While most corporate sales planning personnel are overwhelmed by weekly market dynamics and competitor reports, Hotai Motor has empowered its talent through AI, reducing data organization time by more than 50%. Transitioning from a traditional automobile distributor to a MaaS (Mobility as a Service) provider, Hotai Motor's key battle, with the assistance of GAIA Information Technology, has not only avoided security risks but also truly achieved cost reduction and efficiency enhancement.
Before the weekly business meetings, it is often the most tense time for the planning units. Everyone needs to analyze based on the latest sales status reports, competitor dynamics, and market changes. In the past, these tedious data collection and report writing tasks always relied on a large amount of manual effort .
However, Hotai Motor's partners can now face these complex data points with relative ease.
By introducing Gemini Enterprise, Google Cloud’s agent development and orchestration platform, Hotai Motor employees can now use AI to assist in organizing relevant data and conducting multi-angle market analysis. Partners are no longer data-organizing machines buried in numbers; they can invest more effort and time into strategic thinking, creative brainstorming, and high-value decision-making.
This change can significantly reduce the data organization time for planning units.
How did Hotai Motor, transitioning from a traditional automobile distributor to a mobility service company, combine AI to create benefits, step by step? And in this wave of AI transformation, how did GAIA Information Technology, playing the role of a key "running mate," assist the enterprise in balancing security and efficiency to build a truly trusted service?
Breaking Data Silos and Enabling Dialogue Between Talent and AI: Hotai Motor's "AI Empowerment Plan for All"
In addition to being the general agent for vehicle brands Toyota, Lexus, and Hino, the Hotai Group also owns multiple business entities such as iRent and yoxi. In the past, the biggest challenge was that the information systems of various subsidiaries were built at different times, had different architectures, and unified data formats were lacking.
In response, Hotai Motor established a group data center to connect these scattered "data silos," transforming them into data assets with business insight value. These data assets are then used for analysis. With a rich, complete, and powerful data center, the company is better equipped to promote "AI empowerment" for all as the AI wave arrives. Through internal "AI self-research" activities, employees are encouraged to start applying AI in their work, and monthly cross-departmental sharing allows successful cases to spread horizontally within the organization from points to lines and planes. Furthermore, AI is combined with data assets to improve various on-site operation processes. Initial trials were conducted at some locations with successful results, and there are plans to use Gemini Enterprise and Google Cloud's Vertex AI platform to build AI agents. After integrating with internal systems, AI applications will gradually extend to first-line on-site operations.
For example, in the past, when technicians encountered complex and difficult maintenance cases, searching for information alone was time-consuming and laborious. Now, through AI tools to organize technical service documents and vehicle maintenance manuals, technicians can quickly understand the causes of problems and possible countermeasures, significantly shortening the time for data search.
This service is expected to establish AI agents through Gemini Enterprise and Vertex AI, integrate with internal service systems, and be promoted to first-line on-site operations. Additionally, with AI assistance, the legal department can quickly identify differences between contract templates and actual signed content and list areas for adjustment. This not only reduces the probability of errors in previous manual comparisons but also increases the review speed of such contracts by nearly 30%.
As of now, more than 70% of Hotai Motor's employees use Gemini Enterprise in their daily work.
Assisting Hotai Motor in Introducing Gemini Enterprise! GAIA Information Technology's Oliver Wu: "Trust" is the New Doctrine in the AI Era
"AI has given hackers' attack power a 'qualitative leap,' and corporate trust is facing internal and external attacks." Oliver Wu, founder and CEO of GAIA Information Technology, observed that the challenge currently facing enterprises is the desire to use AI to accelerate team processes, but because data is highly sensitive, most explicitly prohibit the use of public AI services like ChatGPT.
This has led to the rise of demand for "Closed AI." Because what enterprises need is not an all-knowing but publicly available robot on the internet, but an internal exclusive brain that can balance productivity and information security. It must be able to assist in analyzing internal Excel data reports and technical documents within the enterprise environment, while possessing strict authority control and data segmentation to ensure that data is not leaked or used for external model training.
This is precisely why Hotai Motor introduced Gemini Enterprise. To help ensure that data assets only run within a dedicated environment and to solve the data risks present in traditional open AI platforms, Hotai Motor chose an enterprise-grade solution that provides privacy protection. Through such a layout, an environment is established that can both enjoy the computing power of generative AI and ensure data sovereignty.
The Era of AI Agents: AI Learns to "Take Initiative in Handling Tasks," and Enterprises Further Strengthen Security Controls
Moving through 2025, AI is no longer just a "one question, one answer" assistant. GAIA Information Technology points out that the new generation of AI must be an agent capable of understanding complex intentions and proactively decomposing tasks.
Hotai Motor has already begun deployment, planning multiple AI agents to assist employees in their daily operations based on business needs. Taking the data agent as an example, in the past, if managers needed cross-departmental data analysis, they often had to rely on IT personnel to help retrieve data and develop reports, a process that was time-consuming and laborious. In the future, through agents, colleagues will be able to more easily obtain data scattered across different systems; AI can not only present numbers but also provide appropriate suggestions combined with commercial backgrounds, allowing teams to more quickly gain insight into data meaning and make precise decisions.
However, when AI starts to take initiative in handling tasks for humans, the system's authority management and logical judgment must be more rigorous. GAIA Information Technology reminds that introducing AI is not just about deploying agents, but also a long-term project involving "process transformation and architecture planning." It is recommended that enterprises adopt a "phased introduction" strategy to reduce the cultural impact brought by new technology; and rather than pursuing a "large and comprehensive" system from the start, it is better to first verify the effects of small-scale implementation, and after confirming that efficiency can be effectively improved, gradually promote it to other business entities.
Looking to the future, through Google Cloud's powerful computing power and model resources, Hotai Motor is committed to creating brand new service experiences that were impossible to achieve in the past and are closer to needs. In the process, GAIA Information Technology will continue to play the role of a key technical consultant, ensuring that information security evolves from a simple cost into the foundation of enterprise trust and sustainable competitiveness.
This transformation chapter opened by Hotai Motor and GAIA Information Technology in collaboration with Google Cloud shows that in the AI era, only by balancing innovation and trust can one truly lead successful digital transformation.
GCP Premier Partner | GAIA Information Technology
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