Gasgoo Munich- On February 11th, a new company was established in Beijing with a registered capital of 5 million yuan. In the automotive AI field, where spending as much as 100 million yuan is common, that amount barely covers one month’s R&D salary at a top company. However, the company, named BAIC Yuanjing Intelligent Technology, is fully controlled by BAIC BluePark, with Liu Guanqiao, marketing director of BAIC New Energy, serving as its legal representative.
Image source: Tenyancha app
The breakdown of Tianyan Che’s share ownership reveals a clear picture. Beiqi Yuanjing’s sole shareholder is Beijing New Energy Automobile Co., Ltd., the core automobile manufacturing entity of Beiqi Blue Park. That means this new business was not planned from the beginning as a financial strategy or an outside investment.
“Artificial intelligence basic software development” occupies an important position within its business scope. The automotive industry has already entered the deep waters of AI-driven innovation. L2 driver assistance is becoming the norm, smart cockpits are expanding into mainstream price points, and technological parity is reshaping the market landscape. At this critical moment, BAIC New Energy’s decision to launch a fully-funded technology division sends an unmistakable signal that BAIC is serious about AI.
BAIC BluePark accelerates
Beiqi Blue Park’s financial performance over the past two years has been disappointing.
According to the report for the first three quarters of 2025, the net loss was 3.426 billion yuan. As of the market close on February 12, 2026, the stock price was 8.08 yuan (down 3.81% from the past year), and the market capitalization was 51.4 billion yuan. Compared to BYD, Tesla, Li Auto, and NIO, BAIC BluePark’s product line certainly offers value. But when customers walk into a dealership, they inevitably ask whether the smart cockpit is fluid and whether the driver assistance actually works. In these respects, the brand lacks a memorable edge.
Previously, BAIC BluePark relied on third-party partnerships for intelligence, including sourcing ADAS solutions from suppliers, outsourcing cockpit systems, and sharing vehicle definition rights with partners. This model served in the early days of new energy vehicles, when combat was fought over range and specifications, and intelligence was just a bonus feature.
Image source: Arcfox
However, the logic of competition has changed since 2025. Fu Lifeng, executive vice president of the China Automobile Manufacturers Association, declared at the 2025 China Automotive Software Conference that the industry is accelerating the transition from “hardware-defined” vehicles to “software-defined” vehicles.
Consumers are no longer satisfied with cars that just drive. They ask if the car can be understood. That understanding comes not from simply piling up hardware specs, but from in-house development or tight integration.
Enter Beiqi Enkyo. Fully owned, staffed by core management from BAIC New Energy’s marketing department, and focused squarely on AI fundamental software, this structure sends a straightforward message. BAIC BluePark no longer wants to be a “patchwork player” in the intelligence field. The company intends to take control of its core technology into its own hands.
Can you utilize AI with 5 million yuan?
What does a registered capital of 5 million yuan actually mean in the field of automotive AI research and development? In major companies, the total compensation for algorithm engineers routinely reaches several million yuan, while building an autonomous driving data collection fleet easily exceeds 10 million yuan. Strictly speaking, Beiqi Enjing’s capital only covers a few months’ worth of salaries and a few servers.
But that’s not the only way to do the calculations.
Breaking down the scope of its business, Beiqi Enjing’s direction appears to be extremely realistic. It does not address capital-intensive, long-cycle “tough challenges” such as advanced autonomous driving or cockpits for large models. Instead, three core cores – AI basic software development, IoT application services, and automotive component R&D – work together to address technology gaps that can be implemented in the short term and reused in the medium term.
Let’s start with AI software. Rather than building an ADAS chip or end-to-end algorithm from scratch, the most practical entry point is to focus on three specific scenarios: In addition to existing L2 functionality, it adjusts driver assistance to China’s road conditions. Predict component life from real-time data using AI diagnostics. This will reduce maintenance costs and strengthen the after-sales service system. These are not disruptive innovations, but tangible experience upgrades that users experience every day.
Image source: BAIC BluePark
The value of IoT application services lies in ending the isolation of the BAIC model. Remote phone control, car-to-home connectivity, and real-time status updates have become the norm at major startups, and BAIC needs to catch up. Meanwhile, the company’s auto parts research and development targets hardware such as smart sensors and in-vehicle controllers, ensuring synergies between software and hardware and gradually reducing dependence on external suppliers.
The cleverness of this combination is that it allows BAIC BluePark to close the experience gap with industry leaders without spending astronomical amounts of money on research and development. The wholly owned structure also keeps the decision-making chain as short as possible, avoiding the internal friction over differing strategies that plagues joint ventures.
But the drawbacks are equally obvious. Beyond limited capital, a bigger concern is human resources. The Ministry of Human Resources and Social Security predicts that by the end of 2025, the intelligent manufacturing sector will need 9 million professionals, leaving a gap of 4.5 million. Talent with dual expertise in AI and automotive engineering is the subject of a fierce tug-of-war across the industry.
Given BAIC BluePark’s weak track record in intelligence and lack of competitive pay and technology platform resources, poaching the right talent from the gravitational pull of Tesla, BYD, and even Huawei is a more fundamental challenge than choosing a technology roadmap.
Synopsis: A must-win return match
BAIC Yuanjing is not the first in the industry. FAW established Qiyi Technology to focus on the integration of low-altitude economy and AI, while Geely established Qianli Technology with the aim of commercializing autonomous driving. By comparison, BAIC’s layout is more grounded, not chasing the flying car hype or betting on concepts like the Metaverse. It’s just catching up on the basics and developing the parts properly.
This “inward-looking” strategy is at least moving in the right direction.
But going in the right direction doesn’t guarantee success. The biggest uncertainty for BAIC Blue Park is not whether it chose the wrong technology roadmap, but whether it can reconcile the contradiction between profitability pressures and the need for long-term investment. Will a serially loss-making company be able to withstand the pressure of short-term financial reporting to continue funding this AI venture?
But this is a battle that BAIC Blue Park has to fight. The window of opportunity in the information race is narrowing, and the technological barriers for industry leaders are getting higher and higher. BAIC BluePark must deliver compelling internal innovation and competitive products to win this turnaround.
