The resonance of six-dimensional forces cultivates a tree, the industry resonance behind ABLE DIGITAL (02687)'s mid-term performance.

If we compare AI in higher education to a tree, then in the first half of 2026, six forces are simultaneously nurturing it. ABLE DIGITAL (02687)'s interim performance announcement shows that by the end of the reporting period, the value of contracts on hand reached RMB 505 million, a year-on-year increase of 34.7%, far exceeding the revenue growth rate of 19.1% during the same period. Orders serve as a leading indicator of demand, and this round of demand expansion is driven not by a single policy stimulus or short-term event, but by a structural resonance of six forces converging: national strategy, industrial transformation, teaching practice, learning methods, research paradigms, and the ecosystem of large models. What the nation needs: Infrastructure for an autonomous knowledge system. During the reporting period, the state intensively released significant top-level policies in science and education. The "Outline for Building a Strong Education Nation" proposes establishing a Chinese autonomous knowledge system, with coordinated development of education, science, and technology talent, further clarifying the strategic position of knowledge graphs as the infrastructure of the knowledge system; the "AI + Education Action Opinions, Action Plan," and the "14th Five-Year Plan" were published intensively, accelerating the integration of intelligent teaching and virtual experiments into new education infrastructure; the "Opinions on Accelerating the Digitalization of Education" promote in-depth integration of large models with education and teaching; the "Basic Discipline Series '101 Plan'" continues to expand into new engineering and new agricultural fields. Policies have formed a systematic deployment around building an autonomous knowledge system, tackling challenges in university research, and training innovative talents. Recognition at the national level has been translated into substantive positioning. In May 2026, the Ministry of Education released the first batch of 18 national-level intelligent education agents at the World Digital Education Conference, with projects that the company deeply participated in selected among them. In the Ministry of Education's "101 Plan," a core national project for higher education teaching reform led by academicians from both academies, the company has cumulatively engaged in collaborative works covering multiple disciplines including computer science, physics, basic medicine, economics, chemistry, mechanics, atmospheric science, agricultural engineering, Jiangsu Nonghua Intelligent Agriculture Technology, geology, intelligent medical engineering, pharmacy, traditional Chinese medicine, and philosophy, extending from a technology supplier to a co-builder of standards. What the industry needs: Supply of AI talent and integration of industry and education. Demand from the industry comes from two directions: one is the large talent gap created by the penetration of AI technology into various sectors, and the other is the urgent need for composite talents due to the digital transformation of traditional industries. The company's business has broken the boundaries of higher education scenarios, extending into high-value vertical fields such as healthcare, research, and industry, with collaborative partners including numerous hospitals, academic institutions, research organizations, and leading enterprises in advanced manufacturing. On the international front, the AI Talent Factory (AITF) project co-constructed by the company in China and Indonesia will formally sign a cooperation agreement in August 2026 in Jakarta. This project is one of the first national-level pilot projects for talent training under Indonesia's "National AI Strategy 20202045," aiming to train a total of 1,000 skilled AI practitioners from 2026 to 2029. Additionally, the company unveiled the China-Kyrgyzstan Clean Energy Storage Joint Laboratory at the Third Shanghai Cooperation Organization Green Energy Academician Forum, applying self-developed AI technology to cross-border platform construction. What educators need: From tools to intelligent collaborative partners. The core demand of teachers is to be liberated from repetitive teaching tasks to focus on instructional design and academic innovation. The company's AI agents employ a dual-architecture of "course agents" and "school agents," with the course side focusing on the intelligent automation of teaching processes including lesson preparation, adaptive question generation, and student performance analysis, while the school side supports local deployment and data security. The panoramic space provides offline physical platforms through immersive displays and multimodal human-computer interaction terminals for educators. During the reporting period, the contract amount for AI agents increased by 62.3%, and the number of customers in the panoramic space grew by 77.8%, directly reflecting the speed at which teaching demands are being released. What learners need: Personalized and immersive learning experiences. Learners require personalized paths tailored to their needs rather than standardized knowledge delivery. Based on the "Damingbai" large model and knowledge graph system, the company can offer core capabilities such as personalized learning path recommendations, knowledge inference and Q&A, and information retrieval. The physics AI virtual experiments expand knowledge from two-dimensional semantic mapping to three-dimensional physical spaces, integrating spatial relationships, operational logic, and real-time feedback, providing learners with a repeatable practice environment for high-risk, high-cost, and high-complexity experiments. During the reporting period, the contract value for physics AI virtual experiments increased by 52.6%, and the number of customers grew by 46.4%, with application scenarios widely penetrating cutting-edge engineering fields such as unmanned systems and intelligent logistics. What researchers need: A disciplinary foundation of AI for Science. Research paradigms are being reshaped by AI. The company has formed a product matrix covering multiple disciplines including medicine, mechanics, nuclear technology, marine intelligence and unmanned technology, atmospheric science, and nuclear physics around C9 Alliance universities, with Peking University's Future Learning Center in Medicine being a flagship collaboration project. These discipline-specific large models and knowledge graphs provide researchers with a full chain of AI assistance from literature organization and knowledge inference to virtual experiments. The company explicitly designates "AI for Science" as its official standard expression, using it only when the cooperative content has distinct research attributes, reflecting a serious positioning towards research scenarios. What large models need: Vertical data and practical application scenarios. General large model vendors urgently require high-quality vertical industry data and scalable application scenarios, which is precisely the core asset accumulated by ABLE DIGITAL over the past two decades. During the reporting period, the company successively signed strategic cooperation framework agreements with Alibaba Cloud (June), Volcano Engine (July), and Baidu Intelligent Cloud (August). In collaboration with Alibaba Cloud, they are creating a multi-agent platform called "Damingbai Polymas" based on the open-source AgentScope Java framework; with Volcano Engine, they are collaborating on four areas: empowering large model knowledge, integrating virtual and practical training, AI audio-video interactive teaching, and digital talent cultivation; and with Baidu Intelligent Cloud, they are integrating the Qianfan large model, Wenxin series large model, and professional encyclopedia resources to jointly develop vertical intelligent agents for educational, industrial, and research scenarios. The fact that three leading general large model providers have chosen to collaborate with the company rather than to replace it within two months fundamentally reflects a consensus on the cooperative path of "general foundation + vertical specialized knowledge + practical campus application." These six forces do not exist in isolation but are mutually reinforcing and amplifying. National policies provide direction and market space, industry demand offers funding and application scenarios, educators and learners constitute the final user base, and researchers expand the frontiers of knowledge, while the large model ecosystem provides technological leveragethese six forces converge on the same tree: with a root of structured knowledge assets, a trunk of multimodal AI, branches of a nationwide delivery network, and leaves of multidisciplinary scenarios. During the reporting period, revenue grew by 19.1%, gross profit increased by 28.0%, orders on hand rose by 34.7%, and the number of high-value customers grew by 26.7%. This group of data is a concentrated reflection of how the six-dimensional forces transition from policy vision to commercial realization. When the roots of a tree have been deeply established for twenty years and are nourished simultaneously by six forces, its growth is not merely a transient gust of wind, but rather a structural inevitability.