04 June 2026
How artificial intelligence is reshaping vehicle repair and diagnostics
Article Summary
AI is transforming vehicle repair with smarter diagnostics, predictive maintenance, and faster service. Read on to learn how its helping to innovate global vehicle repair markets.
Artificial intelligence is transforming vehicle repair, improving the accuracy of vehicle troubleshooting and enabling smarter diagnostics. We look at some key innovations and analyze the addressable market for repair globally.
The automotive aftermarket is no stranger to artificial intelligence (AI) in cars. Messaging apps that schedule vehicle repair appointments in minutes, software that automatically sends maintenance interval reminders and algorithms that help with inventory management and remote vehicle diagnostic tools have been around for a while. These are examples of AI working quietly in the background.
But as vehicles become more complex and AI technology progresses, AI adoption is becoming more prevalent, especially in vehicle repair. Predictive maintenance, diagnostics, customer service, vehicle inspections and damage assessment are increasingly using AI. In predictive maintenance, for instance, AI is used to analyze the rising quantities of vehicle data to identify patterns and make vehicle repair services predictions.
Technology firms expand their role in AI-driven vehicle repair
As the vehicle repair and service industry embraces artificial intelligence in cars, technology firms and leading automotive suppliers are launching products and pursuing strategic acquisitions to strengthen their position in this rapidly evolving space.
In March 2026, Bosch announced plans to acquire Uptake Technologies, Inc., a Chicago-based startup specializing in AI-based predictive analytics for commercial fleets. Bosch said Uptake’s AI capabilities would expand its predictive maintenance offerings and vehicle health services capabilities.
Technology firms such as Uptake are leveraging AI to improve vehicle repair and maintenance in several ways. When a vehicle is already in the shop for routine maintenance, AI identifies minor, non-urgent repairs that can be addressed at the same time. This allows owners to get more out of scheduled vehicle repair services. AI is also used to enhance data quality by helping standardize fleet maintenance records, which often contain errors, missing details or inconsistent formatting. The cleaned data can be used for predictive modeling and trend analysis.
AI is also used to provide solutions that move from a fault code to vehicle repair, resulting in quicker, more accurate outcomes. “One fleet I reviewed recently had nearly 8,000 faults per vehicle annually, which makes it difficult to distinguish critical issues from noise,” stated Brian Silva, senior director of data science at Uptake. By applying AI, he said, the company can “reduce those 8,000 codes to just 5–10 actionable issues per vehicle each year.”
At the AAPEX Show in November 2025, Bosch demonstrated its AI-powered diagnostic assistant called the Super Technician. It uses Bosch’s global knowledge pool of vehicle repair issues and solutions to help technicians diagnose problems.
Swedish parts distributor Meko has rolled out a similar service. In March 2026, the company announced an AI service for faster and more accurate vehicle diagnostics. The service uses a database to provide technicians with the information needed to carry out vehicle repairs. The growing database includes information on the repairs handled by Meko’s workshop chains over the past decade.
Bilstein’s aftermarket brand Febi has launched a fluid testing device for garages that can assess fluid condition and contaminants on site. The AI-enabled vehicle diagnostic tool analyzes samples of fluids like engine oil or transmission fluid and generates a report detailing their condition and the likely causes of any abnormalities. The company says this process enhances transparency with the customer and opens new revenue opportunities.
In March 2026, AutoTechIQ, a digital vehicle assessment service in the US, introduced AutoQuoteIQ, a platform for workshops to streamline estimates. The platform uses AI, the shop's historical data and millions of work orders to help generate accurate and transparent vehicle repair estimates.
Global vehicle repair services expand as out-of-warranty fleet grows
S&P Global Mobility expects about 426 million vehicles in operation (VIO) to be out-of-warranty in Europe by the end of 2035, the highest of any region globally. This data provides an indication of the vast pool of vehicles the aftermarket will have to support with parts, service and repairs.
Greater China is forecast to have the second-largest pool of out-of-warranty VIO—337 million by 2035. The region’s out-of-warranty car parc is expected to grow at a healthy compound annual growth rate (CAGR) of 2% from 2026 to 2035, overtaking North America (CAGR: 1%) in overall volumes by the end of the decade.
The highest growth in out-of-warranty VIO among key global regions is expected in Other Asia Pacific (CAGR: 3.4%). This represents roughly 3.5x faster growth than in Europe or North America, albeit on a lower base. With a large middle-class population, emerging APAC countries are more sensitive to macroeconomic and credit conditions than Europe and the US, and that sensitivity tends to push owners to hold vehicles longer. This increases the out-of-warranty fleet and creates more aftermarket vehicle repair opportunities.
Outlook for artificial intelligence in vehicle repair and diagnostics
The innovations launched in the vehicle repair space indicate that AI-enabled vehicle diagnostic tools are especially useful for garages serving fleet vehicles, as the technology allows them to quickly assess multiple vehicles at once. This helps reduce downtime and ensure maximum vehicle availability.
Instead of replacing human mechanics, AI is likely to be a helpful tool that makes their work more efficient, reduces mistakes and speeds up repairs. Some entry-level jobs, like changing tires or oil, might transform as automation takes over those tasks. But new roles will appear, such as technicians who maintain and troubleshoot AI systems used in diagnostics and vehicle repairs.
Apart from vehicle diagnosis, practical applications of AI tailored to the aftermarket may also include enhancing the quality of product catalogs and regulatory compliance, where AI helps streamline adherence to industry standards through automation.
Companies are also using AI to change how drivers interact with their vehicles. California-based startup Sparq launched an on-board diagnostics (OBD) port device last year that simplifies vehicle diagnostics for car owners. The device translates complex vehicle diagnosis situations into plain English, allowing drivers to communicate with their vehicles using voice commands, text, images and even recordings of troubling sounds.
AI has the potential to extend its value beyond diagnostics into the full operating rhythm of a workshop or vehicle fleet. Chicago startup Uptake points to a future in which expanding sensor coverage across tires, trailers and other components will make service more proactive and less disruptive. Vehicle repair businesses are likely to move toward more integrated systems, in which diagnostics, technician workflow, scheduling, parts ordering and billing work together.
Today, production scrap still outweighs EOL batteries as a recycling feedstock because the EV fleet is relatively young. Gigafactory rejects, off-spec cells, and electrode scrap are currently the largest near-term source of recoverable material. Over the next decade, however, EOL volumes are expected to overtake scrap.
The long-term strategic importance is clear. Cobalt recovery is particularly attractive because of its value and its role in evolving battery chemistries. Nickel, supported by continued use of NCM cathodes and growth in high-nickel variants, is also positioned to provide nearly a third of demand through recycling by 2037.
Lithium is more complex. Although recycled lithium could still supply more than 22% of demand by 2037, this is lower than earlier estimates because low lithium prices and the rise of LFP weaken recycling economics. Without regulation, lithium recovery may fall short of its potential.
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This article was published by S&P Global Mobility and not by S&P Global Ratings, which is a separately managed division of S&P Global.