As we step into 2025, the automotive retail industry is ready to take its next step in modernizing its operations, where artificial intelligence (AI) and machine learning (ML) are poised to reimagine dealership operations. The focus is shifting from customer-facing AI applications to leveraging these technologies for back-end data optimization, particularly in inventory management and operational efficiency.

In 2024, AI’s role expanded to include critical back-office functions like identity and income verifications, as well as credit application processing. However, a recent survey revealed that only 5% of dealerships currently use AI for inventory management and pricing optimization, highlighting a substantial gap in adoption.

The need for an inventory data platform

At the heart of this evolution is the emergence of what industry insiders are calling the “inventory data platform.” This platform represents the convergence of AI, ML, and big data analytics, specifically tailored to the needs of auto dealerships. It’s not just about inventory management; rather, it’s the powerful intersection of inventory data, audience data, and media consumption data. This comprehensive approach enables dealers to determine make and model inventory needs at the ultra-local level, analyzing a vast array of data points, including local market trends, economic indicators, consumer behavior patterns, and even social media sentiment, to predict which models are likely to be in high demand in the coming months.

This level of insight allows dealers to optimize their inventory mix, ensuring they have the right vehicles on their lots at the right time. It’s not just about stocking popular models; it’s about having the perfect balance of vehicles to meet the specific needs and preferences of their local market. This targeted approach can significantly reduce the risk of overstocking slow-moving vehicles while ensuring high-demand models are always available.

These platforms also tackle operational efficiencies, such as duplicate leads. For instance, 80% of leads are often duplicates on the same unit, and once the unit sells, most dealers consider these leads dead. However, agentic AI can detect when a lead remains actively in-market and identify alternate in-stock units a buyer is likely to engage with. This AI-powered agent can then automatically retarget this relevant inventory to the “dead” lead, effectively bringing it back to life and re-engaging potential buyers.

Digital transformation is expected to also accelerate significantly in 2025, with dealers investing heavily in platforms offering a seamless online car-buying experience. These platforms will combine customer relationship management (CRM), dealer management system (DMS), inventory, Google Analytics, and customer data platform (CDP) into a single system where machine learning can analyze and monitor data 24/7.

Another critical aspect where AI is set to revolutionize dealership operations is in carryover and risk management. AI-driven systems in 2025 will offer sophisticated risk assessment tools that can identify potential slow-moving inventory early in the sales cycle.

These tools will not only flag at-risk vehicles but also provide actionable recommendations for mitigating that risk. This might include suggesting targeted marketing campaigns, recommending optimal pricing strategies, or even advising on the best timing for inter-dealership transfers. AI systems will also predict risk vehicles on day one, enabling dealers to make optimal pricing and promotion moves early. Dealers often wait too long to address pricing on such units, leading to costly aging. By using these AI tools, dealerships can pre-empt financial losses and improve inventory turnover efficiency.

Perhaps one of the most exciting applications of AI in 2025 will be in vehicle pricing and markdown strategies. With AI, dealerships can implement dynamic pricing strategies that respond in real-time to market conditions, competitor actions, and individual vehicle attributes.

For new vehicles, AI algorithms can analyze a wealth of data to suggest optimal pricing that maximizes both sales volume and profit margins for new and used vehicles. These systems can take into account factors such as local market demand, competitor pricing, vehicle features, and even the time of year to recommend the most effective pricing strategy.

When it comes to aged units, AI-powered markdown strategies will become increasingly sophisticated. Rather than relying on blanket markdown policies, dealerships will be able to implement tailored approaches for each vehicle. AI systems can analyze the specific characteristics of a vehicle, its market position, and historical sales data to recommend the most effective markdown strategy. This might involve gradual price reductions, bundling with value-added services, or even suggesting the optimal timing for trades between dealerships.

Adapt and learn

The true power of these AI-driven systems lies in their ability to learn and adapt. As they process more data and observe the outcomes of their recommendations, these systems will continuously refine their algorithms, becoming more accurate and effective over time.

What makes the 2025 landscape particularly exciting is the intersection of the inventory data platform with customer data platforms and audience breakouts. This convergence will allow for highly targeted marketing and sales strategies, matching specific vehicles with the most likely buyers and creating personalized marketing campaigns.

By integrating customer data, dealerships can align their inventory strategies with the specific needs and preferences of their customer base. For instance, if the customer data platform indicates a growing interest in electric vehicles among a particular demographic, the inventory data platform can adjust its recommendations to ensure the dealership is well-stocked with the right mix of EVs to meet this demand.

While inventory levels are generally improving, there is an imbalance across brands. Some brands, like Toyota and Lexus, are expected to maintain a tight day supply, while others, such as Stellantis, may continue to operate with a high day supply. Used car day supply is expected to remain tight and steady.

Furthermore, economic pressures will continue to impact the automotive market in 2025. Higher interest rates may pressure affordability, leading to longer loan terms and greater emphasis on leasing options. Rising operational costs, including labor and energy, could narrow profit margins, putting pressure on marketing costs

Dealers are expected to put mounting pressure on original equipment manufacturers (OEMs) to offer competitive incentives, address challenges with final pay of significantly aged units, and better configure vehicles to match consumers’ affordability challenges. Shareholders will likely increase pressure on OEM leadership to be more responsive to current economic conditions.

The used car market is predicted to remain robust, but luxury and larger-sized vehicles may be challenging to sell. Dealers will need to focus heavily on certified pre-owned (CPO) programs to attract budget-conscious customers, despite shortages from off-lease vehicles.

As these AI-powered tools become more prevalent, dealerships that embrace them will be better positioned to navigate market fluctuations, respond to changing consumer preferences, and maintain profitability even in challenging economic conditions. However, successful implementation will require more than just technological investment and the right strategic partners. Dealerships will need to foster a data-driven culture, where decisions at all levels are informed by insights derived from these platforms.

Len Short is the executive chairman of Lotlinx, which offers an inventory platform that can enable dealers to automatically adapt to market dynamics, mitigating inventory risk through VIN-specific strategies. For more information, visit www.lotlinx.com.