2026 International Conference on Artificial Intelligence and Education Systems (AIES 2026)
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About this event
2026 International Conference on Artificial Intelligence and Education Systems (AIES 2026)
Date: December 18-20, 2026
Venue: Kunming, China
Host: Yunnan Normal University
About the Conference
The 2026 International Conference on Artificial Intelligence and Education Systems (AIES 2026), hosted by Yunnan Normal University, will be held in Kunming, China, from December 18 to 20, 2026. This conference brings together scholars, experts, and professionals in the fields of artificial intelligence and education to explore the transformative impact of AI on personalized learning, efficiency, and accessibility in education.
AIES 2026 focuses on translating research into scalable solutions, fostering interdisciplinary collaboration, and building consensus on teacher training and assessment reforms. The event aims to accelerate thoughtful innovation that maximizes the educational benefits of AI while mitigating potential risks, ensuring that AI serves learners, educators, and society equitably.
Conference Theme
The conference theme, "Intelligent Enlightenment, Cloud Teachers, and Pioneering New Chapters," explores AI as a catalyst for educational transformation. Key areas of focus include:
- Intelligent teaching bodies
- Knowledge graph construction
- Opportunities and challenges brought by multimodal learning
- The digital transformation of teacher education and the reshaping of teacher roles in the AI era
Submission and Publication
Submission Guidelines: Full papers are required for publication, while abstracts are sufficient for presentation purposes. All submissions must be made electronically via the EasyChair Submission System using the provided templates.
Publication: Accepted full papers (registered and presented) will be published in the International Conference Proceedings.
Important Dates
- Submission Deadline: July 10, 2026
- Notification Date: August 10, 2026
- Registration Deadline: August 30, 2026
- Conference Date: December 18-20, 2026
Conference Topics
The conference will cover a wide range of topics, including but not limited to:
Generative AI in Education
- AI content generation for teaching
- LLM-powered tutoring systems
- Automated essay evaluation
- Synthetic educational materials
- Ethical use of GenAI by students
- Hallucination mitigation in EdTech
- Prompt engineering for learning
Intelligent Tutoring Systems
- Adaptive learning algorithms
- Knowledge tracing models
- Personalized learning paths
- Real-time feedback mechanisms
- Learner modeling techniques
- Cognitive diagnostic assessment
- Multi-agent tutoring architectures
Conversational AI & Chatbots
- Educational dialogue systems
- Virtual learning assistants
- Socratic questioning bots
- Collaborative learning support
- Emotional support chatbots
- Multilingual educational bots
- Voice-based learning interfaces
Contact Information
For assistance, please contact us at:
Phone: +86-19196997173 (Monday to Friday, 10:00 AM - 12:00 PM; 1:30 PM - 5:00 PM, holidays excepted)
Email: info@aies.net
© Copyright - AIES 2026. All rights reserved.
Data sheet
2026 International Conference on Artificial Intelligence and Education Systems (AIES 2026) – Event Attendee & Buyer Profile Analysis
Event date: December 18–20, 2026
Location: Yunnan Lishui Yunquan Hotel, Kunming, Yunnan, China
Event status: Upcoming
Research date: June 29, 2026
Event Overview
| Event Name | 2026 International Conference on Artificial Intelligence and Education Systems (AIES 2026) |
| Event Date | December 18–20, 2026 |
| Event Status | Upcoming |
| Venue | Yunnan Lishui Yunquan Hotel |
| City | Kunming |
| State / Region | Yunnan |
| Country | China |
| Organizer | Yunnan Normal University (official website states the conference is sponsored by Yunnan Normal University) |
| Official Event Website | aies.net |
| Event Type | International academic conference / research and professional exchange event |
| Primary Category | Education & Training |
| Secondary Applicable Categories | IT & Technology; Science & Research |
| Audience Reach | Global conference positioning with strongest practical concentration likely in China and broader Asia-Pacific education and AI communities |
| Estimated Attendance / Expected Footfall | Attendance figure not publicly confirmed by the organizer. |
| Attendance Data Reliability | Low for attendance volume; confirmed for dates, city, country, conference positioning, themes, and submission milestones based on the official event website excerpt |
| Main Purpose of Event | To convene scholars, experts, and professionals in artificial intelligence and education systems to share research, discuss scalable AI-enabled education solutions, and build consensus around teacher training, assessment reform, and digital transformation in education |
About the Event
AIES 2026 is an international conference focused on the intersection of artificial intelligence and education systems. According to the official website, the event will take place in Kunming, China, from December 18 to 20, 2026, and is sponsored by Yunnan Normal University. Its published topic areas include generative AI in education, intelligent tutoring systems, conversational AI, knowledge tracing, adaptive learning, and multimodal learning.
From a commercial and buyer-intelligence perspective, the event is most relevant for organizations involved in higher education technology, digital learning infrastructure, AI-enabled teaching tools, research collaboration, curriculum innovation, teacher training, assessment technology, and education digital transformation. It is primarily a conference for academic, institutional, research, and solution-evaluation stakeholders rather than a mass trade show, which means lead quality can be high for specialized B2B outreach, but public attendee-list transparency is likely limited.
1. Who Attends: Buyers / Attendees
| Buyer / Attendee Segment | Typical Organizations | Buying Role or Influence | Relevance to Exhibitors / Suppliers |
|---|---|---|---|
| University leadership and digital transformation teams | Universities, normal universities, research institutes, digital campus programs | Approve or influence institutional AI adoption, platform pilots, and strategic partnerships | High relevance for enterprise education software, LMS enhancement, AI learning tools, and campus technology solutions |
| Faculty researchers and academic labs | Education faculties, AI labs, learning science departments, pedagogy centers | Evaluate research merit, recommend pilots, influence grants and project selection | Strong fit for research tools, data platforms, AI model applications, and collaborative publications |
| Instructional technology and e-learning managers | Teaching support centers, e-learning teams, online education offices | Assess usability, integration, training, content workflow, and deployment feasibility | Relevant for tutoring systems, automated feedback tools, chatbot interfaces, and courseware solutions |
| Education policy and public sector education stakeholders | Education bureaus, public universities, government-backed research programs | Influence compliance, policy alignment, procurement pathways, and standards adoption | Important for regulated deployments, teacher training initiatives, and public education transformation projects |
| EdTech product leaders and solution vendors | Education technology companies, AI learning startups, platform providers | Seek partnerships, pilots, channel development, and academic validation | Useful for partnership selling, white-label opportunities, and applied AI use cases |
| Teacher education and training specialists | Teacher colleges, professional development centers, pedagogical institutes | Influence curriculum design, training budgets, and adoption of instructional AI frameworks | Relevant for workforce upskilling, assessment reform, and AI literacy programs |
| Publishing, content, and assessment stakeholders | Educational publishers, assessment providers, content platforms | Evaluate AI content generation, automated marking, and knowledge graph applications | Good fit for content automation, multilingual support, and student performance analytics |
2. Event Location and Attendee Geographic Origin
| Geographic Area | Likely Attendee Origin | Buyer Concentration | Notes |
|---|---|---|---|
| Kunming | Local universities, teacher education institutions, nearby public education stakeholders | Moderate | Host city base for onsite academics, local organizing partners, and regional institutions |
| Yunnan Province | Provincial higher education network, teacher training bodies, public institutions | Moderate to High | Likely strong domestic academic participation due to local sponsorship and venue location |
| Major China education hubs | Beijing, Shanghai, Guangzhou, Shenzhen, Hangzhou, Chengdu, Wuhan, Xi’an, Nanjing | High | Likely source of AI researchers, EdTech firms, and university innovation teams |
| National China reach | Scholars, graduate researchers, administrators, and digital education decision-makers across China | High | Official site positions the event as an international conference and invites broad participation in AI and education |
| International / Asia-Pacific and global academic network | Overseas scholars, international research collaborators, AI-in-education specialists | Selective but valuable | Likely driven by paper submissions, presentations, and research collaboration rather than broad commercial delegation volume |
3. Audience Reach
| Reach Level | Assessment | Explanation |
|---|---|---|
| Global | Primary classification | The event is explicitly branded as an international conference and invites global scholars and experts in AI and education. |
| National | Strong secondary reach | Actual buyer density is likely strongest across China’s university, research, and education-technology ecosystem. |
| Regional | Operational secondary reach | Kunming and Yunnan will likely contribute local and regional attendees due to host proximity and lower travel barriers. |
4. Sample Buyer Companies and Websites
| Buyer Company / Organization | Buyer Type | Why It Is Relevant | Website | Best Job Titles to Target | Evidence Level |
|---|---|---|---|---|---|
| Yunnan Normal University | Host / sponsor university | Official website states the conference is sponsored by Yunnan Normal University; highly relevant for AI-in-education research, teacher training, and institutional deployment discussions | ynnu.edu.cn | Vice President, Dean, Director of Educational Technology, Director of Information Center, Research Director | Confirmed Government / Procurement Organization |
| Official current-year attendee organization list | Not publicly released | No public current-year attendee, buyer, exhibitor, sponsor, or speaker organization directory was available in the provided official website content | aies.net | N/A | Confirmed current-year public list unavailable |
Public buyer-company transparency is currently limited. This event appears stronger for specialized account-based outreach into likely university, education technology, and research stakeholders than for broad attendee-list extraction based on official public directories.
5. Job Profiles, Industries and Event Type
| Priority | Job Title / Function | Department | Seniority Level | Why This Role Matters |
|---|---|---|---|---|
| 1 | Vice President / Provost / University Executive | Executive Leadership | C-Level / VP | Can sponsor institutional AI strategy, funding, and cross-campus digital transformation programs |
| 2 | Dean / Associate Dean | Academic Affairs | Director / VP | Influences faculty adoption, pilot programs, curriculum redesign, and departmental partnerships |
| 3 | Director of Educational Technology | Educational Technology / Teaching & Learning | Director | Core evaluator for AI teaching tools, LMS integration, faculty training, and deployment support |
| 4 | Director of Information Center / CIO / IT Director | IT / Digital Infrastructure | Director / VP / C-Level | Owns security, infrastructure, platform compatibility, and procurement feasibility for AI systems |
| 5 | Research Director / Lab Director / Principal Investigator | Research | Director / Senior Individual Contributor | Key for collaborative research, model evaluation, grants, and academic validation |
| 6 | Instructional Design Director / E-Learning Manager | Online Learning / Instructional Design | Manager / Director | Assesses classroom practicality, faculty usability, and learner experience |
| 7 | Teacher Training Director | Professional Development / Teacher Education | Director | Relevant because the official conference description highlights teacher training and teacher-role transformation |
| 8 | Product Director / Partnerships Director | Product / Business Development | Director / VP | Important for EdTech vendors seeking pilots, integration partners, and institutional channels |
| Priority | Apollo Industry | Why It Fits the Event | Best Buyer Use Case |
|---|---|---|---|
| 1 | Higher Education | Core institutional audience for AI-enabled teaching, research, and digital transformation | University-wide pilots, campus AI platforms, faculty enablement |
| 2 | Education Management | Fits administrative and operational education organizations | Institutional modernization, assessment, analytics, and policy alignment |
| 3 | E-Learning | Direct match to online learning systems, tutoring, and content delivery | Learning platforms, learner engagement, virtual assistants |
| 4 | Information Technology & Services | Relevant for systems integration, implementation, cloud support, and digital infrastructure | Integration partners, managed services, enterprise deployment |
| 5 | Computer Software | Strong fit for AI platforms, assessment tools, and education applications | Product partnerships, embedded AI, licensing |
| 6 | Research | Academic and applied research institutions are central to the conference model | Research collaboration, model evaluation, grant-funded pilots |
| 7 | Government Administration | Relevant for public education bodies and state-backed institutions | Education policy programs, procurement, teacher training initiatives |
| 8 | Primary/Secondary Education | Important where AI tools are evaluated for teacher support and classroom learning | Curriculum support, tutoring, assessment automation |
| 9 | Professional Training & Coaching | Relevant for teacher upskilling, certification, and institutional training providers | Faculty development and AI readiness programs |
| 10 | Publishing | Relevant to AI-generated educational content and assessment ecosystems | Content platforms, digital textbooks, automated feedback |
6. Estimated Attendance
| Metric | Figure | Status | Source / Basis | Notes |
|---|---|---|---|---|
| Estimated total footfall | Attendance figure not publicly confirmed by the organizer. | Unconfirmed | Official website excerpt reviewed | No public attendee volume stated in the provided official content |
| Exhibitor count | Not publicly confirmed | Unconfirmed | Official website excerpt reviewed | Conference appears presentation- and paper-driven rather than exhibition-heavy |
| Buyer count | Not publicly confirmed | Unconfirmed | Official website excerpt reviewed | No published institutional attendee directory or buyer program identified |
| Speaker count | Not publicly confirmed in the provided content | Unconfirmed | Official website navigation references keynote and invited speeches | Program detail exists on site navigation, but speaker organizations were not included in the supplied source text |
| Sponsor count | 1 publicly identified in supplied source | Confirmed | Official website | Yunnan Normal University stated as sponsor |
| Historical attendance | No verified prior-year attendance found in supplied source | Unavailable | Official website excerpt reviewed | No prior-edition attendance benchmark provided |
7. Key Focus Areas and Buyer Engagement
| Focus Area | Typical Buyer Need | Buyer Engagement Opportunity | Relevant Supplier Offering |
|---|---|---|---|
| Generative AI in Education | Content generation, feedback automation, policy-safe classroom use | Demonstrate responsible AI workflows, educator controls, and multilingual support | GenAI teaching assistants, writing support, content authoring tools |
| Intelligent Tutoring Systems | Personalized learning pathways and adaptive support | Show measurable learner outcomes, intervention logic, and integration capabilities | Adaptive tutoring platforms, learner analytics, intervention engines |
| Knowledge Graph Construction | Structured curriculum mapping and intelligent content retrieval | Position data architecture, semantic learning models, and curriculum intelligence | Knowledge graph tools, educational search, taxonomy systems |
| Multimodal Learning | Support for text, voice, image, and interactive learning experiences | Present accessibility, engagement, and cross-format instruction benefits | Speech interfaces, multimodal AI, interactive content systems |
| Teacher Training and Role Transformation | Practical upskilling and AI-readiness for educators | Offer training modules, implementation playbooks, and change-management support | Professional development platforms, certification, enablement programs |
| Assessment Reform | Automated evaluation, fairness, and learning diagnostics | Lead with explainability, bias reduction, auditability, and academic integrity | Assessment engines, essay evaluation, analytics dashboards |
| Conversational AI & Chatbots | Scalable learner support, multilingual engagement, FAQ automation | Target support services, online learning teams, and student success stakeholders | Student service bots, tutoring chatbots, voice-based interfaces |
Lead Quality Assessment
| Factor | Assessment | Explanation |
|---|---|---|
| Buyer relevance | High | Highly relevant for niche education AI, research tooling, campus technology, and teacher-training solutions |
| Decision-maker availability | Medium | Decision-makers are likely present, but many attendees may be researchers and faculty rather than direct procurement owners |
| Data collection potential | Low to Medium | Public attendee transparency appears limited; prospecting will rely more on account-based targeting than list extraction |
| Apollo targeting potential | High | Strong fit for higher education, e-learning, software, research, and education-management segmentation |
| Geographic targeting potential | High | Can target China-wide universities plus Asia-Pacific AI-in-education ecosystems |
| Best outreach approach | High | Use thought-leadership outreach, pilot proposals, research collaboration angles, and faculty-enablement value propositions |
| Overall lead quality | High for specialized B2B; Medium for broad attendee-list sales | Best suited for targeted institutional outreach rather than large-scale verified attendee list building |
| Best use case | High | ABM into universities, research centers, digital learning teams, and EdTech partners |
| Limitations / risks | Medium | Limited public buyer confirmation, uncertain attendance scale, and potentially slower procurement cycles in academic institutions |
Apollo.io Targeting Recommendation
| Filter Type | Recommended Filters | Purpose |
|---|---|---|
| Apollo industries | Higher Education; Education Management; E-Learning; Information Technology & Services; Computer Software; Research; Government Administration; Primary/Secondary Education; Professional Training & Coaching; Publishing | Focus on institutions and vendors most aligned with AI in education |
| Departments | Education, Information Technology, Operations, Product Management, Research, Business Development, Partnerships | Reach both academic buyers and solution-side partnership owners |
| Seniority | C-Level, VP, Director, Head, Manager, Owner, Partner, Professor where available | Balance procurement influence with academic evaluation authority |
| Job titles | Provost, Vice President, Dean, Associate Dean, Director of Educational Technology, CIO, IT Director, Director of Teaching and Learning, Instructional Design Director, E-Learning Manager, Research Director, Lab Director, Teacher Training Director, Product Director, Partnerships Director | Target strategic adopters and evaluators of AI education solutions |
| Geography | China first; then Asia-Pacific; optionally global English-language higher-education and EdTech accounts | Match the event’s host market while preserving international conference relevance |
| Employee size | 201–500, 501–1,000, 1,001–5,000, 5,001+ | Best fit for universities, sizable education groups, and mature technology providers |
| Keywords | artificial intelligence, AI in education, adaptive learning, intelligent tutoring, knowledge graph, learning analytics, digital campus, teacher training, educational technology, multimodal learning, assessment technology, conversational AI, LLM | Surface organizations actively aligned to the conference themes |
| Technologies | Use where available: LMS, cloud collaboration, analytics platforms, AI/ML stack indicators | Improve precision for deployment-ready accounts |
| Revenue range | Apply selectively for vendor-side accounts; less reliable for universities and public institutions | Useful for prioritizing commercial partner targets |
| Company type | Educational institution, public institution, private company, research organization | Separate procurement pathways and outreach messaging |
Suggested Apollo Search Logic: ("artificial intelligence" OR "AI in education" OR "adaptive learning" OR "intelligent tutoring" OR "learning analytics" OR "knowledge graph" OR "teacher training" OR "digital campus" OR "educational technology" OR "LLM") AND (Dean OR Provost OR "Director of Educational Technology" OR CIO OR "E-Learning Manager" OR "Research Director" OR "Instructional Design Director" OR "Partnerships Director").
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Sources & Verification Notes
| Source | Type | What It Verified | Reliability |
|---|---|---|---|
| AIES 2026 Official Website | Official event website | Event title, official dates, Kunming/China location, sponsor, conference purpose, topic areas, and submission timeline | High |
| AIES 2026 Official Website Navigation | Official site structure | Confirms that program, keynote, invited speeches, venue, visa, and registration sections exist, but detailed participant data was not included in the supplied text extract | High |
| Yunnan Normal University | Institutional website | Institutional identity and official domain for the named sponsor/host organization | High |
| User-supplied known event details | Provided input | Venue name and state/region used where not contradicted by the official website excerpt; venue was not visible in the supplied official text | Medium |
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