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AI has the potential to address skilled labor shortages, help companies and communities to achieve their sustainability goals, while optimizing waste collection to be more efficient and eco-friendlier.
By Jed Dawson

The widespread adoption of artificial intelligence has impacted industries as diverse as healthcare, supply chain management, energy, and agriculture. Despite the hype cycle, including fears of job losses and hopes for revolutionary advances in productivity, AI has not yet been widely adopted in waste management. While chatbots for customer service are already in use and applications like data analysis and route optimization are on the horizon, waste management is lagging behind other industries in the widespread adoption of AI. As is true for the use of AI in many industries, the greatest potential lies in how we can harness its power to improve the lives of the living, breathing humans who are actually doing the work.

Five-star Service
Right now, tools like chatbots, e-mail automation, and autoreplies are widely available for customer service in a wide range of industries, including waste management. However, there remains vast untapped potential for AI in customer service. The ability to integrate AI into call centers can assist representatives by analyzing conversations while simultaneously pulling up relevant information—such as driveway photos without bins present—and even initiating service orders. This customer-centric approach empowers customer service teams to provide faster, more accurate, and personalized support. With real-time AI assistance, representatives can address customer concerns more efficiently, reducing wait times and eliminating the frustration of repetitive explanations. Additionally, AI’s ability to analyze conversations in real time ensures that customers receive relevant information and tailored solutions, fostering trust and enhancing the overall service experience.

Contamination Reduction
Material recognition is another use case for AI and machine vision in the waste management industry. This technology is already being deployed at material recovery facilities (MRFs) and even in the hoppers of waste collection vehicles. By leveraging proprietary AI models, waste management organizations can alert drivers of risks using tablets, cameras, and specialized sensors to detect contaminants. For example, if a load marked as organic waste contains trash, the system flags it as a contamination risk. Similarly, if recyclable materials are found in a solid waste load, it identifies this as a missed opportunity for recycling and can prompt educational outreach to the resident. These applications not only streamline waste management operations and increase sustainability efforts, but they also improve customer satisfaction while providing frontline employees with valuable, actionable data-driven insights in the flow of their day-to-day work.

Safety First
The potential for AI to improve the lives of workers can be extended even further, helping to keep them safe, well-trained, and even ensure that they are feeling supported in their jobs. Waste management jobs are both physically and mentally demanding, requiring long hours, repetitive tasks, and continuous focus on safety for themselves and the communities they serve. Drivers operating automated side loaders daily navigate tight spaces while managing precise equipment, which can be physically taxing and mentally draining. AI can monitor performance and provide instant feedback or coaching to improve efficiency and safety. AI tools can recognize and reward exceptional performance, boosting morale and fostering a sense of accomplishment, which is critical for employee retention in every industry. Additionally, these AI-powered systems can offer data-driven, proactive suggestions, such as taking breaks or addressing signs of fatigue, promoting driver well-being, and reducing the risk of accidents.

Improved Efficiency
By harnessing the data generated during day-to-day operations, waste management companies can monitor and optimize collection routes. Real-time data analysis can adjust for delays, unexpected workload increases, or interruptions. AI can be used for dynamic load-balancing between drivers, ensuring operational efficiency, and increasing customer satisfaction with timely service. These tools can also enable companies to efficiently and effectively manage their most important assets—their human resources. AI can help to support drivers with specific scheduling needs, overtime preferences, and more, acting as support mechanisms for route supervisors—not a replacement—once again providing tangible benefits for hardworking frontline employees.

Compliance Made Easy
In the future, AI could be leveraged to streamline regulatory compliance by analyzing constantly changing regulations. As states, municipalities, and countries continue to introduce new regulations designed to drive sustainable outcomes, waste management organizations are often faced with a patchwork of requirements based on their operating locales. Regulatory compliance for sustainability acts as a critical driver for the waste management industry to adopt more environmentally responsible practices, minimizing their environmental footprint and promoting a circular economy. Proper compliance documentation is critical to achieving regulatory alignment because it provides a clear, verifiable record of adherence to the complex and evolving sustainability requirements imposed by various governing bodies. Accurate documentation ensures that waste management organizations can demonstrate compliance, avoiding penalties and building trust with stakeholders, including customers, governmental bodies, and community members.

In all of these applications, AI provides waste management organizations with powerful tools to better serve their employees, customers, and communities. By keeping the humans using these tools top-of-mind, companies can achieve more sustainable outcomes, while providing a customer-focused approach that bolsters their brands through superior service delivery. In addition, AI’s role in retaining, training, and supporting skilled employees ensures continuous improvement, continuity of service, and creates safer working environments.

Looking to the Future
While we are only at the beginning of understanding the full capabilities of AI to improve waste management, there remain several barriers to adoption. The industry’s often-fragmented and siloed nature, along with a long history of paper-and-pencil route management, can lead to slower adoption rates for new technologies. The hyper-localized nature of waste collection—where regulations, customer needs, and infrastructure vary widely by region—makes it challenging to implement sweeping technological advancements at the same pace as other industries. Overcoming these obstacles will require fostering collaboration between stakeholders, while demonstrating clear value to encourage widespread adoption of AI-driven solutions that benefit drivers, customers, and the environment.

Fears of AI replacing humans in the workplace should be replaced with understanding of how this technology can enhance the workplace. AI can create a safer, more efficient, and more human-centric waste management industry. It has the potential to address skilled labor shortages, help companies and communities to achieve their sustainability goals, while optimizing waste collection to be more efficient and eco-friendly. Implementing AI with a human-centered focus creates numerous positive outcomes, where employees feel supported, customers receive exceptional service, and communities benefit from more sustainable and efficient waste management practices. | WA

Jed Dawson is VP of Product Engineering for Routeware. With more than 25 years of experience in the waste and recycling industry, Jed began his career at Paso Robles Waste & Recycle before transitioning to Core Computing as the Director of Innovation. At Core, Jed played a pivotal role in developing eMobile, a groundbreaking solution that led to a shift across the waste industry from fragile, custom hardware to more reliable Android platforms. In this role, Jed expanded the team and guided them through Core’s acquisition by Routeware. Today, Jed leads the Product Engineering team at Routeware, overseeing all product lines and driving innovation within the company. For more information, visit .