Article Summary
AI in collision repair is designed to support and enhance human estimators by automating repetitive tasks and enabling pre-estimate capabilities, not to replace them. By allowing customers and staff to upload damage photos before vehicles arrive at the shop, AI can generate initial assessments that streamline parts ordering and scheduling, improving efficiency and cycle time while alleviating pressure on experienced professionals facing industry shortages.
- AI automates lower-complexity, repetitive tasks, freeing estimators to focus on high-value, nuanced decisions rather than replacing them entirely.
- Pre-estimate capability allows damage assessment from photos uploaded before vehicle arrival, initiating parts procurement and scheduling within minutes.
- For low to medium-impact and cosmetic damage claims, AI is already capable of handling assessments with minimal or no human input.
- Full AI autonomy in repair estimation requires improved accuracy, seamless system integration, and broader industry trust in AI-generated assessments.
- AI-driven workflow changes reduce cycle time, improve customer satisfaction, and address the industry's shortage of experienced estimators.
UNLOCKING THE REAL POTENTIAL OF AI IN COLLISION REPAIR: BEYOND THE ESTIMATE
An interview with Max Ali, Head of Motor Engineering, Tractable
At the 2025 IBIS Global Summit in Istanbul, artificial intelligence took centre stage in conversations about the future of the collision repair industry. One of the speakers leading that dialogue was Max Ali, a seasoned expert in AI-driven estimating solutions. Following his presentation on how AI is transforming real-world repair workflows, Collision Repair caught up with Max to dive deeper into the industry’s response, the biggest misconceptions around AI, and what a truly intelligent repair process might look like.
Collision Repair magazine: You recently spoke at the IBIS Global Summit in Istanbul about AI in the collision industry. What was the feedback like, and what were your key takeaways?
Max Ali: The feedback was very encouraging. Attendees found the session informative and appreciated the opportunity to understand where AI is practically delivering value today and how it’s evolving.
There was a real appetite to move beyond the buzzwords and look at how AI is being applied on the ground.
My key takeaway was that while there’s strong interest, there’s still a lack of awareness around just how many parts of the repair journey AI can enhance—especially in terms of integrating it into the traditional estimating process.
CRM: There’s been a lot of industry talk about AI in recent years. What’s the most common misconception you hear?
Ali: The biggest one is that AI will replace human estimators. That’s not the case. What AI is really doing is helping to alleviate the increasing pressure on estimators, especially as the industry faces a shortage of experienced professionals and a slow pipeline of new talent.
AI can automate lower-complexity, repetitive tasks, giving estimators more time to focus on the more nuanced, highvalue decisions. It’s a tool to support—not to substitute.
CRM: Do you see a future where estimating becomes fully ‘human-less’? If so, when and under what conditions?
Ali: Yes, for certain types of claims— particularly low- to medium-impact and cosmetic damage—we’re already close to that point. AI is advanced enough to handle these scenarios with minimal to no human input.
But for full autonomy to become the norm, we’ll need continued improvements in accuracy, seamless integration with insurer and repairer systems, and broader trust in AI-generated assessments. That said, the real potential isn’t just in automation—it’s in changing how we approach the repair process altogether.
CRM: What do you mean by changing the process? Can you elaborate?
But AI allows us to rethink that flow. A customer, the recovery driver, or even front-of-house staff can upload photos via a secure web link before the vehicle even arrives at the shop. The AI can then generate an initial damage assessment that helps pre-load the work schedule and initiate parts procurement—often within minutes.
This pre-estimate capability isn’t just faster; it’s smarter. It’s one of the most overlooked benefits of AI, yet potentially one of the most impactful for efficiency, cycle time and customer satisfaction.
CRM: In your view, who has best captured the AI message in this space—both in vision and execution?
Ali: Having worked in this industry through its major transitions—from paper-based estimating to digital platforms and now AI—I’ve seen many approaches.
What makes Tractable different is our blend of industry experience and AI science. We don’t just train models on historical data; we design them to reflect real-world decisions made by experienced professionals.
That human grounding ensures our AI doesn’t just “guess” damage—it understands it in the context of repairability and workflow. It’s that commitment to practical, usable AI that sets our vision apart and keeps us aligned with the real needs of the industry.
