--- title: "Two workers, 3,000 mu of cotton: China's AI 'super farm' in action" date: 2026-09-30 category: AI in Action site: NeuroAI canonical: https://neuroai.site/a/na-app-xag-super-farm language: en --- # Two workers, 3,000 mu of cotton: China's AI 'super farm' in action > At XAG's Guangzhou and Xinjiang "super farms", drones, BeiDou-guided tractors and an AI 'field brain' have cut water, pesticide and labor costs — a concrete case of AI落地 (AI deployed) in agriculture. At 6 a.m., no workers are standing in the paddy field — just a drone lifting off a rooftop pad, sweeping 300 mu (about 20 hectares) of rice in 30 minutes. The "digital farm manager" has already started the day. This is not a pilot video. It is XAG's operational **超级农场 (super farm)** in Huangpu, Guangzhou, reported by People's Daily in April 2026 — and it shows what AI deployed in agriculture actually looks like when the demos end. ## The field brain, not the robot The headline is not one machine. It is a loop. Drones, BeiDou-guided tractors, and IoT sensors feed a central AI the farm calls its "field brain." - A drone seeds nearly **300 mu (≈20 ha) in 30 minutes** at 8 m/s, carrying close to 80 kg of seed — up to 50× the speed of manual sowing. - **北斗 (BeiDou)**-guided tractors prepare land with an error of no more than 2.5 cm. - Soil sensors, weather stations, and cameras upload readings every 15 minutes; the AI turns temperature, humidity, light, and fertility into irrigation and fertilization advice. ## The numbers farms actually care about Across the Guangzhou super farm's last full cycle, XAG's operations manager told People's Daily the system: - cut **water and electricity cost per mu by 47%** - cut **pesticide use by 30%** - raised **fertilizer efficiency by 40%** During a rice-blast outbreak, the AI flagged zones of mild infection where reduced dosing was enough — saving more than **10,000 yuan (≈ US$1,400)** in pesticide on its own. AI-planned transplanting routes also lifted land use per mu by 15%. The Xinjiang "super cotton field" is the sharper example: **two employees manage 3,000 mu (≈200 hectares)**, with per-mu yield 16% above conventional farming and overall cost 22.89% lower. Year-round, the farm needs only three technical staff. ## From drone to robot ecosystem On 6 July 2026, XAG held its Agricultural Robot Conference in Guangzhou and moved beyond standalone drones into an autonomous workflow (reported by Pandaily and the Guangzhou development-zone government): - **X Series drone** with the SuperX 5 Apex controller (2× compute) and a 4D imaging radar plus vertical radar; power-line detection above 90%. - **XA1 docking station** — millimeter-level auto-docking, 10,000 takeoff-landing cycles, automatic charging and refilling. - **LM1 smart liquid-mixing unit** — handles 8 liquid sources, 60 L/min fill, one-click self-cleaning. - **B18630 smart flash battery** — 2.5 minutes for a quick charge, 3.5 minutes full, ~4,000 charge cycles. - **RM80 unmanned mower** — 143 kg, all-aluminum, climbs 30% slopes, covers 0.33–0.53 ha/h in orchards. XAG is also a business: the company reported 2025 revenue above **1.166 billion yuan (≈ US$164 million)**, with overseas sales of **419 million yuan (≈ US$59 million)**, up 13% year-on-year, about 36% of total revenue, across nearly 70 countries (AgroSpectrum). ## Why this is the real "AI落地" story Healthcare and education get the headlines, but agriculture is where autonomous AI has the clearest ROI in China: labor shortage, thin margins, and huge acreage. The gain is not "cool robots" — it is fewer workers covering more land at lower input cost, with the AI doing the boring, repetitive sensing and spraying. ## Honest limitations - The Guangzhou and Xinjiang savings (47% water/electricity, 30% pesticide, 40% fertilizer; 16% yield, 22.89% cost in Xinjiang) are reported by **XAG's own farm manager to People's Daily** — they describe XAG demonstration "super farms," not a randomized multi-farm study. - XAG's 2025 revenue and overseas share are **company disclosures** (AgroSpectrum), not independently audited by us. - Product specs (B18630 3.5-min charge, 4,000 cycles, 90% line detection) are **XAG launch claims**; we found no independent lab test. - This covers one company's ecosystem; it does not compare DJI Agras or other Chinese agtech vendors. ## What readers can do now - **Run one task's ROI**: if you farm or advise farms in China, price a single task — spraying or seeding — with a drone + 北斗 (BeiDou) setup versus manual labor for one season. - **Demand multi-farm data**: policymakers and NGOs should visit a demo super farm but require multi-season, multi-farm yield data before scaling any subsidy. - **Plan the labor transition**: automation displaces the 10–15 workers once needed per 300 mu — pair deployment with retraining, not just replacement. --- Published by NeuroAI (https://neuroai.site/) — https://neuroai.site/a/na-app-xag-super-farm Free to quote with attribution and a link to the original.