When Coordination Meets Intelligence: Real‑time Policies for Maximizing Throughput in Autonomous Forklift Operations

With advancements in artificial intelligence (AI), Internet of Things (IoT) and sensor fusion technologies, such as 3D vision and Light Detection and Ranging (LiDAR) systems, the global autonomous forklift market is projected to grow from $2.73 billion in 2025 to $5.07 billion in 2032 (MarketsandMarkets, 2025).

With the surge in e‑commerce and rising expectations for flexible throughput and fast delivery, intelligent fleet orchestration has emerged as a strategy to synchronize forklift operations with the broader warehouse workflow. By leveraging IoT connectivity and AI‑driven predictive analytics, forklift fleets are evolving from isolated workhorses into coordinated, efficient contributors to end‑to‑end material flow. In particular, real‑time fleet coordination policies can minimize fleet downtime and enhance throughput performance (De Koster et al., 2025).

Intelligent fleets can be categorized by level of intelligence: AI‑augmented, fully autonomous and hybrid

• AI‑Augmented Human‑Operated Fleets: Many warehouses still rely on human operators driving forklifts, but now those vehicles can be outfitted with IoT sensors and assistive technology. In this model, a central system analyzes data from each forklift and helps guide decisions. It dispatches tasks to drivers and flags maintenance needs or unsafe driving in real time. The forklifts remain human‑controlled, but an AI “brain” optimizes their work. This approach is relatively easy to adopt—existing trucks can be retrofitted with sensors—and it boosts productivity while leveraging human flexibility. Workers feel empowered rather than replaced, which eases the adoption of the technology…