2026 3rd International Conference on Artificial Intelligence and Future Education(AIFE 2026)
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About this event
2026 3rd International Conference on Artificial Intelligence and Future Education (AIFE 2026)
The 2026 3rd International Conference on Artificial Intelligence and Future Education (AIFE 2026) is a premier interdisciplinary forum dedicated to exploring the transformative intersection of artificial intelligence (AI) and education. This conference brings together researchers, educators, policymakers, industry leaders, and technologists to discuss cutting-edge advancements, pedagogical innovations, and ethical considerations shaping the future of learning in an AI-driven world.
Event Overview
AIFE 2026 will convene under the theme "Empowering Education Through Intelligent Technologies", focusing on how AI can revolutionize teaching methodologies, personalized learning, administrative efficiency, and lifelong skill development. The conference will feature keynote addresses, panel discussions, workshops, and peer-reviewed paper presentations to foster collaboration and knowledge exchange.
Key Themes and Topics
- AI-driven adaptive learning systems
- Intelligent tutoring and cognitive modeling
- Ethical AI in educational settings
- Virtual and augmented reality for immersive learning
- AI for accessibility and inclusive education
- Machine learning in curriculum design and assessment
- AI policy frameworks for educational institutions
- Blockchain and AI for credential verification
- Human-AI interaction in classroom environments
Target Audience
- Academic researchers in AI, education, and EdTech
- K-12 and higher education administrators
- Corporate training and workforce development professionals
- AI engineers and data scientists in education
- Government and NGO policymakers
- E-learning platform developers and investors
Event Structure
AIFE 2026 will include:
- Keynote speeches by global leaders in AI and education
- Parallel technical sessions for paper presentations
- Industry exhibitions showcasing AI-powered educational tools
- Hands-on workshops for educators and developers
- Networking opportunities for cross-sector collaboration
Why Participate?
Attendees will gain insights into:
- Emerging AI technologies disrupting traditional education models
- Best practices for integrating AI into curricula and administrative systems
- Global trends in EdTech investment and adoption
- Opportunities for partnerships between academia, industry, and governments
Call for Contributions
Researchers and practitioners are invited to submit original papers, case studies, and demo proposals. Topics of interest align with the conference themes, emphasizing both theoretical contributions and real-world applications.
Event Logistics
Date: July 15–18, 2026
Venue: [To be announced – Major international hub with academic and tech infrastructure]
Language: English (official conference language)
Registration: Open from January 1, 2026. Early-bird discounts available.
AIFE 2026 promises to be a catalyst for reimagining education in the age of AI, offering unparalleled opportunities for professional growth, innovation, and global networking. Join us in shaping the classrooms and workplaces of tomorrow.
Data sheet
2026 3rd International Conference on Artificial Intelligence and Future Education (AIFE 2026) – Event Attendee & Buyer Profile Analysis
Event date: 26 June 2026 – 28 June 2026
Location: Waseda University Building 3, 1 Chome-6-1 Nishiwaseda, Shinjuku City, Tokyo, Japan
Event status: Completed
Research date: 29 June 2026
Event Overview
| Event Name | 2026 3rd International Conference on Artificial Intelligence and Future Education (AIFE 2026) |
| Event Date | 26 June 2026 – 28 June 2026 |
| Event Status | Completed |
| Venue | Waseda University Building 3, 1 Chome-6-1 Nishiwaseda |
| City | Shinjuku City, Tokyo |
| State / Region | Tokyo Metropolis |
| Country | Japan |
| Organizer | Organizer not publicly confirmed in the provided materials. |
| Official Event Website | Official event website not verified from the supplied materials. |
| Event Type | International academic conference / education technology summit |
| Primary Category | Education & Training |
| Secondary Applicable Categories | IT & Technology; Science & Research |
| Audience Reach | International / academic-professional conference audience. Estimated from the conference title, theme, and format. |
| Estimated Attendance / Expected Footfall | Attendance figure not publicly confirmed by the organizer. |
| Attendance Data Reliability | Low for attendance metrics; confirmed for dates and venue based on supplied event brief. |
| Main Purpose of Event | To convene researchers, educators, policymakers, and technology stakeholders around AI-driven learning, pedagogy innovation, accessibility, governance, assessment, and future education models. |
About the Event
AIFE 2026 is positioned as an interdisciplinary conference focused on the intersection of artificial intelligence and future-oriented education. Based on the supplied event description, the program centers on adaptive learning, intelligent tutoring, classroom human-AI interaction, inclusive education, curriculum design, policy, immersive learning, and credential innovation. The format appears to combine keynote sessions, panel discussions, workshops, and peer-reviewed presentations.
From a commercial and lead-generation perspective, this event is most relevant for higher education institutions, research organizations, edtech platforms, digital learning providers, AI solution vendors, public education agencies, and institutional innovation teams. It is stronger for thought-leadership, partnerships, research collaboration, pilot projects, and institutional buying conversations than for high-volume mass-market attendee list building.
1. Who Attends: Buyers / Attendees
| Buyer / Attendee Segment | Typical Organizations | Buying Role or Influence | Relevance to Exhibitors / Suppliers |
|---|---|---|---|
| University leadership | Universities, colleges, graduate schools | Approves digital learning strategy, innovation budgets, institutional pilots | High-value institutional buyers for AI platforms, LMS enhancements, analytics, and research tools |
| Faculty and academic researchers | Education departments, computer science labs, learning sciences centers | Influences trials, curriculum adoption, grant partnerships, and publication-backed credibility | Important for product validation, pilot design, and research collaboration |
| Instructional technology and e-learning teams | Centers for teaching excellence, digital transformation offices, LMS teams | Evaluates usability, integrations, deployment timelines, and student outcomes | Core operational buyers for software and implementation services |
| Public-sector education policymakers | Education ministries, school boards, public agencies, standards bodies | Shapes policy frameworks, procurement pathways, and compliance expectations | Critical for public-sector sales, pilots, and policy alignment |
| Edtech product and partnership leaders | Learning platforms, tutoring systems, assessment and analytics vendors | Evaluates channel partnerships, integrations, OEM opportunities, and co-development | Relevant for alliances, reseller discussions, and embedded AI use cases |
| Accessibility and inclusive learning specialists | Special education units, accessibility offices, inclusive technology teams | Influences product requirements, compliance, and learner support priorities | Good fit for adaptive content, speech, translation, and accessibility tools |
| Corporate L&D and workforce development teams | Large employers, training academies, enterprise learning teams | Buys AI-enabled upskilling, assessment, microlearning, and credential tools | Useful secondary buyer segment where lifelong learning is in scope |
| Research funders and innovation networks | Grant bodies, foundations, research institutes, consortia | Supports project funding, consortia, and strategic initiatives | Relevant for long-cycle relationship building rather than direct transactional sales |
2. Event Location and Attendee Geographic Origin
| Geographic Area | Likely Attendee Origin | Buyer Concentration | Notes |
|---|---|---|---|
| Shinjuku City, Tokyo | Local academic and institutional attendees | High | Strong concentration of universities, research institutions, technology firms, and public agencies |
| Tokyo Metropolis | Regional educators, ministry stakeholders, edtech operators, researchers | Very High | Tokyo is Japan’s main hub for education policy, enterprise technology, and international collaboration |
| Greater Kanto region | Nearby institutions from Yokohama, Chiba, Saitama, Tsukuba, and surrounding areas | High | Accessible catchment for same-day and short-stay conference participation |
| Japan nationwide | Universities, teacher-training institutions, education vendors, public-sector bodies | Medium to High | Likely national reach given international conference branding and AI-in-education theme |
| Asia-Pacific | Researchers, conference speakers, graduate scholars, edtech collaborators | Medium | Likely source of paper presenters and institutional partnerships |
| Global academic market | International scholars, AI researchers, education innovators | Medium | International title suggests cross-border participation, but current-year attendee geography is not publicly confirmed |
3. Audience Reach
| Reach Level | Assessment | Explanation |
|---|---|---|
| Global | Primary classification | The event title, conference format, and AI/education subject matter indicate an international academic and professional audience rather than a purely domestic gathering. |
| National | Secondary reach | Tokyo venue placement makes the event highly relevant for Japanese universities, public-sector education agencies, and domestic edtech companies. |
4. Sample Buyer Companies and Websites
No official current-year attendee, exhibitor, sponsor, or buyer list was publicly verified from the supplied materials. The organizations below are buyer-side and high-fit prospecting targets for AIFE 2026 themes; they should not be treated as confirmed attendees.
| Buyer Company / Organization | Buyer Type | Why It Is Relevant | Website | Best Job Titles to Target | Evidence Level |
|---|---|---|---|---|---|
| Waseda University | Host-site higher education institution | Natural target for AI teaching tools, research platforms, academic partnerships, and campus pilots | waseda.jp | Vice President, Dean, CIO, Director of Educational Technology, Professor, Research Center Director | Strong Market Fit, Attendance Not Confirmed |
| The University of Tokyo | Research university | Relevant for AI pedagogy, digital learning research, and institutional technology adoption | u-tokyo.ac.jp | Professor, CIO, Director of Learning Innovation, Dean, Academic Affairs Director | Strong Market Fit, Attendance Not Confirmed |
| Kyoto University | Research university | Likely interest in AI ethics, research collaboration, and advanced learning systems | kyoto-u.ac.jp | Dean, Professor, Director of Digital Education, CIO, Research Administrator | Strong Market Fit, Attendance Not Confirmed |
| Osaka University | Research university | Potential buyer of adaptive learning, AI assessment, and immersive teaching technologies | osaka-u.ac.jp | Director of ICT, Dean, Professor, Teaching Innovation Lead | Strong Market Fit, Attendance Not Confirmed |
| Keio University | Private university | Relevant for digital transformation, blended learning, and academic-industry pilots | keio.ac.jp | Vice President, CIO, Dean, Director of Educational Innovation | Strong Market Fit, Attendance Not Confirmed |
| Tohoku University | National university | Good fit for AI-enabled student support, analytics, and research collaboration | tohoku.ac.jp | Professor, CIO, Research Center Director, Digital Learning Director | Strong Market Fit, Attendance Not Confirmed |
| National Institute of Informatics | Research institute | Relevant to AI research, data infrastructure, and education technology standards | nii.ac.jp | Research Director, Professor, Program Manager, Digital Infrastructure Lead | Strong Market Fit, Attendance Not Confirmed |
| Ministry of Education, Culture, Sports, Science and Technology (MEXT) | Government education policymaker | Key stakeholder for AI policy, public education frameworks, and national digital learning priorities | mext.go.jp | Policy Director, Program Officer, Innovation Lead, Education Technology Advisor | Strong Market Fit, Attendance Not Confirmed |
| Benesse Corporation | Education services / corporate learning buyer | Strong fit for AI learning content, assessment, and platform partnerships | benesse.co.jp | Head of Product, Learning Innovation Director, Partnerships Director, CTO | Strong Market Fit, Attendance Not Confirmed |
| Classi Corp. | Edtech platform operator | Relevant for K-12 and institutional AI learning workflows, analytics, and engagement tools | classi.jp | Product Director, Partnerships Manager, CTO, Learning Solutions Lead | Strong Market Fit, Attendance Not Confirmed |
5. Job Profiles, Industries and Event Type
| Priority | Job Title / Function | Department | Seniority Level | Why This Role Matters |
|---|---|---|---|---|
| 1 | Chief Information Officer | IT / Digital Transformation | C-Level | Owns enterprise technology adoption, integration, security, and infrastructure decisions |
| 2 | Director of Educational Technology | Academic Technology / Learning Innovation | Director | Direct operational buyer for AI learning tools, LMS extensions, and pilot deployments |
| 3 | Dean / Associate Dean | Academic Leadership | VP / Director | Influences curriculum, faculty priorities, and departmental adoption |
| 4 | Professor / Principal Investigator | Research / Faculty | Manager / Individual Contributor | Key influencer for pilots, publications, and institutional credibility |
| 5 | Director of Digital Learning | E-Learning / Online Programs | Director | Leads learner engagement, online delivery, and assessment modernization |
| 6 | Partnerships Director | Business Development / Alliances | Director | Relevant for co-development, content partnerships, and ecosystem deals |
| 7 | Product Director | Product / Innovation | Director | Important at edtech companies evaluating embedded AI or partner solutions |
| 8 | Policy Director / Program Officer | Government / Public Policy | Director / Manager | Relevant for public-sector adoption pathways and compliance-driven engagement |
| Priority | Apollo Industry | Why It Fits the Event | Best Buyer Use Case |
|---|---|---|---|
| 1 | Higher Education | Core institutional audience for university-centered AI and future learning adoption | Campus-wide learning systems, research tools, faculty enablement |
| 2 | Education Management | Covers education operators, school groups, and learning administration entities | Administrative AI, learner analytics, assessment modernization |
| 3 | E-Learning | Direct fit for platforms delivering online, blended, or adaptive learning | AI tutors, content personalization, assessment engines |
| 4 | Information Technology & Services | Relevant for system integrators, digital transformation teams, and AI implementation partners | Deployment, integration, managed services |
| 5 | Computer Software | Captures AI platform providers, learning software vendors, analytics firms | Product partnerships, OEM integrations, institutional sales |
| 6 | Research | Relevant for academic labs, institutes, and evidence-driven innovation buyers | Research collaboration, pilots, data projects |
| 7 | Government Administration | Important for ministries, public universities, and public education systems | Policy-aligned technology procurement and program rollout |
| 8 | Public Policy | Supports outreach to education policy and standards stakeholders | AI governance, ethics, framework development |
| 9 | Professional Training & Coaching | Relevant for lifelong learning and workforce reskilling applications | AI-enabled corporate learning and competency mapping |
| 10 | Internet | Useful for web-native education platforms and digital content operators | Scalable SaaS learning products and AI-enabled student engagement |
6. Estimated Attendance
| Metric | Figure | Status | Source / Basis | Notes |
|---|---|---|---|---|
| Estimated total footfall | Attendance figure not publicly confirmed by the organizer. | Not Confirmed | No verified public organizer statistic available in supplied materials | Do not use this event for volume-based attendance claims without organizer proof |
| Exhibitor count | Not publicly confirmed | Not Confirmed | No verified exhibitor directory provided | Conference appears content-led rather than expo-led |
| Buyer count | Not publicly confirmed | Not Confirmed | No verified attendee or delegate breakdown supplied | Relevant buyers are more likely institutional decision-makers than retail-style buyers |
| Speaker count | Not publicly confirmed | Not Confirmed | No verified program roster supplied | Conference description indicates keynote and panel activity |
| Sponsor count | Not publicly confirmed | Not Confirmed | No verified sponsor list supplied | Sponsorship data would materially improve buyer targeting accuracy |
| Historical attendance | No prior-year official attendance figure verified | Historical / prior-year evidence unavailable | No official prior-year data confirmed from supplied materials | Prior-year participation evidence was not available for verification |
7. Key Focus Areas and Buyer Engagement
| Focus Area | Typical Buyer Need | Buyer Engagement Opportunity | Relevant Supplier Offering |
|---|---|---|---|
| Adaptive learning systems | Personalized student pathways and learning outcome improvement | Pilot deployments with universities and digital learning teams | AI tutoring, recommendation engines, learner analytics |
| Intelligent tutoring | Scalable support for instruction and student engagement | Demo-led conversations with faculty and learning innovation teams | Conversational AI, tutoring assistants, feedback engines |
| Ethical AI in education | Governance, bias mitigation, transparency, data privacy | Policy roundtables and framework discussions | Governance tools, audit frameworks, compliance consulting |
| VR / AR immersive learning | Interactive instruction and engagement enhancement | Department-level pilots and innovation lab showcases | XR content, simulation platforms, immersive assessment |
| Accessibility and inclusive education | Better access for diverse learners and multilingual cohorts | Needs-based discussions with inclusion and disability support teams | Captioning, translation, adaptive interfaces, assistive AI |
| AI in curriculum and assessment | Faster evaluation, smarter design, better feedback loops | Engage deans, faculty leads, and accreditation-aware stakeholders | Assessment automation, rubric tools, curriculum intelligence |
| AI policy frameworks | Institutional guardrails and public trust | Executive briefings and public-sector engagement | Policy advisory services, governance templates, training |
| Credential verification | Trusted record management and lifelong learning pathways | Institutional registrar and digital credentialing conversations | Blockchain credentials, verification systems, learner records |
Lead Quality Assessment
| Factor | Assessment | Explanation |
|---|---|---|
| Buyer relevance | High | Good fit for education, research, academic technology, and AI solution providers |
| Decision-maker availability | Medium | Academic conferences attract influential stakeholders, but purchasing cycles may be committee-based and slower than corporate events |
| Data collection potential | Low to Medium | Current-year public attendee transparency appears limited from the supplied materials |
| Apollo targeting potential | High | Institutional, edtech, research, and public-sector personas can be targeted by industry, title, and geography |
| Geographic targeting potential | High | Tokyo, Japan, and Asia-Pacific education innovation hubs provide a clear prospecting perimeter |
| Best outreach approach | Thought-leadership-led outreach | Use case studies, research alignment, policy awareness, and pilot offers perform better than generic sales messaging |
| Overall lead quality | High | Strong quality for targeted B2B institutional outreach, but not ideal for large-scale attendee list assumptions without official data |
| Best use case | Partnership and institutional demand generation | Best for account-based outreach into universities, edtech operators, and public education stakeholders |
| Limitations / risks | Medium | Limited confirmed participant data reduces confidence for event-specific attendee list building |
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; Public Policy; Professional Training & Coaching | Narrow to institutional and AI-for-education buyers |
| Departments | Information Technology; Education; Product; Engineering; Operations; Business Development; Research; Program Management | Find technical evaluators, innovation leaders, and partnership owners |
| Seniority | C-Level; VP; Director; Head; Manager; Partner; Professor-equivalent titles where available | Prioritize budget owners and strong internal influencers |
| Job titles | CIO, CTO, Director of Educational Technology, Director of Digital Learning, Dean, Vice President Academic Affairs, Professor, Principal Investigator, Partnerships Director, Product Director, Learning Innovation Director, Policy Director | Build lists around adoption, governance, and innovation roles |
| Geography | Japan first; Tokyo, Kanagawa, Chiba, Saitama, Osaka, Kyoto, Miyagi; secondary APAC markets | Replicate likely event catchment and expansion markets |
| Employee size | 51-200; 201-500; 501-1,000; 1,001-5,000; 5,001+ | Target institutions and solution providers with implementation capacity |
| Keywords | AI in education, adaptive learning, learning analytics, digital learning, edtech, intelligent tutoring, assessment, accessibility, immersive learning, curriculum innovation, AI policy | Surface organizations aligned to event themes |
| Technologies | Use where available: LMS, AI/ML tools, analytics platforms, cloud learning infrastructure | Identify digitally mature accounts more likely to adopt AI solutions |
| Revenue range | Use selectively for private edtech or training firms; less useful for public universities | Prioritize commercial buyers with scalable budgets |
| Company type | Educational institution, government agency, software vendor, research institute, training provider | Segment outreach by sales motion and decision cycle |
Suggested Apollo Search Logic: ("artificial intelligence" OR AI OR "adaptive learning" OR edtech OR "digital learning" OR "learning analytics" OR "intelligent tutoring" OR "educational technology") AND (university OR college OR school OR research OR learning OR training) AND (CIO OR CTO OR dean OR professor OR "director of educational technology" OR "director of digital learning" OR "learning innovation" OR partnerships).
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Sources & Verification Notes
| Source | Type | What It Verified | Reliability |
|---|---|---|---|
| User-supplied event brief | Provided event material | Event title, city, country, venue, dates, conference theme, and topic areas | High for supplied fields; limited for organizer and attendance verification |
| Waseda University | Official institution website | Host institution domain and venue context | High for institution identity; specific room/building event booking not independently verified here |
| MEXT | Official government website | Public-sector education policy stakeholder relevance in Japan | High for organization legitimacy; not evidence of event attendance |
| Official event website / agenda / organizer page | Primary source sought | Organizer name, attendee counts, speaker roster, sponsor list, and delegate composition were not verified from the supplied materials | Not available for confirmation in this brief |
Verification note: This event appears suitable for targeted B2B prospecting into higher education, research, public education, and edtech accounts. It is less suitable for selling as a confirmed attendee-list event unless the organizer publishes a verified attendee, sponsor, speaker, or exhibitor directory.
🎯 Selling to this event's audience? Get a free tailored buyer list
Tell us your work email and our AI instantly builds a buyer list matched to 2026 3rd International Conference on Artificial Intelligence and Future Education(AIFE 2026) — the best‑fit companies to target, the exact decision‑maker job titles, and the industry filters that fit what you sell.
🔒 Get my buyer details Free · ~20 seconds