Amazon introduced a prototype set of AI enabled delivery glasses, described as hands free tools that guide routes, scan packages, and capture proof of delivery photos, aiming to reduce friction in last mile workflows while keeping drivers focused on the curb to doorstep path.
The company positioned the glasses as part of a broader operations refresh that also includes a new robotic cell, Blue Jay, and an agentic AI system, Project Eluna, which together promise faster sortation and fewer touch points from inbound bins to outbound loading.
What do Amazon’s AI driver glasses actually do?
The glasses, referred to as Amelia in demonstrations, pair a heads up display with cameras that activate when a vehicle is parked, then present turn by turn walking guidance, instant package verification, and photo capture for proof of delivery, all without a phone in hand or manual app tapping.
A compact controller embedded in a delivery vest supplies power with swappable batteries for shift length use, and includes an emergency button for high visibility escalation, while the roadmap highlights computer vision alerts for misdeliveries, pet detection for yard safety, and low light adaptation in future updates.
Did you know?
Amazon has deployed more than a million robots across hundreds of facilities, with reports indicating that robots assist in a significant share of deliveries, reflecting a decade-long shift toward human-robot collaboration.
How could Blue Jay change warehouse flow?
Blue Jay combines multiple robotic arms into a single workstation that picks, sorts, and consolidates items that previously required movement across separate cells, eliminating handoffs that add time and error, and freeing humans to supervise exceptions and value-added tasks rather than repetitive lifting.
The system is already being exercised at a South Carolina site. It is designed to handle a wide range of catalog items, with grippers and perception tuned for standard packaging formats, which could improve throughput in same-day and regional fulfillment centers once scaled.
What is Project Eluna’s role in operations?
Project Eluna presents an agent style AI that ingests real time facility telemetry, inventory positions, and staffing data, then answers natural language queries from managers while proposing actions that balance lanes, clear jams, and preempt bottlenecks before they slow outbound waves.
During the initial pilot at a Tennessee fulfillment center, Eluna is slated to assist holiday volumes by raising early warnings on sortation queues and suggesting targeted adjustments to labor allocation, dock timing, and shuttle routing, reducing dashboard switching and manual spreadsheet checks.
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Are jobs at risk from these systems?
Internal planning documents cited by external reports described a path in which automation could reduce future hiring needs, raising questions from labor advocates about how productivity gains are shared and how retraining keeps pace with the introduction of robotic cells and AI-powered oversight.
Amazon has stated that these tools augment rather than replace workers, emphasizing safety, career ladders in mechatronics and AI support roles, and seasonal hiring for peak periods.
At the same time, critics argue that unit economics will ultimately drive learner staffing as Blue Jay and Eluna mature across more sites.
What comes next for deployment and safety?
The glasses are being tested across multiple delivery service partners, with metrics focused on time saved, error rates, and incident reduction. The hardware stack includes a dedicated safety button, allowing drivers to call for help without a separate device quickly.
Blue Jay and Eluna are positioned for phased rollouts, contingent upon pilots meeting throughput and quality targets.
Governance is centered on incident reporting, ergonomic baselines, and fairness audits, ensuring that speed improvements do not increase musculoskeletal strain or widen performance gaps across teams.
Looking ahead, the company will face pressure to publish standardized safety and productivity data, expand worker training cohorts, and clarify how automation timelines align with hiring plans.
At the same time, customers will judge the value by fewer missed deliveries, more precise ETAs, and consistent service during seasonal peaks.
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