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About this event

AI Con USA 2026

Event type: Artificial Intelligence, Machine Learning, Data Science, Enterprise Technology, Automation, Digital Transformation, Software & Innovation

Estimated attendance: Likely several thousand attendees, with a strong mix of enterprise buyers, technical decision-makers, founders, product leaders, data teams, solution providers, and AI ecosystem stakeholders.

Audience profile: This is typically a high-value B2B technology event, especially attractive for companies selling AI tools, analytics platforms, cloud services, automation software, data infrastructure, cybersecurity, developer tools, consulting, and enterprise transformation solutions.

1️⃣ Who attends: Buyers / Attendees

AI Con USA 2026 is best understood as a business and technology decision-maker event rather than a general consumer exhibition. The strongest buying audience usually comes from organizations that are actively exploring, implementing, scaling, or monetizing artificial intelligence across their operations.

The main attendee groups you should expect include:

  • C-suite and executive leadership such as CEOs, CTOs, CIOs, Chief Data Officers, Chief AI Officers, and innovation leaders.
  • Technology and product teams including engineering managers, AI architects, ML engineers, data scientists, platform leads, and solution architects.
  • Business transformation leaders responsible for automation, digital strategy, operations optimization, and enterprise modernization.
  • Data and analytics teams focused on predictive modeling, reporting, governance, business intelligence, and AI adoption.
  • Security, compliance, and risk teams concerned with responsible AI, privacy, governance, model safety, and enterprise controls.
  • Consulting and systems integration firms that advise clients on AI strategy, implementation, and change management.
  • Startups, venture-backed companies, and product innovators seeking partnerships, investment, tools, and enterprise visibility.
  • Enterprise buyers from vertical industries such as healthcare, finance, retail, manufacturing, logistics, telecom, education, media, government, and professional services.

For attendee-list monetization, the best buyers are not just “people interested in AI.” The highest-value targets are the ones with budget authority or active project ownership: AI transformation leads, enterprise architects, data platform managers, innovation directors, product leaders, and digital strategy executives.

2️⃣ Where the show is happening + attendee geographic origin

Location: The exact venue for AI Con USA 2026 should be confirmed from the official event page, because this title can be used for a conference format that may shift by city or venue.

Attendee origin: Based on the event positioning, the audience is likely national with global interest. AI events in the U.S. typically attract:

  • Domestic attendees from major U.S. technology hubs such as California, New York, Texas, Washington, Massachusetts, Illinois, Georgia, and Florida.
  • Traveling corporate buyers from across North America.
  • International attendees from Europe, India, the Middle East, Canada, and Asia if the event has a strong thought-leadership and enterprise-technology profile.

If the conference is held in a major city like San Francisco, New York, Las Vegas, Austin, Chicago, or Boston, the local draw will likely be strong, but the real value will come from national and global travel buyers attending for AI strategy, product discovery, and partnership development.

3️⃣ Audience reach: Local / National / Global

Reach type: National with global relevance

AI is a globally relevant subject, but the buyer mix usually depends on the event’s scale and speaker lineup. For an event named AI Con USA 2026, the strongest reach classification is generally:

  • Local: Yes, if the event is in a major metro area with a dense tech ecosystem.
  • National: Definitely. This is the primary reach category.
  • Global: Also possible, especially if the event covers enterprise AI, generative AI, model deployment, governance, and real-world commercial use cases.

That makes this a strong event for selling buyer/attendee data to vendors serving enterprise innovation, SaaS, cloud, analytics, automation, and digital transformation markets.

4️⃣ Sample buyer company names + websites

Below is a practical sample buyer list of companies that would likely be strong matches for AI Con USA 2026. These are buyer-style targets only, chosen for their likely interest in AI, enterprise tech, data infrastructure, automation, or digital transformation.

Priority Company Website Best Title to Target Why This is a Good Buyer Fit
1 Microsoft microsoft.com Director, AI Strategy / Cloud Solution Architect / Enterprise Innovation Lead Strong enterprise AI, cloud, developer, and productivity platform buyer fit.
2 Google Cloud cloud.google.com AI Product Marketing Manager / Industry Solutions Lead Excellent fit for AI infrastructure, analytics, and enterprise transformation.
3 Amazon Web Services aws.amazon.com GenAI Specialist / Partner Solutions Manager / Enterprise Account Executive High alignment with cloud AI, machine learning, and enterprise adoption.
4 IBM ibm.com AI Partnerships Manager / Data & AI Sales Leader Longstanding enterprise AI, consulting, and governance relevance.
5 NVIDIA nvidia.com Developer Relations Manager / AI Ecosystem Manager Very strong fit for AI computing, model training, and enterprise acceleration.
6 Salesforce salesforce.com Product Marketing Director, AI / CRM Innovation Lead Buyer fit for generative AI, customer intelligence, and workflow automation.
7 Oracle oracle.com Cloud AI Solutions Director / Data Platform Sales Lead Strong enterprise data, database, and AI platform alignment.
8 Adobe adobe.com AI Product Manager / Digital Experience Strategy Lead Great fit for creative AI, marketing automation, and digital experience solutions.
9 ServiceNow servicenow.com Workflow Automation Strategist / AI Solutions Manager High relevance for enterprise workflow AI and operational automation.
10 Palantir palantir.com Government/Enterprise AI Sales Lead / Solutions Engineer Excellent fit for data platforms, decision intelligence, and AI operations.
11 Databricks databricks.com Field Marketing Manager / Data Platform Partnerships Lead Very strong buyer for data engineering, ML, and enterprise AI stacks.
12 Snowflake snowflake.com AI/ML Product Marketing Manager / Strategic Alliances Lead Good fit for AI data cloud, analytics, and enterprise data governance.
13 Accenture accenture.com Managing Director, AI Transformation / Technology Strategy Lead Consulting-heavy buyer with active AI advisory and implementation work.
14 Deloitte deloitte.com AI Advisory Partner / Digital Transformation Director Strong fit for enterprise AI strategy, governance, and client delivery.
15 PwC pwc.com Innovation Leader / AI & Data Strategy Partner Relevant for AI consulting, audit-tech, risk, and enterprise transformation.
16 IBM Consulting ibm.com/services Transformation Director / AI Consulting Lead Strong AI implementation and enterprise modernization buyer.
17 HPE hpe.com AI Infrastructure Product Manager / Enterprise Sales Director Good fit for hybrid cloud, compute, storage, and AI infrastructure buying.
18 Cisco cisco.com AI Networking Strategy Lead / Product Marketing Manager Relevant for AI-enabled infrastructure, networking, security, and collaboration.

Top 5 best sample buyers to show first: Microsoft, AWS, NVIDIA, Databricks, Accenture. These cover the strongest buyer categories across cloud, compute, data, and enterprise AI services.

5️⃣ Job profiles, industries & event type

This event attracts a highly qualified audience, so the best targeting strategy is to prioritize titles connected to AI strategy, technical implementation, data governance, and business transformation.

Best job profiles to target:

  • Chief AI Officer
  • Chief Technology Officer
  • Chief Information Officer
  • Chief Data Officer
  • VP, Artificial Intelligence
  • VP, Data & Analytics
  • Director, AI Strategy
  • Director, Digital Transformation
  • Director, Machine Learning
  • Head of Data Science
  • AI Product Manager
  • Machine Learning Engineer Manager
  • Solutions Architect
  • Enterprise Architect
  • Innovation Director
  • Data Platform Manager
  • Responsible AI / Governance Lead
  • Automation Program Manager
  • Technology Partnerships Manager
  • Consulting Partner / Practice Leader

Best industries to use:

  • Computer Software
  • Information Technology & Services
  • Internet
  • Computer & Network Security
  • Financial Services
  • Banking
  • Insurance
  • Management Consulting
  • Marketing & Advertising
  • Telecommunications
  • Retail
  • Healthcare / Hospital & Health Care
  • Pharmaceuticals
  • Education Management
  • Government Administration
  • Utilities
  • Transportation / Logistics
  • Manufacturing-related sectors through company keywords and functions

Event type fit: Enterprise AI conference, technical summit, innovation forum, B2B networking, product showcase, solution buyer conference, thought leadership event.

6️⃣ Estimated attendance / expected footfall

Without the official event brief in hand, the safest estimate for AI Con USA 2026 is mid-size to large conference attendance. For a U.S. AI event with this positioning, expected footfall is often in the range of:

  • 1,000 to 5,000+ attendees for a focused, high-quality conference
  • 5,000 to 10,000+ if the event includes multiple tracks, an expo floor, sponsorship-heavy participation, and strong enterprise branding

The quality of the audience matters more than raw numbers for attendee-list sales. Even a smaller AI event can be highly valuable if it contains senior leaders, product decision-makers, technical buyers, and active implementation teams.

7️⃣ Key focus areas & buyer engagement

AI Con USA 2026 will likely center on practical business outcomes rather than abstract theory. The strongest focus areas generally include:

  • Generative AI and large language model adoption
  • Machine learning model development and deployment
  • Data engineering, data quality, and data governance
  • AI infrastructure, cloud, compute, and platform scaling
  • Responsible AI, compliance, ethics, and risk management
  • AI in enterprise workflows and automation
  • AI product strategy and product management
  • Customer experience, marketing, and sales enablement through AI
  • AI for cybersecurity and threat detection
  • Vertical AI use cases in healthcare, finance, retail, logistics, and manufacturing

Buyer engagement angle: This event is ideal for positioning solutions around measurable business outcomes. Buyers at AI conferences respond best to clear messaging such as:

  • How your solution reduces cost or manual effort
  • How it accelerates deployment of AI models
  • How it improves governance, trust, and compliance
  • How it integrates with existing data and cloud stacks
  • How it supports enterprise use cases rather than just demos

The most engaged buyers are usually those with active budgets, current proof-of-concept projects, or clear mandates to implement AI within 6–12 months.

8️⃣ Client-product fit note

Before finalizing the best buyers for this event, I should review your client’s website and product positioning. The right buyer list changes a lot depending on what your client actually sells.

Examples:

  • If your client sells AI software or automation tools: target AI leaders, CTOs, data platform managers, and innovation executives.
  • If your client sells cloud or infrastructure services: target platform architects, cloud engineering leaders, and enterprise IT decision-makers.
  • If your client sells consulting or implementation services: target transformation leaders, strategy teams, and operations executives.
  • If your client sells cybersecurity: target security leaders, compliance officers, and infrastructure decision-makers.
  • If your client sells analytics or data tools: target CDOs, data science leads, BI leaders, and engineering managers.

Best next step: Share the client website, and I can narrow this into the most relevant buyer companies, job titles, and industries for your exact product.

9️⃣ Final recommendation

Overall assessment: AI Con USA 2026 looks like a strong event for high-value B2B attendee-list sales, especially if your database includes enterprise technology leaders, AI decision-makers, data teams, and consulting buyers.

Best buyer segments to collect:

  • Chief AI / Technology / Data officers
  • AI strategy and innovation leaders
  • Machine learning and data science managers
  • Cloud and platform architects
  • Digital transformation executives
  • Consulting firms and systems integrators
  • Enterprise buyers from finance, healthcare, retail, manufacturing, and telecom

Quality rating for attendee-list sales: 9/10

This is the kind of event that can produce very strong lead quality if the audience is properly segmented by title, function, seniority, and buying intent. The key is not just collecting “AI interest” contacts, but identifying people tied to real enterprise budgets and implementation needs.

Recommendation: If you share your client website, I can refine this into a sharper buyer shortlist and tell you which industries and titles are the best match for your product.

Data sheet

AI Con USA 2026 – Event Attendee & Buyer Profile Analysis
Event date: 7 June 2026 – 12 June 2026
Location: Hyatt Regency Seattle, Seattle, Washington, United States
Event status: Completed
Research date: 22 June 2026
Event Overview
Event Name AI Con USA 2026
Event Date 7 June 2026 – 12 June 2026
Event Status Completed
Venue Hyatt Regency Seattle
City Seattle
State / Region Washington
Country United States
Organizer Organizer not publicly confirmed in the source set reviewed for this brief.
Official Event Website Official event website not publicly confirmed in the source set reviewed for this brief.
Event Type B2B conference / summit focused on artificial intelligence, machine learning, data science, enterprise technology, automation, digital transformation, software, and innovation.
Primary Category IT & Technology
Secondary Applicable Categories Business Services
Audience Reach Likely national, with potential international participation from the AI, cloud, software, data, and enterprise technology ecosystem.
Estimated Attendance / Expected Footfall Attendance figure not publicly confirmed by the organizer.
Attendance Data Reliability Unconfirmed for the 2026 edition. Available assessment is based on event positioning, venue scale, and typical enterprise AI conference patterns.
Main Purpose of Event To convene enterprise technology leaders, AI practitioners, product teams, data stakeholders, solution providers, and innovation decision-makers around AI adoption, deployment, governance, tooling, and business transformation.
About the Event

AI Con USA 2026 appears to be a business-focused artificial intelligence event positioned around enterprise AI adoption, machine learning, analytics, automation, software innovation, and digital transformation. Based on the event title, venue, schedule, and the descriptive brief supplied for this report, the event is most relevant to senior technology leaders, AI and data teams, product and engineering functions, and commercial providers selling into enterprise modernization programs.

From a lead-generation perspective, the event matters because AI budgets increasingly span multiple buying centers, including IT, data, product, operations, cybersecurity, cloud, and transformation leadership. Even where public attendee verification is limited, an event of this profile is typically valuable for B2B outreach, partnership development, account-based marketing, and buyer mapping across enterprise software, consulting, infrastructure, analytics, and automation categories.

1. Who Attends: Buyers / Attendees
Buyer / Attendee Segment Typical Organizations Buying Role or Influence Relevance to Exhibitors / Suppliers
C-suite technology leadership Enterprise software firms, large corporates, financial institutions, healthcare systems, manufacturers, retailers, public sector technology teams Budget ownership, transformation sponsorship, platform approval High relevance for strategic software, infrastructure, AI transformation, and consulting deals
Chief data, analytics, and AI leaders Data-driven enterprises, digital-native companies, regulated industries, advanced analytics teams Model strategy, data stack decisions, governance, AI program ownership Key buyers for data platforms, MLOps, observability, governance, and data engineering solutions
Product and engineering leaders SaaS companies, enterprise platforms, application development organizations, innovation teams Evaluation of AI-enabled product features, developer tools, APIs, and deployment platforms Strong relevance for AI tooling, developer infrastructure, and product acceleration vendors
Machine learning and data science practitioners Internal data science teams, research groups, applied AI teams, innovation labs Technical recommendation, proof-of-concept validation, stack influence Important influencers for pilot adoption and technical shortlisting
IT infrastructure and cloud teams Enterprises operating hybrid cloud, security, storage, and enterprise architecture functions Platform integration, hosting decisions, architecture and scalability approval Relevant to cloud, compute, orchestration, storage, security, and networking suppliers
Operations and transformation leaders Large enterprises seeking workflow automation and process optimization Use-case prioritization, ROI evaluation, cross-functional sponsorship High relevance for automation, process intelligence, and change-management offerings
Cybersecurity and risk leaders Security-conscious enterprises, financial services, healthcare, government-adjacent organizations AI risk controls, data protection, compliance, vendor due diligence Relevant to AI governance, cybersecurity, privacy, and compliance vendors
Procurement and sourcing stakeholders Mid-market and enterprise buying organizations Commercial review, supplier onboarding, contract negotiation Useful for converting technical interest into approved vendor status
Consulting, systems integrator, and advisory firms Management consulting, cloud consultancies, implementation partners, digital transformation advisors Influence technology selection and implementation scope Strong partner and channel relevance
Investors, founders, and innovation ecosystem participants VCs, startups, incubators, venture studios, strategic innovation units Partnership, funding, early technology scouting Relevant for ecosystem mapping, alliances, and market visibility
2. Event Location and Attendee Geographic Origin
Geographic Area Likely Attendee Origin Buyer Concentration Notes
Seattle Local enterprise technology, cloud, software, startup, and consulting ecosystem High Seattle is a strong base for cloud, software engineering, AI talent, and enterprise digital transformation buyers.
Washington State Regional attendees from technology, healthcare, higher education, manufacturing, and public sector-adjacent organizations Medium to High Likely draw from wider state business and innovation communities.
Pacific Northwest Oregon, Idaho, British Columbia, and nearby innovation corridors Medium Good regional access for technology and enterprise modernization buyers.
United States national market Enterprise buyers, software vendors, AI startups, consultants, and practitioners from major U.S. business hubs High Likely strongest participation from West Coast, Texas, Northeast, and major data/AI business centers.
International Possible participation from Canada, Europe, and Asia-Pacific technology organizations Medium International reach is plausible for an AI event in Seattle, but the 2026 attendee mix is not publicly confirmed.
3. Audience Reach
Reach Level Assessment Explanation
National Primary classification The event profile, Seattle venue, and AI enterprise subject matter indicate a likely U.S.-wide audience of technology buyers, practitioners, and solution providers.
Secondary description Regional plus selective international spillover Seattle’s technology ecosystem may increase Pacific Northwest attendance and attract some cross-border participation, but this is not confirmed by a published attendee breakdown.
4. Sample Buyer Companies and Websites
Buyer Company / Organization Buyer Type Why It Is Relevant Website Best Job Titles to Target Evidence Level
No official current-year attendee, buyer, exhibitor, sponsor, or speaker-organization list was publicly confirmed in the source set reviewed for this brief. To avoid unsupported attendance claims, no company-level attendee table is asserted here. This limits current-edition attendee list building accuracy. If an official participant directory, agenda, sponsor page, or exhibitor list is shared, this section can be upgraded immediately.
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 roadmap, architecture direction, and strategic vendor selection.
2 Chief Information Officer IT C-Level Controls enterprise technology budgets, security posture, and integration approvals.
3 Chief Data Officer / Chief Analytics Officer Data & Analytics C-Level Leads data governance, analytics maturity, and enterprise AI readiness.
4 VP / Head of AI AI / Innovation VP Critical buyer for AI platforms, model operations, deployment, and governance tools.
5 Director of Data Science Data Science Director Influences technical evaluation, POC design, and team tool adoption.
6 Director of Machine Learning / MLOps Engineering / ML Platform Director Key role for production AI, scalability, monitoring, and deployment infrastructure.
7 VP Product / Director of Product Product VP / Director Buys or influences AI features, user experience enhancements, and embedded intelligence capabilities.
8 Enterprise Architect / Solutions Architect Architecture Manager to Director Determines integration fit, interoperability, and stack compatibility.
9 Director of Digital Transformation Strategy / Transformation Director Owns business case and cross-functional implementation priorities.
10 Procurement Manager / Strategic Sourcing Manager Procurement Manager Important for supplier onboarding, compliance, and contract conversion after technical selection.
Priority Apollo Industry Why It Fits the Event Best Buyer Use Case
1 Information Technology & Services Core fit for enterprise technology adoption and AI solution procurement AI platforms, cloud tooling, engineering services
2 Computer Software Strong relevance for product-led and embedded AI buyers APIs, copilots, developer tools, model integration
3 Computer & Network Security AI governance and security are common enterprise buying themes Model security, risk management, compliance controls
4 Financial Services High AI spend and strong analytics maturity Fraud detection, automation, customer intelligence
5 Hospital & Health Care Growing demand for AI-enabled clinical and operational optimization Workflow intelligence, predictive analytics, operational automation
6 Retail Retailers use AI for pricing, personalization, demand forecasting, and service automation Customer analytics, supply optimization, recommendation engines
7 Telecommunications Large-scale data operations and automation use cases Network intelligence, customer support AI, operations analytics
8 Manufacturing Industrial AI use cases continue to expand Predictive maintenance, quality intelligence, process automation
9 Government Administration Public sector AI interest is growing in service delivery and operational efficiency Automation, citizen service, document intelligence
10 Management Consulting Consultancies influence enterprise AI strategy and vendor selection Partnerships, implementation channels, referral opportunities
11 Internet Digital-native companies are active adopters of AI tooling Growth analytics, personalization, operational automation
12 Research Applied research and innovation labs often evaluate leading AI tools Experimental platforms, advanced analytics, collaboration
6. Estimated Attendance
Metric Figure Status Source / Basis Notes
Estimated total footfall Attendance figure not publicly confirmed by the organizer. Unconfirmed No official 2026 attendance figure located in the source set reviewed Any market estimate would be speculative without organizer disclosure.
Exhibitor count Not publicly confirmed Unconfirmed No official exhibitor directory verified for this brief Important limitation for list-building use cases.
Buyer count Not publicly confirmed Unconfirmed No official attendee segmentation data verified Buyer composition is inferred from the event theme only.
Speaker count Not publicly confirmed Unconfirmed No official 2026 speaker roster verified Agenda access would materially improve stakeholder mapping.
Sponsor count Not publicly confirmed Unconfirmed No official sponsor page verified Sponsor data would help identify ecosystem buyers and partners.
Historical attendance No prior-year official attendance figure verified in the reviewed source set Historical / prior-year evidence unavailable Current brief is based on supplied event details and venue verification Can be updated if official archives are shared.
7. Key Focus Areas and Buyer Engagement
Focus Area Typical Buyer Need Buyer Engagement Opportunity Relevant Supplier Offering
Enterprise AI adoption Move from experimentation to production deployment Executive strategy discussions, roadmap workshops, platform evaluation AI platforms, implementation services, change management
Machine learning operations Model deployment, monitoring, reproducibility, and scale Technical demos and architecture conversations MLOps, observability, model management, workflow orchestration
Data infrastructure Trusted data pipelines, storage, integration, and quality Data modernization planning and architecture mapping Lakehouse, ETL/ELT, governance, metadata, quality platforms
Automation and digital transformation Process efficiency and measurable ROI Use-case workshops and functional buyer outreach Workflow automation, intelligent document processing, process mining
AI governance and security Risk mitigation, privacy, compliance, explainability Security-led buying conversations and governance briefings Security tools, auditability, access control, policy enforcement
Cloud and compute optimization Performance, cost control, deployment flexibility Infrastructure ROI discussions with architecture teams Cloud services, GPU optimization, storage, container platforms
Product innovation Add AI features to improve usability, retention, and monetization Product leadership and engineering team outreach Developer APIs, copilots, search, recommendation, analytics tooling
Lead Quality Assessment
Factor Assessment Explanation
Buyer relevance High The event theme aligns with enterprise technology, AI, data, product, and transformation buyers.
Decision-maker availability High AI events commonly attract director-level to C-level stakeholders and technical influencers.
Data collection potential Medium Potential is good if sponsor, speaker, or attendee directories become available; currently limited by lack of public lists.
Apollo targeting potential Very High The event maps well to searchable industry, title, department, and keyword filters in Apollo.io.
Geographic targeting potential High Seattle, Pacific Northwest, and U.S. enterprise hubs are practical targeting clusters.
Best outreach approach High Use value-led messaging around AI adoption, governance, cost optimization, deployment speed, and measurable business outcomes.
Overall lead quality High Good event fit for enterprise software, cloud, analytics, automation, consulting, and AI infrastructure offers.
Best use case High ABM targeting, speaker/sponsor-based prospecting, post-event outreach, and role-based buyer mapping.
Limitations / risks Medium Current-edition attendee list building is constrained by the absence of publicly confirmed participant data in the reviewed source set.
Apollo.io Targeting Recommendation
Filter Type Recommended Filters Purpose
Apollo industries Information Technology & Services; Computer Software; Computer & Network Security; Financial Services; Hospital & Health Care; Retail; Telecommunications; Manufacturing; Government Administration; Management Consulting; Internet; Research Captures the most likely enterprise AI buyer environments
Departments Engineering; Information Technology; Product Management; Operations; Data / Analytics; Innovation; Procurement Targets both technical buyers and commercial approvers
Seniority C-Level; VP; Director; Head; Manager Focuses on decision-makers and strong influencers
Job titles CTO; CIO; Chief Data Officer; Chief Analytics Officer; Head of AI; VP AI; Director of Data Science; Director of Machine Learning; Director of AI Engineering; VP Product; Enterprise Architect; Director of Digital Transformation; Strategic Sourcing Manager Aligns with AI budget ownership, productization, deployment, and governance
Geography United States; Washington; Seattle metro; Pacific Northwest; major U.S. technology hubs Supports event-adjacent and national account targeting
Employee size 51-200; 201-500; 501-1,000; 1,001-5,000; 5,001-10,000; 10,001+ Covers both growth-stage AI adopters and enterprise-scale budgets
Keywords artificial intelligence; machine learning; generative AI; data science; MLOps; analytics; AI governance; digital transformation; automation; computer vision; NLP; LLM; data platform Improves precision for event-theme alignment
Technologies Cloud data platforms, AI/ML tooling, analytics stacks, orchestration, security tooling where available in Apollo enrichment Useful for tailoring outreach to maturity stage and environment
Revenue range $10M-$50M; $50M-$250M; $250M-$1B; $1B+ Segments growth-stage versus enterprise buying capacity
Company type Private; Public; Subsidiary; Nonprofit where research-led AI adoption is relevant Broadens search across corporate and institutional buyers
Suggested Apollo Search Logic: ("artificial intelligence" OR "machine learning" OR "generative AI" OR "data science" OR MLOps OR "AI governance" OR automation OR analytics) AND (CTO OR CIO OR "Chief Data Officer" OR "Head of AI" OR "Director of Data Science" OR "Director of Machine Learning" OR "VP Product" OR "Director of Digital Transformation") AND geography filters for United States, Seattle, Washington, or priority national technology hubs.
Client Fit Review Required
Please share the client website or product/service details. I will review the client offering and identify the highest-fit buyer companies, Apollo industries, seniority levels, departments, and job titles from this event.
Sources & Verification Notes
Source Type What It Verified Reliability
User-supplied event brief Client-provided source Event name, dates, venue, city, country, and thematic description used as the starting brief for this report Medium
Hyatt Hotels Official Website Venue / hotel source Venue brand verification for Hyatt Regency Seattle High for venue brand; limited for event-specific participation data
Public source set reviewed for this brief Research note No official current-year attendee list, exhibitor directory, sponsor roster, or speaker-organization list was publicly confirmed in the materials available for this draft High confidence in the limitation statement

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