How AI Is Helping Auto Recyclers Improve Efficiency and Scale Operations

AI can help auto recyclers improve efficiency by reducing administrative workload, organising information more effectively and freeing up time for revenue-generating activity. For operators facing labour pressure and rising costs, the real value of AI lies in practical, targeted use that supports growth without requiring a full-scale systems overhaul.

Auto recycling facility manager standing among organised shelves of used vehicle parts, illustrating AI-supported inventory management and operational efficiency in an indoor dismantling environment. — Natasha Broxton

Artificial intelligence is often discussed in broad terms, but for auto recyclers, the more useful question is a practical one: can it reduce workload, improve internal processes and free up time for growth?

For one Milwaukee-based operator, the answer appears to be yes.

Select Auto Parts & Sales, a 125,000 sq ft indoor facility led by Natasha Broxton, has been operating for more than 14 years and is increasingly using AI to support day-to-day business tasks, from workflow management and internal organisation to routine administration. According to the company, these tools have helped streamline operations and free up more time for higher-value work. Through Alitura Group, the firm’s AI implementation business, Broxton also supports other auto recyclers and small business operators in adopting and using AI systems in their own day-to-day operations.

That matters in a sector where time is constantly under pressure. From inventory processes and sales support to documentation and staff coordination, many recycling businesses are still balancing growth ambitions against the reality of labour-intensive administration.

A Practical Approach to AI Adoption

What stands out in this case is that AI has not been introduced as a large-scale technology overhaul. Instead, it has been used in a focused and incremental way.

Rather than attempting to transform the entire business at once, the company appears to have identified areas where digital tools could reduce friction in existing processes.

That kind of targeted adoption is likely to be more relevant to many recyclers than ambitious technology programmes that require major costs, restructuring, or specialist teams.

In operational terms, the value of AI is not in the label itself. It is in the ability to handle repetitive work faster, organise information more effectively and support quicker decision-making.

Why This Matters for Auto Recyclers

Across the vehicle recycling sector, businesses are facing similar challenges: tighter margins, rising costs, labour shortages and increasing pressure to run more structured, data-aware operations.

Against that backdrop, AI is beginning to look less like a trend and more like a practical support tool.

If administrative friction can be reduced, recyclers have more capacity to focus on the activities that directly affect performance, parts sales, customer service, stock accuracy, marketing and supplier relationships. Even modest efficiency gains can have a meaningful commercial effect when applied consistently across the business.

For smaller and mid-sized operators, that may be the most important takeaway. AI does not need to arrive as a disruptive platform change. It can begin with a narrow operational purpose and expand only when it proves useful.

A Wider Industry Signal

There is also a broader message here for the sector.

Auto recycling has often been viewed from the outside as a traditional, manual industry. In reality, many operators are already embracing more advanced approaches to logistics, stock control, dismantling strategy and digital sales. The use of AI is simply the latest extension of that shift.

That does not mean every claim around AI should be accepted uncritically. Vendor-led case studies naturally emphasise success, and results will vary depending on business model, staff capability and the quality of existing processes. But the underlying direction of travel is clear: digital tools are becoming more accessible, and recyclers are finding practical ways to put them to work.

Natasha Broxton, CEO, Select Auto Parts & Sales | Founder, Alitura Group, said:

“My advice to any operator is simple: start where the money is leaking. Before you implement any AI tool, that’s the question you have to ask. For us, the leaks were missed after-hours calls, inconsistent pricing, slow inventory lookups, and too many decisions running through me as the owner. We addressed each one systematically. Our inbound call capture rate went from 61% to over 90%. We now handle 2,000 to 3,000+ calls a month without adding headcount. Over three years of phased implementation, we’ve achieved 30% revenue growth. AI didn’t change everything at once; it stopped the bleeding, one leak at a time.”

Source note: This article is an original editorial rewrite based on publicly available case study material published by Google about Select Auto Parts & Sales. Original source: www.publicpolicy.google/stories/auto-select-parts-sales-wisconsin