The evolution of the research and academic services sector offers a revealing lens on the digital transformation of China's knowledge-intensive service industries. In this process, one question stands out: how can intelligent technologies be deeply embedded in organisational operations, rather than remaining at a superficial level?
Recently, a paper published in the Journal of Economic Development, Innovation and Policy examined this question through the case of AiScholar, one of China's leading research and academic service platforms. The study systematically analysed AiScholar's intelligent transformation journey from its founding in 2014 to the present.
The paper identifies a clear three-stage trajectory: from process digitalisation, to platform digitisation, and then to intelligent ecosystem enablement. According to the researchers, what sustained this progression was not only increasing investment in technology, but also an adaptive mechanism in which technological implementation and organisational evolution advanced in parallel. In other words, AiScholar was not simply upgrading its systems; it was also reshaping its organisation, workflows and modes of collaboration.
From 0 to 1: Starting with Operational Pain Points
In 2014, China's research and academic services industry was in a period of rapid growth, yet its service model remained relatively traditional. Academic conference organisation, paper submission support, journal selection and liaison all relied heavily on manual operations and offline communication. Low efficiency, limited transparency and poor process traceability were common pain points for researchers and institutions alike.
At that time, AiScholar's parent company, Guangzhou KEO Information Technology Co., Ltd. (hereafter referred to as KEO), identified this structural opportunity and chose to approach it from the technology side.
Rather than competing in an already crowded market, KEO set out to reshape research and academic service workflows through technology. In 2015, it launched the AEIC Academic Exchange Information Center brand, becoming one of the first platforms in China to digitalise the entire academic conference management process, including registration, payment, agenda generation and notification delivery.
At this stage, the core logic was to replace traditional manual operations with standardised digital systems. According to the study, by 2018 the AEIC Academic Exchange Information Center had supported more than 100 international academic conferences and served over 100,000 research users. This phase not only helped the platform build its early user base, but more importantly marked a critical step in moving research services from experience-led operations to online process management.
As an enterprise deeply engaged in research and academic services as well as technological innovation, KEO has consistently upheld its mission of serving as a connector within the research community. Driven by technological advancement and service innovation, the company has built a one-stop service platform spanning academic exchange, research tools, and end-to-end publication support.
From 1 to N: Building a Trusted Platform Ecosystem
The gains brought by early digitalisation also gave rise to new challenges. As the business expanded, data silos between systems became increasingly apparent. Conferences, submissions and peer review remained disconnected, while decision-making still relied heavily on individual experience.
External pressures were also mounting. On the one hand, universities and journal publishers were demanding stronger data connectivity and greater workflow automation. On the other hand, the market saw the rise of numerous standardised conference SaaS tools, shifting competition from simply having a system to whether that system could truly enable collaboration and seamless data flow.
In 2019, AiScholar completed a major brand strategy upgrade, marking the start of its digitally driven phase. The key breakthrough was a transition from standalone tools to an integrated platform model, enabling data connectivity and modular workflows through platform-based restructuring.
Yet the technological shift was only part of the story. The study points out that the deeper challenge at this stage was the restructuring of user relationships: how to transform client relationships once built largely on personal connections into long-term trust in the platform's professional capabilities and service reliability. To address this, AiScholar introduced its "Four Online" strategy, in which "employees online" and "customers online" played a central role in building a new form of trust.
In practice, the platform made service processes more transparent and standardised. For example, it established a real-time service rating mechanism, ensuring that every service interaction became a touchpoint for building trust. As one company executive noted in an interview, AiScholar was moving "from people driving processes to processes driving people, with data empowering people".
By 2024, the platform's system stability had reached 97%, while it had also developed innovative features such as AI-assisted peer review and intelligent journal matching. This marked a shift in its service model from resource integration to value creation. At this stage, AiScholar had evolved beyond a functional platform into a research service ecosystem centred on trusted service and the continuous accumulation of user confidence.
In recent years, supported by its proprietary AI technologies and extensive research data resources, KEO has launched a series of innovative products, including an end-to-end academic conference SaaS system, an intelligent journal big-data matching system and the AiReviewer intelligent reviewer platform. With more than 100 intellectual property assets, the company has steadily developed into a leading player in the industry.
A New Phase: Building an Intelligent Service Ecosystem
In 2025, generative AI, represented by large models, entered a period of rapid growth, bringing fresh change to the research services industry. The focus of competition has shifted from tool-based functionality to the ability to integrate AI deeply into real research scenarios.
In response, AiScholar upgraded its "AI for Science" service vision and launched the AI Research Workspace, integrating AI capabilities deeply into research workflows. The platform brings together modules for topic selection, literature retrieval, experimental design, data analysis and paper writing, creating an intelligent augmentation system that supports the full research process and delivers improvements in both efficiency and user experience.
The deeper application of AI has also introduced new organisational questions: how should people and AI work together, and where should the boundaries of each be defined? To address this, AiScholar has carried out a series of structural initiatives. These include establishing an academic committee led by academicians and domain experts, as well as co-founding joint industry-university laboratories with institutions such as Southern University of Science and Technology and Chengdu University of Information Technology, in order to validate and continuously optimise AI applications through collaborative innovation.
At the same time, the team has explored human-AI collaboration in real business scenarios through a dual-track mechanism combining "AI-based technical checks + manual review". In this model, AI handles standardised, high-frequency tasks such as academic integrity checks, while human experts focus on non-standard requests and professional evaluation. The core principle is clear: the value of AI lies not in replacing people, but in freeing them to focus on more creative and higher-value work.
The results of this intelligent transformation are now clearly reflected in market performance. To date, the AiScholar platform has supported more than 5,600 international academic conferences, served over 3 million research users, partnered with more than 3,000 universities and institutions worldwide, and built an active expert network of over 50,000 specialists. Since 2025, AiScholar has also entered into strategic partnerships with Universiti Teknologi Malaysia and the University of Salamanca, while establishing a Malaysia Operations Center and a Europe Operations Center. Through these efforts, the company is actively expanding international research collaboration and bringing China's experience in intelligent research services to the global stage.
As the researchers note, "The endpoint of digital and intelligent transformation is never a technological platform itself, but a more creative and sustainable network of shared value." From process digitalisation, to platform digitisation, and then to intelligent transformation, AiScholar's ten-year journey reflects the broader evolution of China's research services industry: from improving efficiency, to optimising experience, and ultimately to empowering the wider ecosystem.
Related paper:
https://doi.org/10.55578/jedip.2511.011
