2026 10th International Conference on Artificial Intelligence and Virtual Reality (AIVR 2026)
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About this event
2026 10th International Conference on Artificial Intelligence and Virtual Reality (AIVR 2026)
The 10th International Conference on Artificial Intelligence and Virtual Reality (AIVR 2026) will be held in Kobe, Japan from July 11-13, 2026. This conference brings together researchers and scientists from both academic and industrial backgrounds who are working on novel outcomes in Artificial Intelligence (AI) and Virtual Reality (VR). The event focuses on the intersection of these two fields, aiming to create more natural and realistic virtual worlds and develop more effective applications.
Event Overview
AIVR 2026 is part of a successful series that has previously been held in cities such as Nagoya (2018), Singapore (2019), Kumamoto (2023), Fukuoka (2024), and Osaka (2025), with virtual conferences taking place from 2020 to 2022. The conference provides an ideal platform for reflection on past developments and a forward-looking perspective on future advancements in AI and VR technologies.
Conference Tracks
- Track 1: Systems, including techniques, performance, and implementation
- Track 2: Content creation and modelling
- Track 3: AI technologies
- Track 4: Cognitive aspects, perception, user behaviour
- Track 5: Interactions / interactive and responsive environments
- Track 6: Applications and use cases
Key Dates
| Event | Date |
|---|---|
| Deadline for Paper Submission | June 10, 2026 |
| Notification of Acceptance | June 20, 2026 |
| Deadline for Registration and Camera Ready Submission | June 25, 2026 |
| Dates of the Conference | July 11-13, 2026 |
Publication
All accepted papers will be published in the conference proceedings by Springer-Verlag as part of the Smart Innovation, System and Technologies (SIST) book series. This series is indexed by SCOPUS, EI Compendex, INSPEC, WTI Frankfurt eG, zbMATH, Japanese Science and Technology Agency (JST), SCImago, and DBLP. Selected papers may also be recommended for publication in the International Journal of Reasoning-based Intelligent Systems.
Venue and Location
The conference will take place at the Conference Venue in Kobe, Japan. Kobe is a port city known for its international culture and is located less than an hour from Osaka and Kyoto by train.
Contact Information
For any queries regarding the conference, please contact aivr@chairmen.org.
Data sheet
2026 10th International Conference on Artificial Intelligence and Virtual Reality (AIVR 2026) – Event Attendee & Buyer Profile Analysis
Event date: July 11–13, 2026
Location: Kobe, Japan
Event status: Upcoming
Research date: June 29, 2026
Event Overview
| Event Name | 2026 10th International Conference on Artificial Intelligence and Virtual Reality (AIVR 2026) |
| Event Date | July 11–13, 2026 |
| Event Status | Upcoming |
| Venue | Not publicly specified in the provided official website content |
| City | Kobe |
| State / Region | Hyogo Prefecture |
| Country | Japan |
| Organizer | Not clearly identified in the provided official website content |
| Official Event Website | www.aivr.org |
| Event Type | International academic and industry conference |
| Primary Category | IT & Technology |
| Secondary Applicable Categories | Science & Research; Education & Training |
| Audience Reach | International research and innovation audience with strong Asia-Pacific relevance |
| Estimated Attendance / Expected Footfall | Attendance figure not publicly confirmed by the organizer. |
| Attendance Data Reliability | Low for headcount; high for dates, city, country, conference tracks, and publication details |
| Main Purpose of Event | To bring together academic and industrial researchers working at the intersection of Artificial Intelligence and Virtual Reality for paper presentations, knowledge exchange, networking, and future collaboration. |
About the Event
AIVR 2026 is the 10th edition of the International Conference on Artificial Intelligence and Virtual Reality, scheduled for July 11–13, 2026 in Kobe, Japan. According to the official event website, the conference is designed to bring together researchers and scientists from both academic and industrial backgrounds who are developing new outcomes in AI and VR. Its program focus spans systems, content creation and modelling, AI technologies, cognitive and behavioural aspects, interactive environments, and applications.
From a market-intelligence perspective, AIVR is best understood as a specialist B2B/B2R innovation conference rather than a broad commercial trade show. It matters because it attracts technically informed stakeholders who influence research partnerships, enterprise pilots, university-industry collaboration, product experimentation, and emerging-technology adoption. The event is relevant for organizations selling AI software, XR/VR tools, simulation systems, research infrastructure, spatial computing platforms, data tools, sensors, visualization systems, and applied innovation services.
1. Who Attends: Buyers / Attendees
| Buyer / Attendee Segment | Typical Organizations | Buying Role or Influence | Relevance to Exhibitors / Suppliers |
|---|---|---|---|
| Academic researchers and lab leaders | Universities, engineering schools, computer science labs, XR research centers | Influence software selection, lab tools, compute infrastructure, sensors, simulation platforms, and collaboration partners | High relevance for research tools, AI platforms, development software, headsets, tracking systems, and grant-partner outreach |
| Industrial R&D teams | Technology companies, robotics firms, automotive labs, device manufacturers, simulation developers | Evaluate prototypes, strategic partnerships, licensing, and enterprise use cases | High relevance for solution vendors offering AI engines, computer vision, digital twins, and immersive collaboration systems |
| AI/ML technical leaders | AI software vendors, enterprise innovation groups, applied research organizations | Assess model deployment, data pipelines, experimentation tools, and integration partners | Strong fit for AI tooling, MLOps, synthetic data, analytics, and research compute vendors |
| XR/VR product and platform teams | VR hardware makers, game engines, immersive content studios, metaverse and spatial computing platforms | Influence hardware evaluation, SDK adoption, content pipelines, and ecosystem partnerships | High relevance for rendering, 3D workflow, device accessories, motion capture, and visualization suppliers |
| Cognitive science and HCI specialists | Human-computer interaction groups, usability labs, behavioural research institutes | Influence user testing tools, eye-tracking, interaction systems, and data collection methods | Good fit for user analytics, research software, sensors, and immersive usability platforms |
| Application owners and solution architects | Healthcare innovators, manufacturing digitalization teams, education technology groups, training simulation programs | Assess practical adoption, pilot use cases, partner viability, and ROI scenarios | Relevant for vertical AI/VR solutions, enterprise deployment, and digital transformation messaging |
| Publishers and academic program stakeholders | Conference publication partners, journal stakeholders, indexing ecosystem participants | Influence dissemination, academic visibility, and institutional credibility | Useful for partnership, sponsorship, and academic ecosystem engagement rather than direct product sales |
2. Event Location and Attendee Geographic Origin
| Geographic Area | Likely Attendee Origin | Buyer Concentration | Notes |
|---|---|---|---|
| Kobe | Local universities, innovation programs, and nearby corporate R&D professionals | Medium | Host city benefit for local attendance and regional research engagement |
| Hyogo Prefecture / Kansai region | Attendees from Kobe, Osaka, Kyoto, and surrounding innovation corridors | High | Official site notes Kobe is less than an hour by train from Osaka and Kyoto |
| Japan national | Researchers, professors, graduate labs, and technology companies from across Japan | High | Conference history in multiple Japanese cities supports national academic familiarity |
| Asia-Pacific | Regional academic and industrial participants in AI, VR, HCI, and simulation | Medium to High | Past editions include Singapore, indicating broader regional footprint |
| Global | International scholars and industry researchers publishing in AI/VR fields | Medium | International conference format and English-language publication pathway support global participation |
3. Audience Reach
| Reach Level | Assessment | Explanation |
|---|---|---|
| Global | Primary classification | The event is positioned as an international conference and publishes accepted papers through Springer’s SIST series, which supports international academic and industry participation. |
| Asia-Pacific | Secondary concentration | Japan host location and prior conference history across Japan and Singapore suggest especially strong regional accessibility and relevance. |
4. Sample Buyer Companies and Websites
Current-year attendee, sponsor, exhibitor, speaker-organization, or buyer directory details were not provided in the official event content supplied for this research. The table below is therefore limited to prospecting-relevant organizations with strong market fit to the event theme. Attendance is not confirmed unless stated otherwise.
| Buyer Company / Organization | Buyer Type | Why It Is Relevant | Website | Best Job Titles to Target | Evidence Level |
|---|---|---|---|---|---|
| Sony Group Corporation | Enterprise technology / XR ecosystem buyer | Relevant to AI, immersive media, sensors, visualization, and next-generation interaction platforms | sony.com | XR Product Manager, AI R&D Director, Innovation Lead | Strong Market Fit, Attendance Not Confirmed |
| Panasonic Holdings Corporation | Industrial technology buyer | Strong fit for applied AI, immersive training, smart devices, and digital experience systems | panasonic.com | Innovation Manager, R&D Director, Product Strategy Lead | Strong Market Fit, Attendance Not Confirmed |
| NTT DATA | Enterprise solutions buyer / systems integrator | Relevant for AI solution deployment, digital twin initiatives, public sector innovation, and enterprise transformation | nttdata.com | Head of Innovation, AI Practice Director, Solutions Architect | Strong Market Fit, Attendance Not Confirmed |
| Fujitsu | Enterprise technology buyer | Strong alignment with AI, enterprise computing, simulation, and applied research partnerships | fujitsu.com | AI Program Director, CTO Office Lead, Research Partnerships Manager | Strong Market Fit, Attendance Not Confirmed |
| NEC Corporation | Enterprise and public-sector technology buyer | Relevant to AI, vision systems, human-computer interaction, and digital infrastructure | nec.com | Director AI Solutions, Innovation Executive, XR Program Lead | Strong Market Fit, Attendance Not Confirmed |
| Toyota Motor Corporation | Industrial R&D / simulation buyer | Relevant for AI-enabled simulation, training, HMI, and immersive engineering applications | toyota-global.com | R&D Program Manager, Simulation Lead, Advanced Technology Director | Strong Market Fit, Attendance Not Confirmed |
| Honda Motor Co., Ltd. | Automotive innovation buyer | Potential buyer of AI, immersive design tools, user-behaviour systems, and simulation technologies | global.honda | Advanced Engineering Manager, Digital Innovation Lead, HMI Director | Strong Market Fit, Attendance Not Confirmed |
| Mitsubishi Electric | Industrial systems buyer | Relevant to AI, industrial visualization, automation interfaces, and digital environments | mitsubishielectric.com | Industrial Innovation Director, AI Product Manager, Digital Systems Lead | Strong Market Fit, Attendance Not Confirmed |
| KDDI Corporation | Telecom and digital services buyer | AI, edge, immersive communication, and platform opportunities align with conference themes | kddi.com | Digital Innovation Director, Platform Partnerships Manager, XR Service Lead | Strong Market Fit, Attendance Not Confirmed |
| Rakuten Group | Digital platform buyer | Relevant to AI experience design, user behaviour analytics, and immersive commerce experimentation | global.rakuten.com | Product Director, AI Strategy Lead, Innovation Partnerships Manager | 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 | Director of Research | R&D | Director | Owns technical evaluation, external collaboration, and research tooling decisions |
| 2 | AI R&D Manager | Artificial Intelligence / Engineering | Manager | Core buyer/influencer for models, infrastructure, and AI development tools |
| 3 | XR / VR Product Manager | Product | Manager | Evaluates immersive technologies, content pipelines, and application fit |
| 4 | CTO | Executive / Technology | C-Level | Senior technology sponsor for innovation pilots, partnerships, and platform adoption |
| 5 | Head of Innovation | Innovation / Strategy | Head / VP | Drives external scanning and identifies new AI/VR deployment opportunities |
| 6 | Professor / Principal Investigator | Academic Research | Senior | Key decision-maker for academic procurement, partnerships, and lab collaborations |
| 7 | Program Manager | Applied Research / Delivery | Manager | Useful target for pilots, deployment projects, and sponsored research |
| 8 | Partnerships Director | Business Development / Alliances | Director | Important for technology collaboration, ecosystem building, and channel discussions |
| Priority | Apollo Industry | Why It Fits the Event | Best Buyer Use Case |
|---|---|---|---|
| 1 | Information Technology & Services | Strongest fit for applied AI, enterprise software, and systems delivery | AI platforms, digital transformation, systems integration |
| 2 | Computer Software | Direct alignment with AI models, developer tools, 3D engines, and simulation software | Research software, XR applications, analytics tools |
| 3 | Research | Fits labs, institutes, and applied research organizations | Academic partnerships, grant collaboration, lab tooling |
| 4 | Higher Education | Universities are a core conference audience segment | Lab equipment, software licenses, research collaboration |
| 5 | Computer Hardware | Relevant for immersive devices, sensors, edge AI, and specialized compute | VR hardware, workstation environments, peripherals |
| 6 | Consumer Electronics | Relevant for device makers and interface technology vendors | Headsets, displays, capture systems, interaction devices |
| 7 | Electrical/Electronic Manufacturing | Applies to sensing, hardware integration, and component innovation | Embedded AI, imaging, tracking, interface systems |
| 8 | Industrial Automation | Relevant for simulation, digital twin, training, and operational visualization use cases | Training simulation, operational AI, smart environment control |
| 9 | Automotive | Automotive R&D uses AI, simulation, HMI, and immersive testing extensively | Driver interaction, prototyping, virtual validation |
| 10 | Telecommunications | Telecoms are relevant for immersive services, edge delivery, and connectivity innovation | XR streaming, collaboration, edge computing |
| 11 | Education Management | Useful for institutions adopting immersive learning and AI learning systems | Training environments, educational simulation, content systems |
| 12 | Medical Devices | Applicable where AI/VR supports training, visualization, and intervention planning | Simulation, clinical education, interface design |
6. Estimated Attendance
| Metric | Figure | Status | Source / Basis | Notes |
|---|---|---|---|---|
| Estimated total footfall | Attendance figure not publicly confirmed by the organizer. | Unconfirmed | Official website content provided | No attendee count visible in supplied official text |
| Exhibitor count | Not publicly confirmed | Unconfirmed | Official website content provided | This appears to be a conference format, not a large exhibition-led event |
| Buyer count | Not publicly confirmed | Unconfirmed | Official website content provided | Conference is researcher-centric; buyer presence is likely indirect through R&D and innovation functions |
| Speaker count | Not publicly confirmed in provided text | Unconfirmed | Official website content provided | Menu references keynotes and invited speakers, but headcount was not supplied |
| Sponsor count | Not publicly confirmed in provided text | Unconfirmed | Official website content provided | Website contains “Sponsored by” and “Supported by” headings but no names in the supplied content |
| Historical attendance | Not publicly confirmed | Historical data unavailable in supplied text | Official website content provided | Series continuity is confirmed; numerical attendance is not |
7. Key Focus Areas and Buyer Engagement
| Focus Area | Typical Buyer Need | Buyer Engagement Opportunity | Relevant Supplier Offering |
|---|---|---|---|
| Artificial Intelligence | Model development, experimentation, data handling, applied intelligence | Demo practical use cases and enterprise/research collaboration | AI platforms, MLOps, computer vision, analytics tools |
| Virtual Reality | Immersive environment creation, user interaction, realistic simulation | Show hardware/software compatibility and scenario-based outcomes | Headsets, interaction systems, rendering tools, content pipelines |
| Systems and implementation | Performance, architecture, deployment, and integration | Position solutions around reliability, scale, and interoperability | Infrastructure, compute, APIs, device integration services |
| Content creation and modelling | 3D assets, simulation environments, modelling workflows | Engage product teams, studios, and visualization researchers | 3D tools, design platforms, content management workflows |
| Cognitive aspects and user behaviour | Measurement, testing, perception analysis, HCI optimization | Offer research-grade testing capabilities and analytics | Eye-tracking, usability platforms, behavioural analytics, sensors |
| Interactive and responsive environments | Low-latency interaction, adaptive systems, human-machine response | Target technical teams solving interface and responsiveness issues | Edge systems, real-time engines, input/output technologies |
| Applications and use cases | Industry deployment, education, training, simulation, product innovation | Frame value by vertical outcomes rather than pure technical features | Industry-specific AI/VR solutions, consulting, integration, pilot design |
Lead Quality Assessment
| Factor | Assessment | Explanation |
|---|---|---|
| Buyer relevance | High | Relevant if selling to research, innovation, product, engineering, or advanced technology teams rather than mass-market procurement. |
| Decision-maker availability | Medium | Likely to include technical influencers and research leaders; less likely to be dominated by classic procurement teams. |
| Data collection potential | Medium | Useful for targeted account-building, but attendee counts and public directories were not confirmed in the supplied source. |
| Apollo targeting potential | High | Strong keyword, industry, and title-based targeting is possible across AI, XR, R&D, and higher education accounts. |
| Geographic targeting potential | High | Japan and broader Asia-Pacific filtering is logical due to location and series history. |
| Best outreach approach | High-value consultative outreach | Lead with research enablement, pilot value, integration support, and innovation outcomes instead of generic event-sales messaging. |
| Overall lead quality | High | Best for niche, high-intent, technically sophisticated outreach in AI/VR ecosystems. |
| Best use case | Account-based outreach and partnership mapping | Most useful for building shortlists of labs, innovation teams, and enterprise R&D buyers. |
| Limitations / risks | Medium | Public attendance transparency is limited; this is not a broad exhibition with a large confirmed buyer directory in the supplied source. |
Apollo.io Targeting Recommendation
| Filter Type | Recommended Filters | Purpose |
|---|---|---|
| Apollo industries | Information Technology & Services; Computer Software; Research; Higher Education; Computer Hardware; Consumer Electronics; Electrical/Electronic Manufacturing; Industrial Automation; Automotive; Telecommunications; Education Management; Medical Devices | Capture the strongest AI, VR, simulation, and research-buying environments |
| Departments | Engineering; Information Technology; Research; Product Management; Innovation; Business Development | Focus on technical and strategic buyers |
| Seniority | C-Level; VP; Head; Director; Manager; Owner for specialist firms | Balance budget authority with technical influence |
| Job titles | CTO, Director of Research, AI R&D Manager, Machine Learning Manager, XR Product Manager, VR Product Manager, Head of Innovation, Principal Investigator, Research Scientist, Program Manager, Partnerships Director, Solutions Architect | Targets the most relevant innovation and adoption roles |
| Geography | Japan first; secondary Asia-Pacific markets including Singapore, South Korea, Taiwan, China, Australia | Aligns with likely event participation footprint |
| Employee size | 51–200; 201–500; 501–1,000; 1,001–5,000; 5,001+ | Covers research-driven scale-ups through major enterprise R&D organizations |
| Keywords | artificial intelligence, virtual reality, XR, AR/VR, spatial computing, immersive, simulation, computer vision, digital twin, HCI, machine learning, interactive environments | Improves thematic precision beyond broad industry filters |
| Technologies, if relevant | AI/ML stack, cloud platforms, 3D engines, computer vision, simulation software, edge computing | Useful for narrowing enterprise innovation targets |
| Revenue range, if relevant | Mid-market to enterprise; prioritize organizations with active R&D or innovation budgets | Improves buyer readiness and solution-budget fit |
| Company type | Public companies, private innovation firms, universities, applied research institutions | Covers both commercial and research-led acquisition paths |
Suggested Apollo Search Logic: (“artificial intelligence” OR “machine learning” OR “virtual reality” OR XR OR “spatial computing” OR simulation OR “computer vision” OR “digital twin”) AND (research OR innovation OR product OR lab OR immersive) with geography filtered to Japan first, then broader APAC, and seniority restricted to Director+ plus research managers and principal investigators.
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Sources & Verification Notes
| Source | Type | What It Verified | Reliability |
|---|---|---|---|
| AIVR 2026 Official Website | Official event website | Confirmed event title, host city, country, conference dates, event theme, conference tracks, key deadlines, publication pathway, and conference history | High |
| Provided official website text extract | Primary-source content supplied by user | Validated that venue name, organizer name, attendance figures, sponsor names, and participant lists were not visible in the supplied source text | High |
Suitability for B2B attendee list building: Moderate. The conference is highly relevant for targeted AI/VR prospecting and partnership mapping, but the supplied official source does not provide a public current-year attendee directory or attendance volume.
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