claude, noting that different tools appear better suited to different types of work. The discussion suggested Copilot was useful within Microsoft applications, while several CFOs felt Claude was stronger for more complex projects, analysis, and structured task work.
One CFO noted that Copilot had been turned on broadly for managers, while Gemini Enterprise (Google) was being 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 by synthesizing multiple reports and email updates, helping the general manager quickly focus on priority items.
Participants also cited use cases in marketing, communication strategy, customer complaint responses, business development, policy writing, training materials, insurance claims forms, valuation support, private equity term sheet review, and dealership financial statement analysis. Several groups are also using AI to clean up existing procedure manuals and draft new procedures for review and approval.
Should Dealership CFOs Build Data Lakes or Rely on AI-Enabled Vendor Tools?
As vendors increasingly position themselves as AI-enabled, CFOs discussed how to separate practical value from inflated claims. Several said they are testing both broad AI tools and specialized vendors while watching for overlap across systems already used in the dealership.
One CFO described using an AI-enabled data warehouse and reporting tool to upload policies and procedures and query both policy content and financial data. Another described using a data lake to combine DMS data, customer relationship management (CRM) data, CSI data, website data, loaner data, original equipment manufacturer (OEM) inputs, and other sources for AI-supported analysis.
The discussion raised a strategic question for dealership groups: whether to build internal data lakes and reporting environments or continue relying on vendor bolt-ons. One CFO noted that building a data lake can require meaningful investment and technical resources, while another suggested that AI may reduce some of the heavy lifting that previously required consultants.
How Can Dealership Groups Control Vendor Redundancy as AI Tools Multiply?
Several CFOs discussed the challenge of controlling redundancy when stores or general managers pilot new vendor products. Participants mentioned advertising and vendor spreadsheets, financial reviews, marketing leadership review, vendor approval controls, IT access controls, and systems such as DealerVault as ways to create more visibility and discipline. At the end of the day, one CFO noted, they approve every expense that comes through the dealership and make sure their services do not overlap with one another.
Marketing data platforms were also part of the conversation. Participants discussed tools designed to aggregate customer and marketing data in one place and noted that owning and organizing data could eventually help reduce or renegotiate third-party vendor costs.
Can AI Automate Dealership Accounting Tasks, or Is It Still Mainly an Efficiency Tool?
One CFO asked whether groups have moved beyond AI-assisted analysis into true task automation for accounting processes such as floor plan reconciliations, OEM postings, factory statement entries, payroll tasks, commission calculations, and other manual spreadsheet-heavy work.
Several CFOs said automation of accounting-office tasks is a goal, but most are not fully there yet. One CFO is considering outside help to build structured AI projects, train controllers or store champions, and identify repetitive tasks that can be automated or standardized. Another suggested reverse engineering existing reconciliations by asking AI to analyze current workpapers and create an instruction set that could then be used to build a repeatable process.
The group generally framed the near-term opportunity as time savings, better consistency, and improved training rather than immediate headcount reduction. Participants also emphasized the importance of trusted human review, testing, sampling, and avoiding write-back to core DMS systems without controls when AI is cleaning or changing data.
Should Dealerships Block Public AI Tools on Company Networks?
As enterprise AI licenses roll out, CFOs also discussed whether to restrict access to public AI sites on company networks. The responses were consistent: it is important to block public tools on company machines, reinforce policies through HR acknowledgements and warn employees not to upload company or customer data into public AI tools.
Network restrictions are only one part of the control environment. Even when public AI tools are blocked on company devices, employees may still be able to access them from personal phones or personal accounts, which makes policy communication and ongoing education critical. Several CFOs discussed the need to clearly define what types of information can and cannot be entered into AI tools, especially when customer data, employee information, financial records, or other sensitive dealership information may be involved.
The common theme was that blocking access may help to reduce risk, but it does not replace the need for training, governance, and practical detective controls.
To Wrap It Up: AI for Automotive Dealerships
As your dealership drives along the road of AI, identifying what tools to use, how to employ them at scale, and how to remain compliant and achieve return on investment will depend on your goals, long-term strategy, and organizational structure. Of most importance is keeping customer data safe and finding the best use cases for the areas of the organization you want to focus on.
How Forvis Mazars Can Help Auto Dealers With AI Transformation
As dealership groups evaluate AI opportunities, the challenge is no longer simply choosing a tool. Success depends on aligning AI initiatives to business objectives, protecting sensitive data, identifying high-value use cases, and creating a roadmap for sustainable adoption.
Forvis Mazars combines deep automotive dealership experience with AI, technology, and process transformation capabilities to help dealers move from experimentation to measurable results.
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