China Securities Journal Interview with Gansha Wu: 99 Points Equals Zero in Autonomous Driving, Aiming to Deploy 1 Million AI Drivers Worldwide

2026-06-22

The following is the content of

an interview with Gansha Wu, Co-founder, Chairman and CEO of UISEE, by China

Securities Journal.

Reporters: Zheng Cuiying, Yang Wanyu, Li

Yuning

On the apron of Urumqi Tianshan

International Airport, a fleet of 40 Autonomous Electric Tractors and 20 Autonomous Shuttle Buses operates in an orderly manner,

transporting luggage, cargo, and passengers, maintaining stable routine

operation even under extreme weather conditions like rain, snow, and

strong winds.

Recently, this L4 autonomous

driving fleet built by UISEE successfully reached the

milestone of 1 million kilometers of commercial operation,

marking a breakthrough where domestic airport unmanned operation technology has

overcome extreme environmental constraints and entered a new stage of large-scale

commercialization, replicability, routine operation, and commercial

implementation.

As a provider of L4 autonomous

driving solutions, UISEE listed on the Hong Kong Stock Exchange (HKEX) on May 20, becoming the "first stock of full-scenario L4

autonomous driving". According to Frost & Sullivan statistics, in 2025, UISEE held a 90.5% market share in the L4

commercial vehicle autonomous driving market for airport scenarios in Greater

China, and a 31.7% market share in factory area scenarios,

ranking first in both industry segments.

Over its ten-year history, the

company has deployed over 1,200 sets of L4 autonomous driving vehicles

and supporting kits globally, with a cumulative total true

driverless mileage exceeding 9.2 million kilometers.

Its business covers 249 industry clients across 6

countries. Beyond 17 domestic airports, UISEE's vehicles are also

visible in overseas benchmark airports like Singapore Changi Airport and Hamad International Airport in Qatar.

At the listing ceremony, Gansha

Wu, Co-founder, Chairman and CEO of UISEE, outlined a blueprint for global

expansion, with the company planning to expand its business footprint to 50

countries worldwide within the next three years. However, before this

expansion, a mature, reliable operation model and technological accumulation

remain the core of the company's development.

Recently, in an interview with China

Securities Journal at UISEE's R&D center in Beijing's Fangshan

district, Gansha Wu elaborated on the company's technological "moat",

which started from limited semi-closed scenarios and gradually extended to open

roads. He also disclosed the company's business model iteration plan:

transitioning from autonomous vehicle sales and complete solution delivery to

ultimately an AI Driver subscription service, with a future

goal of deploying millions of AI Drivers to build a new

industrial profit model.

<h2>"99 Points

Equals Zero" </h2>

<h3>Tackling the

"Hard Nut" of Airport Autonomous Driving </h3>

In the rapidly developing

autonomous driving industry, a mindset of "prioritizing testing over

implementation" is common. However, Gansha Wu believes "99

points equals zero" is an iron law of the industry. He views

autonomous driving as a protracted war, where competition is not about

short-term technological ceilings but the long-term survival baseline of a

company. Semi-closed airport scenarios serve as a "high-difficulty

examination hall" testing the full-chain capabilities of technology,

operation, and safety.

Unlike pure closed scenarios like

warehouses, which are completely isolated with all equipment interconnected,

airports are typical semi-open environments. Autonomous vehicles must share

apron road rights with civil aviation aircraft, various special operation

vehicles, and manually driven vehicles. The interweaving of pedestrian,

vehicle, and aircraft traffic flows leaves almost zero margin for safety error.

Gansha Wu explained that

achieving unmanned airport operations requires overcoming three major hurdles.

First is the safety standard, which prohibits any collision or risky behavior

throughout the process; any minor incident could directly impact aviation

operations. Second is the high-standard service timeliness; luggage transfer

and passenger shuttle services cannot delay flights due to unmanned equipment.

Third is all-weather high availability, where fleet availability must approach

100% infinitely even in extreme weather like rain, snow, dust, and low

temperatures.

Precisely because of these high

entry barriers, UISEE spent two years obtaining an airport

unmanned operation license and a full seven years to achieve large-scale

commercialization. The complete system honed in these high-difficulty

scenarios has become the company's core competitive advantage in developing

domestic and international airport markets.

Gansha Wu stated that airports

choose UISEE's solution primarily for three reasons: first, proven real-world

cases of large-scale implementation and stable operation at

airports; second, the industry reputation and endorsement formed by serving global

top-tier airport clients; and third, a standardized,

replicable full-process system covering quality control,

certification, data compliance, and operation maintenance services.

The prospectus shows continuous

revenue growth for the company. From 2023 to 2025, UISEE's operating revenue

grew from 161 million yuan to 328 million yuan,

with a three-year compound annual growth rate of 42.7%. Gross

margin improved from 48.8% to 51.1%, while

adjusted net loss narrowed from 181 million yuan to 169

million yuan, showing a trend of decreasing losses. The company

currently has an order backlog exceeding 500 million yuan,

with an additional 95.2 million yuan in new orders scheduled

for concentrated delivery between 2026 and 2027.

Sustained high R&D investment

is the core reason for the company's current phase of losses. The prospectus

shows that in 2023, 2024, and 2025, R&D expenses were 184 million

yuan, 196 million yuan, and 234 million yuan respectively, accounting for 114%, 74%, and 71% of revenue, continuously pressuring the profit side.

In Gansha Wu's view, high R&D

investment is an inevitable choice for the company's survival and development.

"An autonomous driving system has hundreds of modules, each of which must

be safe, reliable, and efficient. It's like a barrel made of a hundred wooden

staves—any short board will cause the entire solution to fail."

While a simple

demonstration-level unmanned fleet in the industry can be deployed with an

annual investment of around 20 million yuan, large-scale commercial

unmanned operation requires a decade of continuous refinement. With no

mature off-the-shelf solutions for core components, underlying algorithms, or

the Vehicle AI Brain and Cloud Brain systems,

the company had to choose full-stack self-developed technology. The team size expanded from dozens to around four hundred people,

and combined costs for computing power, data, patents, and testing kept R&D

expenses high.

Currently, the company's

self-developed U-Drive® intelligent driving platform has

passed the ISO 26262 ASIL-D highest-level functional safety

certification and is evaluated as the only system globally that can both meet

the most stringent airport safety standards and withstand the test of China's

complex traffic scenarios. Furthermore, UISEE will allocate 40% of the funds raised from this IPO to continue investing in

core technology R&D, solidifying its long-term technological barriers.

<h2>Building a Data

Flywheel for Proprietary Scenarios </h2>

UISEE's target scenarios extend

beyond airports and factory areas; the goal is to create a universal

autonomous driving platform.

Gansha Wu stated, "We are

currently looking at nine major scenarios, with passenger vehicles as one major category and commercial vehicles as another.

Within commercial vehicles, there are five sub-scenarios: airports, factory

parks, mines, ports, and agriculture/animal husbandry. Additionally, there are

three major open scenarios: buses, logistics, and sanitation."

In the passenger vehicle domain,

as the autonomous driving industry heats up, competition is intensifying. The

open-road passenger vehicle track is crowded with giants, with overseas

companies like Waymo and Tesla, and domestic companies like Baidu and Huawei

all increasing their investments.

Facing the entry of giants,

Gansha Wu believes that close benchmarking against leading overseas technology

can open up new avenues for technological iteration for domestic autonomous

driving companies. Even if leading companies currently have a technological

advantage, in the field of autonomous driving, the technological gap between

mid-tier and leading companies is only 6-8 months.

Furthermore, disruptive breakthroughs via new technological routes could

reshape the industry landscape at any time.

Data is the nourishment for

improving autonomous driving model capabilities. Gansha Wu noted that compared

to the homogenized data from open roads, UISEE relies on its unique operation

scenarios in airports and factory areas to build its core

"moat"—establishing a data flywheel for proprietary scenarios.

Data on vehicle flows, equipment, and operational processes in airports and

industrial parks possess exclusive attributes. The massive amounts of

differentiated scenario data accumulated through long-term commercial

operation continuously feed back into AI model iteration, forming a

positive cycle where more operation leads to richer data, more precise

algorithms, and stronger scenario adaptation capabilities.

Beyond proprietary data barriers,

UISEE is also building a "moat" in its service model. By providing a

full-process integrated solution, it incorporates business workflows like

autonomous driving hardware, automatic charging, automatic loading/unloading,

and automatic trailer coupling into the solution. "Once technology is

integrated into business processes, forming a solution, it gains exclusive

advantages," Gansha Wu said. When a client's entire operation dispatch and

operation maintenance management system is built on the UISEE Cloud

Brain platform, it significantly increases customer stickiness, as

switching suppliers would entail enormous transition costs.

Currently, relying on the

autonomous driving operation platform composed of the Vehicle AI Brain and Cloud Brain, UISEE achieves three-layer unification of

hardware, software, and AI models, creating a universal autonomous driving

foundation. Gansha Wu believes technological implementation should follow a

path "from difficult to easy" and "from

semi-closed scenarios to open scenarios," prioritizing the

conquest of the highest-standard airport scenarios before extending to factory

areas, parks, and open roads.

<h2>Future Adoption of

Subscription Model </h2>

<h3>Targeting 1 Million

AI Drivers </h3>

UISEE is promoting a business

model iteration. With core technology and a mature operation model in place, a subscription

model transforms hardware delivery into long-term, recurring service

revenue. This will help the company expand its profit margins and dilute

operation and maintenance costs through economies of scale.

Gansha Wu explained that one-time

hardware sales come with high pricing, creating high procurement barriers for

customers and limiting market expansion potential. In contrast, the subscription

model essentially converts traditional vehicle labor costs, management

fees, and operation maintenance expenses into standardized service fees. It

also gives rise to three flexible payment models: monthly subscription,

pay-per-driving-hour, and pay-per-mileage. In the future, the company will

deeply adapt with global mainstream commercial vehicle and passenger

vehicle manufacturers. The AI Driver subscription service can be quickly integrated into various vehicle models, with vehicles connected

to the cloud management platform upon leaving the factory, allowing customers

to purchase AI driving services on demand.

"We hope to achieve 100,000

AI Drivers within three to five years, and 1 million AI

Drivers in the future," Gansha Wu said.

Gansha Wu indicated that UISEE

has already achieved positive unit economics (UE) in some

projects with leading clients, reaching the first stage of its development

goals. The second-stage goal is to achieve overall breakeven, which the company

is steadily progressing towards.

Standing at the ten-year

development milestone, Gansha Wu divides the company's development into two

decades. The core goal of the first decade was "securing the

baseline, seeking survival," overcoming multiple challenges

including scenario implementation, technological safety, commercial viability,

and establishing leadership in niche segments. The strategic focus of the

second decade shifts to "competing for the ceiling, expanding

globally," with the core goal being an order-of-magnitude leap in

the scale of AI Drivers.

Gansha Wu stated that there is a

global, universal demand for replacing high-intensity, harsh-environment manual

positions in scenarios like airports, factory areas, and logistics worldwide. Frost

& Sullivan data indicates that the global and Greater China

markets for L4 autonomous driving in commercial vehicles are in a period of

rapid growth. The Greater China market size is expected to grow from 5.8

billion yuan in 2025 to 53.5 billion yuan in 2030,

with a compound annual growth rate of 52.1% from 2026 to 2030.

Additionally, Advanced Driver-Assistance Systems (ADAS) for passenger vehicles

are widely popular globally, providing a potential market for L2+

Autonomous Driving Solution kits.