Operational Excellence (OPEX) Daily Briefing – Friday, December 26, 2025: AI Moves Into Physical Operations: Automated Robotaxi Charging Cuts Logistics Operating Costs.

Điểm Tin Operational Excellence (OPEX) Mỗi Ngày – Thứ Sáu, Ngày 26/12/2025: AI Đang “Đụng Tay” Vào Vận Hành Vật Lý: Tự Động Hóa Sạc Robotaxi Giúp Cắt Giảm Mạnh Chi Phí Logistics.

Welcome to my unique weekday article for the paid subscriber-only edition.

Operational Excellence (OPEX) Daily Briefing – issued on weekdays (Monday to Friday).

Điểm tin Operational Excellence (OPEX) hằng ngày (phát hành các ngày thứ Hai đến thứ Sáu).

This is the bilingual post in English and Vietnamese. Vietnamese is below.

Đây là bài viết song ngữ Anh-Việt. Tiếng Việt ở bên dưới.

English

PART 1 – OFFICIAL INFORMATION

In the final period of 2025, the robotaxi and automated logistics sector in the United States has recorded a clear increase in AI automation initiatives directly embedded into physical operations, particularly in areas that had previously relied heavily on manual labor. One of the most frequently highlighted areas is the automation of electric vehicle charging processes at robotaxi depots, which is widely regarded as a cost, labor, and scalability bottleneck within autonomous fleet operating models.

According to information disclosed by Rocsys in recent corporate updates, the company is focusing on developing AI-enabled autonomous charging robot solutions, with the objective of fully eliminating manual intervention in the charging process for robotaxi fleets and continuously operating logistics vehicles. Rocsys has stated that its strategic focus is primarily on the U.S. market, while also expanding toward other major markets such as China, where large-scale autonomous vehicle deployments are actively progressing.

Based on the company’s own descriptions, electric vehicle charging in robotaxi operations is not merely a technical challenge, but a core operational problem. In traditional depot models, plugging and unplugging chargers, monitoring vehicle status, and handling exceptions still require direct human labor, resulting in high labor costs, operational error risks, and system delays. Rocsys emphasizes that when fleets scale to hundreds or thousands of vehicles, manual charging models become a structural limitation, directly reducing the efficiency of the entire robotaxi system.

According to operational analysis data shared by Rocsys, depot-related costs—including labor, vehicle waiting time for charging, process deviations, and limited coordination capacity—represent a significant portion of total robotaxi operating costs. The company states that full automation of the charging process has the potential to reduce depot operating costs by approximately 30% to 70%, depending on fleet size, current automation maturity, and depot organization structure. Rocsys clarifies that these figures represent operational estimates rather than financial guarantees, and are intended to serve as indicators of potential efficiency gains.

From a technology perspective, Rocsys describes its solution as a combination of electromechanical robotics, computer vision, AI-based positioning recognition, and operational coordination software, enabling robots to automatically identify charging ports, precisely align with vehicles, and execute charging connections without human involvement. The system is designed to function in high-density depot environments, where accuracy, stability, and repeatability of operations are critical success factors.

Based on publicly released corporate information, Rocsys positions its solution as an operational automation layer, rather than a technology showcase. The emphasis is not on making robots “smarter”, but on standardizing charging workflows, reducing dependence on human labor, and enabling fleet scaling without exponential cost growth.

Within the U.S. market context, where many robotaxi projects are transitioning from pilot phases to commercial expansion, optimizing depot operating costs is increasingly viewed as a survival condition for achieving long-term economic viability. Industry analyses indicate that many operators are shifting their focus away from autonomous driving technology itself toward back-end operational logistics, including charging, maintenance, fleet coordination, and asset management. Rocsys argues that charging automation represents one of the most critical constraints that must be addressed.

According to its stated direction, Rocsys does not aim to replace existing infrastructure entirely, but instead focuses on integrating automation into current depots, allowing operators to upgrade operational capabilities incrementally, without causing major operational disruptions. This approach clearly reflects a broader trend in the United States, where AI automation solutions are increasingly evaluated based on real-world deployability, measurable operational impact, and direct cost reduction, rather than purely on technological sophistication.

The official information indicates that Rocsys is concentrating on solving a highly specific yet system-wide operational problem: reducing costs, lowering complexity, and improving scalability for robotaxi and automated logistics operating models. The integration of AI and robotics directly into the vehicle charging process reflects a broader U.S. trend, in which AI automation is shifting from software-centric applications into physical operations, becoming a structural component of high-technology service systems, rather than merely a supporting technology layer.