The last mile is undergoing its most significant transformation since the invention of the delivery van.

Autonomous vehicles, drones, and robotics are moving from pilot programs to real-world deployment, promising to reshape how goods and services reach customers.

Draven McConville, founder of job management software Klipboard and a veteran of the field service management space, has watched these technologies evolve from science fiction to business reality. “We’re at an inflection point,” McConville says. “The technology is here.

The question now is how quickly businesses can adapt their operations to take advantage of it.”

The Current State of Last Mile Robotics

Autonomous delivery robots are already navigating sidewalks in dozens of cities worldwide, with more coverage announced regularly. And it’s not just in the US. Food drone deliveries have recently started in Ireland. Companies like Starship Technologies have completed millions of autonomous deliveries, primarily for food and small parcels. Drones are expanding beyond consumer deliveries to medical supplies, spare parts, and emergency equipment as regulatory approvals gradually broaden.

Autonomous vehicles present a more complex challenge. While fully autonomous passenger vehicles remain years away, purpose-built delivery vehicles operating on defined routes are closer to reality, particularly in industrial and commercial settings.

Field Service is a Different Challenge

Field service operations face unique challenges that differentiate them from standard delivery logistics. A technician doesn’t just drop off a package. They have to diagnose problems, perform repairs, interact with customers, and adapt to unpredictable situations.

According to McConville, field service has always been about problem-solving in real time. “You can’t fully automate empathy or the ability to think on your feet when a job doesn’t go according to plan,” he says.

The value lies in augmentation rather than replacement by using technology to make human technicians more efficient, better informed, and more productive.

Practical Applications

Several near-term applications show promise:

• Autonomous inventory delivery. Service vans could be automatically restocked overnight, ensuring technicians have the right parts before they start their routes.
• Drone-based site assessment. Before a technician arrives, a drone could survey a site, capturing images and data that help diagnose issues. This is particularly valuable for rooftop equipment, large facilities, or hazardous locations.
• Robot-assisted repairs. For confined spaces or hazardous environments, robots could perform physical work under remote supervision by skilled technicians.
• Predictive routing. AI-powered systems analyzing traffic, weather, and job complexity can dynamically optimize technician routes throughout the day.

Integration is a Challenge

Technology adoption isn’t just about acquiring robots or drones. The real challenge lies in integration with existing systems and workflows, some of which are far from cutting-edge.

McConville is a proponent of technology creating value by seamlessly integrating into how people already work. “The same principle applies to robotics and AI. If it creates more complexity than it solves, it won’t get adopted.”

Field service management software needs to evolve to coordinate both human and robotic resources. The software layer becomes the orchestration engine, determining the optimal combination of human technicians, autonomous vehicles, drones, and remote diagnostics for each job.

Data: The Foundation of Autonomous Operations

Autonomous systems are only as good as the data that drives them. Fleet management platforms tracking vehicle locations and field service platforms capturing job details provide the historical data that enables predictive AI.

“The companies winning in this space will be those that have been collecting and analyzing operational data for years,” McConville says. “That data becomes the training ground for the AI systems that will power autonomous operations.”

The shift toward automation raises inevitable questions about employment. The more likely scenario involves role evolution rather than elimination. Technicians become supervisors of robotic systems, handling complex problems that require human judgment while routine tasks get automated.

The saying goes that you won’t be replaced by AI, but you will be replaced by someone using AI. And the same principle applies in the supply chain. Those technicians who embrace technology and develop hybrid skills will be the most valuable, according to McConville. “The future belongs to people who can work alongside AI and robotics, not compete against them.”

Change is Coming Faster Than You Think

Many industry observers underestimate how quickly these technologies will scale. The pattern follows other technology adoptions: slow initial progress, followed by rapid acceleration once technical and regulatory barriers fall.

Companies don’t need to deploy autonomous fleets tomorrow, but they should be preparing:

• Audit your data infrastructure. Start organizing route history, job details, and performance metrics in formats that can feed AI systems.
• Identify automation candidates. Map your workflows and identify repetitive, predictable tasks that could be automated.
• Engage with technology providers. Build relationships with companies developing autonomous solutions. Participate in pilots.
• Invest in workforce development. Start training programs that prepare technicians for technology-assisted work.

McConville says the playing field is being reset. “Size and legacy won’t protect companies that fail to adapt. Smaller operators who embrace these technologies can compete with much larger rivals. We’re entering a period where operational excellence will be defined by how well you orchestrate both human and machine resources.”