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 reviews, vendor approval controls, IT access controls, and systems such as DealerVault as ways to increase visibility and discipline. At the end of the day, one CFO noted, his office approves 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 automating accounting office tasks is a goal, but most are not 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 in terms of time savings, greater consistency and improved training rather than an 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 acknowledgments 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 down the road of AI, identifying which tools to use, how to employ them at scale, and how to remain compliant while achieving return on investment will depend on your goals, long-term strategy and organizational structure. Most important is keeping customer data safe and identifying the best use cases for the areas of the organization you want to focus on. 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. Learn more at forvismazars.us. 17 UTAH AUTO DEALER
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