Understanding AI: Exploring Different Types and How They Work in Auto Retail and Finance

This blog is part of our “AI in Auto Retail and Finance” series, which explores how AI transforms the auto industry, from reducing costs to improving efficiencies. Check out our other blogs on revolutionary changes AI brings to auto retail and finance, how AI drives down costs, enhances process efficiencies, and AI-based co-pilots.

Welcome to our “AI in Auto Retail and Finance” blog series, where we explore the transformative role of artificial intelligence (AI) in the dynamic landscape of the automotive industry. Let’s first understand what AI is and how different types of AI function in the auto retail and finance sectors.


Artificial Intelligence (AI) is no longer a concept reserved for science fiction; it’s a driving force in modern business, particularly auto retail and finance. As AI evolves, it brings unprecedented changes, making operations more efficient and customer interactions more personalized. For business owners and professionals in auto retail and finance, understanding the different types of AI is essential to harness its full potential. This blog will explore three main types of AI—Traditional AI, Generative AI, and Vertical AI—and how each operates and impacts the industry.

What is AI?

Artificial Intelligence (AI) refers to the ability of machines to simulate human intelligence, including learning from data, reasoning through problems, and making decisions. AI helps streamline operations, improve customer experiences, and drive innovation in auto retail and finance.

Types of AI

Traditional AI

Traditional AI encompasses the early forms of AI that rely on rule-based systems and predefined algorithms. These systems are excellent at handling specific tasks within set parameters but cannot learn from data.

For example,

  • Expert systems that assist in loan approval processes based on predefined rules.
  • Rule-based systems for managing inventory in auto dealerships.

Traditional AI operates strictly within predefined rules and cannot adapt or learn from new data. It is reliable for repetitive, rule-based tasks but needs more flexibility.

Generative AI

Generative AI refers to AI systems that create new content, such as images, text, and music. These systems learn patterns from existing data and use that knowledge to generate novel outputs.

For example,

  • AI systems are generating personalized marketing content for auto dealerships.
  • AI tools create dynamic financial reports based on real-time data.

Generative AI learns from vast amounts of data, identifying patterns and trends to generate new, relevant content. This ability makes it incredibly useful for tasks that require creativity and adaptation.

Vertical AI

Vertical AI is explicitly tailored for particular industries or domains, addressing unique challenges and tasks within those sectors. This type of AI optimizes processes and solves problems specific to an industry.

For example,

  • AI solutions that streamline auto loan applications and approvals.
  • AI systems that manage automotive inventory, predicting demand and optimizing stock levels.

Vertical AI solves industry-specific problems by applying specialized knowledge and processes, making it highly effective in optimizing workflows and enhancing productivity within those domains.

How Each Type Works

Traditional AI:

Traditional AI works by following predefined rules and algorithms. It excels in environments where tasks are repetitive and structured.

For example, a rule-based system can manage a dealership’s inventory. The system follows set rules to reorder cars when stock falls below a certain level, ensuring the dealership always has popular models. In auto finance, it could be like an expert system used for credit scoring. It evaluates loan applications by checking predefined criteria like credit score, income level, and employment status, providing a fast and consistent decision on loan approvals.

Generative AI:

Generative AI works by learning patterns from large datasets and using that knowledge to create new, original content.

For example, an AI tool that generates personalized email campaigns for potential car buyers. By analyzing customer data, the AI creates customized offers and recommendations, increasing the likelihood of a sale. In auto finance, it could be an AI-driven system that produces real-time financial forecasts. By examining historical data and current market trends, AI can predict future financial performance, helping businesses make informed decisions.

Vertical AI:

Vertical AI addresses specific industry challenges by applying specialized knowledge and tailored algorithms.

For example, an AI system that optimizes the supply chain for car parts. It predicts which parts will be in demand based on current market trends and historical data, ensuring that dealerships always have the necessary components in stock without over-ordering. Or an AI platform that automates the entire auto loan process. From initial application to final approval, the AI handles data verification, risk assessment, and compliance checks, significantly reducing processing time and improving accuracy.

Understanding the different types of AI is crucial for auto retail and finance businesses. Each type offers unique advantages, from rule-based decision-making to creative content generation and industry-specific solutions. By leveraging these AI technologies, companies can streamline operations, enhance customer experiences, and stay ahead in a competitive market. Embracing AI is not just about keeping up with technology; it’s about driving innovation and achieving long-term success in the dynamic landscape of auto retail and finance.

Read the other blogs in this series: