Why faster dry times no longer mean compromising finish quality
For decades, the collision repair industry has accepted a seemingly unavoidable trade-off. If you wanted a premium finish, you had to sacrifice speed. Faster-drying clearcoats often raised concerns about gloss retention, appearance, flow, leveling or long-term durability. Shops learned to work within those constraints because chemistry simply had limits.
Today, that assumption is beginning to change.
Advances in artificial intelligence (AI), predictive modeling and materials science reshape how coatings are developed, tested and refined. AI in automotive refinish proves most valuable as a tool that helps technical teams move faster toward better-performing solutions. For collision centers facing pressure to improve throughput, reduce energy consumption and maintain quality standards, that shift matters.
Why Dry Time Has Always Been Difficult to Improve
Clearcoat performance remains a complex aspect of automotive refinish chemistry. A product has to cure quickly enough to keep vehicles moving through the shop, but it also has to deliver appearance characteristics that painters and customers expect, such as gloss, smoothness, depth, durability and repairability. Historically, improving one characteristic often compromised another.
Reducing bake time, for example, could make it harder for the clearcoat to spread evenly and create a smooth finish. Increasing cure speed might make the finish more difficult to polish and refine later. Chemists traditionally worked through those variables sequentially, testing formulations one at a time and refining them incrementally.
That process worked, but it was time-intensive and limited by the number of combinations humans could realistically evaluate.
Modern coatings development proves far more complex than simply mixing ingredients and hoping for the best. Every paint formula contains many ingredients that must work together properly, making product development a complex process. The challenge? Finding a way to narrow those possibilities down efficiently.
How AI Changes the Development Process
Artificial intelligence helps accelerate that narrowing process.
In coatings development, AI can evaluate far more possible paint formulas than people could realistically test by hand. Instead of evaluating variables strictly in sequence, researchers can use advanced modeling tools to identify promising paths much earlier in the development process. Importantly, AI is not replacing chemists or technical expertise. Human guidance remains central to the process.
What AI does particularly well is process large amounts of data quickly, identify patterns and help technical teams eliminate less practical paths sooner. That allows scientists to spend more time validating high-potential solutions in the lab and less time manually sorting through endless formulation variations.
The result? Teams see faster innovation cycles without removing the thorough testing required in automotive refinish. Every formulation still needs to undergo laboratory validation and real-world testing before reaching the market. But by helping teams reach feasible formulations faster, AI can significantly shorten development timelines.
A Real-World Example
One recent example is the development of PPG’s DELTRON NXT DC7020 Speed Glamour Clearcoat. Traditionally, “speed” and “appearance” have rarely coexisted comfortably in the same clearcoat conversation. Most chemists would say achieving both simultaneously is extremely difficult. The objective behind this product was to challenge that assumption.
Using AI-assisted development processes alongside traditional chemistry expertise, technical teams were able to evaluate a broader range of formulation possibilities and identify combinations capable of delivering both accelerated cure times and premium appearance performance.
The result was a clearcoat capable of reducing bake time to approximately five minutes at 140°F, significantly shorter than typical bake cycles that often range from 15 to 30 minutes, while still maintaining the appearance standards painters expect.
The product can also air dry in less than an hour, offering shops additional flexibility depending on booth availability and workflow needs. For body shops, those time savings can have meaningful operational impacts.
What Faster Cure Times Mean for Shops
Reducing cure times affects overall shop efficiency in several ways.
Shorter bake cycles can help shops move more vehicles through the paint booth each day. In busy facilities, even reasonable time reductions can create measurable scheduling advantages over the course of a year.
Energy savings also become significant. Paint booths are among the highest energy-consuming assets in many collision centers. Reducing bake time directly reduces energy usage, which can help offset rising utility costs while supporting broader sustainability goals.
In some cases, the numbers become substantial. A shop performing roughly 1,500 repairs annually could potentially reduce energy consumption significantly each year, helping lower utility costs. Air-dry capability can further reduce energy demand when workflow conditions allow.
At the same time, shops cannot afford to trade productivity gains for rework or appearance issues. Throughput improvements only matter if the finish quality remains consistent. That is why balancing speed with appearance remains critical.
Innovation Beyond Paint
AI’s impact on refinish operations extends beyond coatings formulation itself.
Digital tools used throughout the collision repair process increasingly incorporate AI-assisted capabilities to improve color matching accuracy, reduce waste and streamline workflow efficiency.
Digital tools that help technicians identify paint colors, mix products accurately and find color formulas more quickly help painters spend less time correcting mismatches or manually managing mixing processes. These technologies contribute to the same broader goal: improving efficiency while maintaining consistency and quality.
For shops navigating technician shortages, rising operational costs and increasing repair complexity, those detailed efficiencies can add up quickly.
What’s Ahead
While the technology behind coatings development is evolving rapidly, the industry’s priorities remain unchanged.
Collision repair facilities still need products that help reduce cycle times, improve profitability, minimize waste and deliver reliable results. Painters still expect products to perform consistently under real-world conditions.
AI is simply becoming another tool helping manufacturers solve those longstanding challenges more efficiently. AI can help experienced technical teams process information faster, explore broader possibilities and bring validated solutions to market sooner, so body shops can boost performance, savings and profitability.
Nicole Sinclair is the PPG Collision and Allied Products Segment Director for the Automotive Refinish business. She is a marketing leader with 29 years of experience and 10 years driving business growth, profitability, and market share expansion across the automotive and industrial sectors. For more information, visit www. ppg.com/refinish
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