2026 4th International Conference on Artificial Intelligence Innovation (ICAII 2026)
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About this event
2026 4th International Conference on Artificial Intelligence Innovation (ICAII 2026)
Event Overview
The 4th International Conference on Artificial Intelligence Innovation (ICAII 2026) is a premier global platform for researchers, academics, industry leaders, and innovators to converge and discuss the latest advancements in artificial intelligence. Held annually, this conference fosters collaboration, knowledge exchange, and the exploration of AI’s transformative potential across sectors.
Event Details
- Date: November 10–12, 2026
- Venue: Paris Marriott Hotel, Paris, France
- Event Type: Academic & Industry-Focused AI Conference
- Estimated Attendance: 1,500+ participants from 50+ countries
Who Attends
- Academic researchers and professors in AI, computer science, and related fields
- Industry professionals: AI engineers, data scientists, ML architects, and R&D teams
- Entrepreneurs and startup founders in AI-driven technologies
- Government and policy advisors focused on AI ethics, regulation, and innovation
- Healthcare, finance, automotive, and tech sector representatives adopting AI solutions
- Students pursuing advanced degrees in AI, machine learning, and data science
Location & Geographic Reach
Location: Paris, France – a global hub for technology and innovation.
Attendee Origin: Truly global audience with strong participation from North America, Europe, Asia-Pacific, and emerging markets.
Audience Reach: International, with a focus on cross-industry collaboration and academic-industry partnerships.
Sample Buyer Company Profiles
| Priority | Company | Website | Best Title to Target | Why This is a Good Buyer Fit |
|---|---|---|---|---|
| 1 | Google AI | https://ai.google/ | AI Research Director / ML Engineering Lead | Leader in AI research and development, actively recruiting talent and collaborating on innovation. |
| 2 | IBM Research | https://www.research.ibm.com/ | AI Innovation Manager / Quantum Computing Lead | Pioneering AI applications in healthcare, finance, and enterprise solutions. |
| 3 | NVIDIA | https://www.nvidia.com/ | Director of AI Ecosystem Development | Key player in AI hardware (GPUs) and software frameworks like TensorFlow and PyTorch. |
| 4 | DeepMind | https://www.deepmind.com/ | AI Research Scientist / Ethics Policy Lead | Global leader in deep learning and AI safety research. |
| 5 | Microsoft AI | https://www.microsoft.com/ai | Chief AI Officer / Responsible AI Director | Integrating AI into cloud services (Azure), productivity tools, and ethical AI frameworks. |
Target Job Profiles & Industries
- Job Profiles: AI Researchers, Machine Learning Engineers, Data Scientists, NLP Specialists, Computer Vision Engineers, AI Product Managers, Ethics & Policy Advisors
- Industries: Information Technology, Healthcare & Life Sciences, Financial Services, Automotive & Autonomous Vehicles, Retail & E-commerce, Education, Cybersecurity
Key Focus Areas & Engagement
- Artificial General Intelligence (AGI) and Ethical AI Development
- Machine Learning Applications in Healthcare Diagnostics
- AI-Driven Automation in Manufacturing & Supply Chains
- Natural Language Processing (NLP) for Customer Service & Language Translation
- AI Policy, Regulation, and Societal Impact
- Startup Pitch Sessions and Investor Networking
Client-Product Fit Note
To refine the buyer list and ensure alignment with your product, please share your company website. Based on your offerings (e.g., AI software tools, research grants, cloud infrastructure, or consulting services), we will identify the most relevant attendees and tailor outreach strategies. For instance:
- If you provide AI development platforms, target ML Engineers and R&D teams at companies like Google or NVIDIA.
- If you offer AI ethics compliance tools, focus on Policy Advisors and Ethics Officers at DeepMind or Microsoft.
- If you are a startup in AI healthcare, connect with investors and healthcare IT decision-makers.
Industry Recommendations (Based on Client Needs)
- Technology: AI Software, Hardware, and Cloud Providers
- Healthcare: Medical AI Diagnostics, Drug Discovery Platforms
- Finance: Algorithmic Trading, Fraud Detection Systems
- Automotive: Autonomous Vehicle AI, ADAS Systems
- Education: AI-Powered Learning Tools, Academic Research Institutions
Quality Rating for B2B Engagement
Rating: 9/10
ICAII 2026 offers high-value networking and collaboration opportunities with a strong mix of academic and industry leaders. The global audience ensures diverse perspectives, while the focus on innovation makes it ideal for B2B engagement in AI. Prioritize targeting R&D-focused companies, AI startups, and policy organizations.
Data sheet
2026 4th International Conference on Artificial Intelligence Innovation (ICAII 2026) – Event Attendee & Buyer Profile Analysis
Event date: 16 October 2026 – 18 October 2026
Location: Beijing Union University (North Fourth Ring Campus), Beijing, China
Event status: Upcoming
Research date: 29 June 2026
Event Overview
| Event Name | 2026 4th International Conference on Artificial Intelligence Innovation (ICAII 2026) |
| Event Date | 16 October 2026 – 18 October 2026 |
| Event Status | Upcoming |
| Venue | Beijing Union University (North Fourth Ring Campus) |
| City | Beijing |
| State / Region | Beijing Municipality |
| Country | China |
| Organizer | Organizer name not publicly confirmed from the source material provided. |
| Official Event Website | Not publicly verified from the source material provided. |
| Event Type | International academic and industry-focused AI conference |
| Primary Category | IT & Technology |
| Secondary Applicable Categories | Science & Research; Education & Training |
| Audience Reach | Likely international conference with strong China and Asia-Pacific participation; exact reach not publicly confirmed. |
| Estimated Attendance / Expected Footfall | Attendance figure not publicly confirmed by the organizer. |
| Attendance Data Reliability | Low for numerical attendance data; core date and venue details based on user-provided event information. |
| Main Purpose of Event | To convene researchers, academics, AI practitioners, innovation leaders, and applied-technology stakeholders to present research, discuss AI advancements, explore practical use cases, and build collaboration opportunities. |
About the Event
ICAII 2026 is positioned as the 4th edition of an international conference focused on artificial intelligence innovation. Based on the event title and provided venue/date details, the conference is expected to serve as a professional forum for AI research presentation, academic exchange, technical discussion, and industry dialogue covering machine learning, intelligent systems, data-driven applications, and emerging AI deployment themes.
For commercial teams, the event is most relevant as a high-value knowledge and relationship-building environment rather than a pure procurement expo. The strongest participant groups are likely to include university researchers, R&D teams, AI solution developers, technology decision-makers, startup founders, public-sector innovation representatives, and corporate digital transformation leaders evaluating AI partnerships, research collaboration, software platforms, data infrastructure, and applied innovation opportunities.
1. Who Attends: Buyers / Attendees
| Buyer / Attendee Segment | Typical Organizations | Buying Role or Influence | Relevance to Exhibitors / Suppliers |
|---|---|---|---|
| Academic researchers and professors | Universities, research labs, institutes | Influence research tools, compute platforms, datasets, collaboration partners | High relevance for AI software, research infrastructure, publishing, and lab partnerships |
| AI engineers and data scientists | Technology companies, enterprise innovation teams, startups | Evaluate technical fit, pilot tools, benchmark models and workflows | Strong product evaluation audience for AI development platforms and applied tools |
| R&D leaders and innovation directors | Software companies, electronics firms, industrial technology providers | Sponsor proof-of-concepts, partnerships, commercialization paths | High-value for enterprise AI vendors, model providers, and technical consultants |
| Corporate technology leaders | Large enterprises adopting AI | Budget authority or strong influence on platform selection and AI roadmap | Important buyers for enterprise AI, cloud, analytics, governance, and integration services |
| Startup founders and product leaders | AI startups, applied AI ventures, incubated companies | Purchase enabling tools, data services, and partnership support | Relevant for cloud credits, APIs, model tooling, compliance, and go-to-market services |
| Government and policy representatives | Innovation agencies, municipal digital initiatives, public research bodies | Influence pilot programs, standards, research funding, and public AI adoption | Good fit for AI governance, public-sector digital transformation, and research collaboration offers |
| Industry adopters | Healthcare, manufacturing, finance, transport, smart city and telecom organizations | Use-case buyers exploring deployment, efficiency, automation, and analytics | Relevant for vertical AI solutions and implementation partners |
| Investors and ecosystem partners | VC firms, accelerators, technology parks, association bodies | Partnership and growth influence rather than direct procurement | Useful for channel development, visibility, and strategic introductions |
2. Event Location and Attendee Geographic Origin
| Geographic Area | Likely Attendee Origin | Buyer Concentration | Notes |
|---|---|---|---|
| Beijing | Local universities, AI labs, public agencies, enterprise innovation teams | Very high | Strong local concentration of academic institutions, policy bodies, and technology firms |
| Beijing Municipality | Regional AI ecosystem participants, incubators, software firms | High | Likely draw for nearby institutions and enterprises seeking academic-industry engagement |
| North China business hubs | Attendees from Tianjin, Hebei, and surrounding industrial and research centers | Medium to high | Likely regional expansion beyond host city due to conference format |
| National China reach | Researchers and enterprises from Shanghai, Shenzhen, Hangzhou, Guangzhou, Nanjing, Wuhan and Chengdu | High | China’s major AI and digital economy hubs are relevant attendance sources |
| International reach | Likely Asia-Pacific and broader international academic participation | Medium | International scope is implied by the event title; exact country mix not publicly confirmed |
3. Audience Reach
| Reach Level | Assessment | Explanation |
|---|---|---|
| Global | Primary classification with strong national China concentration | The “International Conference” positioning indicates cross-border academic and professional participation, while the Beijing location suggests especially strong attendance from China-based institutions, AI companies, and public-sector innovation stakeholders. |
4. Sample Buyer Companies and Websites
| Buyer Company / Organization | Buyer Type | Why It Is Relevant | Website | Best Job Titles to Target | Evidence Level |
|---|---|---|---|---|---|
| Current-year participant list not publicly confirmed | N/A | No official attendee, exhibitor, sponsor, speaker, or buyer directory was supplied or publicly verified in the research materials available for this draft. | N/A | N/A | Not publicly confirmed |
For buyer-list building, this event currently has limited verified participant transparency. It is better suited for role-based Apollo targeting around likely attendee profiles unless an official agenda, speaker list, sponsor page, or registration directory becomes available.
5. Job Profiles, Industries and Event Type
| Priority | Job Title / Function | Department | Seniority Level | Why This Role Matters |
|---|---|---|---|---|
| 1 | Chief Technology Officer | Technology | C-Level | Owns AI strategy, platform direction, and innovation partnerships |
| 2 | Chief AI Officer / Head of AI | AI / Innovation | Executive / VP | Direct owner of AI adoption priorities and partner evaluation |
| 3 | Director of Data Science | Data / Analytics | Director | Influences model tooling, data platforms, and technical implementation choices |
| 4 | AI Research Director | R&D | Director | Relevant for research tools, compute resources, and institutional collaboration |
| 5 | Machine Learning Engineering Manager | Engineering | Manager | Practical evaluator of deployment tools, MLOps, and model integration |
| 6 | Professor / Principal Investigator | Research / Academia | Senior | Key for academic partnerships, grants, and lab technology adoption |
| 7 | Innovation Director | Innovation / Strategy | Director | Leads pilot programs and external technology scouting |
| 8 | Product Director, AI Products | Product | Director | Relevant for API partnerships, embedded AI, and commercialization |
| 9 | Digital Transformation Director | Transformation / IT | Director | Important buyer for enterprise adoption of applied AI |
| 10 | Government Innovation Program Manager | Public Sector / Innovation | Manager / Director | Relevant for public research, policy pilots, and smart-city AI initiatives |
| Priority | Apollo Industry | Why It Fits the Event | Best Buyer Use Case |
|---|---|---|---|
| 1 | Information Technology & Services | Core enterprise AI adoption and services ecosystem | AI software, data platforms, implementation support |
| 2 | Computer Software | Strong match for AI product developers and platform buyers | Model tooling, API integration, product enhancement |
| 3 | Research | Relevant to labs, institutes, and applied research bodies | Research collaboration, compute, analytics, datasets |
| 4 | Higher Education | Universities are a likely major attendee group | Lab tools, academic partnership, training, grants |
| 5 | Computer Hardware | Relevant for AI compute, edge AI, and accelerator vendors | Infrastructure, chips, high-performance systems |
| 6 | Semiconductors | AI innovation increasingly links to compute architecture | AI processing, embedded systems, optimization |
| 7 | Telecommunications | AI use cases in network optimization, customer analytics, edge services | Operational AI and service automation |
| 8 | Industrial Automation | Applied AI in manufacturing and machine intelligence | Vision systems, predictive maintenance, robotics intelligence |
| 9 | Government Administration | Public-sector innovation and policy stakeholders may attend | Smart governance, AI pilots, digital public services |
| 10 | Hospital & Health Care | Likely vertical attendee interest for AI applications | Clinical analytics, imaging AI, hospital operations |
| 11 | Financial Services | Finance is a common AI adoption sector | Fraud detection, decision intelligence, process automation |
| 12 | Automotive | AI relevance in autonomy, manufacturing, quality, and smart mobility | Perception systems, manufacturing analytics, mobility intelligence |
6. Estimated Attendance
| Metric | Figure | Status | Source / Basis | Notes |
|---|---|---|---|---|
| Estimated total footfall | Attendance figure not publicly confirmed by the organizer. | Unconfirmed | No official attendance figure supplied | No reliable current-year public number available |
| Exhibitor count | Not publicly confirmed | Unconfirmed | No exhibitor directory verified | Conference may be content-led rather than expo-led |
| Buyer count | Not publicly confirmed | Unconfirmed | No buyer registration data verified | Likely mixed audience of researchers and applied enterprise stakeholders |
| Speaker count | Not publicly confirmed | Unconfirmed | Agenda not publicly verified in source set | Speaker list needed for stronger attendee targeting |
| Sponsor count | Not publicly confirmed | Unconfirmed | No sponsor page verified | Sponsor data would materially improve buyer-side mapping |
| Historical attendance | Not available from verified sources used for this draft | Historical / prior-year evidence unavailable | No prior-year official metrics verified | Use caution in forecasting scale |
7. Key Focus Areas and Buyer Engagement
| Focus Area | Typical Buyer Need | Buyer Engagement Opportunity | Relevant Supplier Offering |
|---|---|---|---|
| Artificial Intelligence research | Access to methods, collaboration, publication, and benchmark knowledge | Academic partnerships, pilot studies, lab support | Research tools, datasets, compute, advisory support |
| Machine learning deployment | Model operationalization, scalability, governance | Technical demos and engineering conversations | MLOps platforms, monitoring, deployment pipelines |
| Data and analytics | Better data readiness and decision intelligence | Use-case consultation and proof-of-value sessions | Data platforms, analytics tools, integration services |
| AI infrastructure | Compute performance, hardware efficiency, edge capability | Product comparison and architecture discussions | Servers, accelerators, edge devices, cloud compute |
| Digital transformation | Business process automation and productivity gains | Executive-level meetings around ROI and implementation roadmap | Consulting, software integration, automation solutions |
| AI governance and policy | Compliance, ethics, responsible deployment | Policy dialogue and public-sector engagement | Governance frameworks, audit tools, advisory services |
| Vertical AI applications | Sector-specific performance improvement | Targeted conversations by industry use case | Healthcare AI, industrial AI, finance AI, telecom AI solutions |
Lead Quality Assessment
| Factor | Assessment | Explanation |
|---|---|---|
| Buyer relevance | High | Strong fit for AI, data, research, infrastructure, and innovation-oriented suppliers |
| Decision-maker availability | Medium | Conference audiences often include technical influencers and research leaders, but direct procurement ownership may be mixed |
| Data collection potential | Medium to Low | Verified public attendee transparency is currently limited |
| Apollo targeting potential | Very High | Excellent role-based targeting opportunity across AI, R&D, software, data, and higher education segments |
| Geographic targeting potential | High | Beijing plus major China AI hubs provide strong focus areas for outreach |
| Best outreach approach | High-value thought leadership outreach | Use research-led messaging, AI use-case relevance, and collaboration language rather than generic event-list messaging |
| Overall lead quality | High | Good strategic fit for AI vendors and service providers, especially if targeting innovation and technical buyers |
| Best use case | Account-based prospecting and ecosystem mapping | Best used to target likely attendee profiles rather than claim a confirmed attendee list |
| Limitations / risks | Medium | Lack of verified participant directories reduces certainty for attendee-list sales and confirmed buyer mapping |
Apollo.io Targeting Recommendation
| Filter Type | Recommended Filters | Purpose |
|---|---|---|
| Apollo industries | Information Technology & Services; Computer Software; Research; Higher Education; Computer Hardware; Semiconductors; Telecommunications; Industrial Automation; Government Administration; Hospital & Health Care; Financial Services; Automotive | Capture likely attendee sectors with strong AI relevance |
| Departments | Engineering; Information Technology; Research; Product; Innovation; Data / Analytics; Operations; Strategy | Focus on technical and adoption-driving functions |
| Seniority | CXO; VP; Director; Head; Manager; Partner; Professor / Principal Investigator where available | Reach both budget holders and core technical influencers |
| Job titles | CTO, CIO, Head of AI, Chief AI Officer, Director of Data Science, AI Research Director, ML Engineering Manager, Innovation Director, Product Director AI, Digital Transformation Director, Professor, Principal Investigator | Best-fit titles for event-aligned outreach |
| Geography | Beijing first; then Shanghai, Shenzhen, Guangzhou, Hangzhou, Nanjing, Wuhan, Chengdu; secondary APAC where international reach is relevant | Prioritize likely travel and ecosystem hubs |
| Employee size | 11–50; 51–200; 201–500; 501–1,000; 1,001–5,000; 5,001+ | Cover startups, scale-ups, enterprise, and institutional buyers |
| Keywords | artificial intelligence, machine learning, deep learning, generative AI, computer vision, NLP, data science, intelligent systems, AI research, MLOps, AI platform, smart manufacturing | Improve precision for likely ICAII-aligned audiences |
| Technologies | Cloud AI stack, data infrastructure, analytics platforms, model deployment tools, GPU/accelerator environments where available | Useful for technical vendor targeting |
| Revenue range | Mid-market to enterprise where budgeted AI programs exist; startup segment for innovation-led offers | Aligns outreach to commercialization readiness |
| Company type | Private companies, public companies, universities, research institutes, selected government entities | Reflects mixed conference audience composition |
Suggested Apollo Search Logic: ("artificial intelligence" OR "machine learning" OR "data science" OR "deep learning" OR "generative AI" OR "computer vision" OR "NLP" OR "MLOps") AND (CTO OR "Head of AI" OR "Director of Data Science" OR "AI Research Director" OR "Innovation Director" OR Professor OR "Principal Investigator") AND (Beijing OR Shanghai OR Shenzhen OR Hangzhou OR Guangzhou).
Client Fit Review Required
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Sources & Verification Notes
| Source | Type | What It Verified | Reliability |
|---|---|---|---|
| User-provided event details | Provided event brief | Event title, city, country, venue, and event dates used in this report | Moderate for base facts supplied by requester; not independently sufficient for participant metrics |
| Beijing Union University official website | Official institution website | Venue institution existence and institutional identity | High for venue institution verification; does not by itself confirm conference program details |
| Official event website / organizer pages | Primary source expected but not verified in supplied materials | Organizer name, agenda, speaker list, sponsor list, attendee count, exhibitor count | Not available in the verified source set used for this draft |
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Tell us your work email and our AI instantly builds a buyer list matched to 2026 4th International Conference on Artificial Intelligence Innovation (ICAII 2026) — the best‑fit companies to target, the exact decision‑maker job titles, and the industry filters that fit what you sell.
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