AI Enterprise Conference 2026 (NYC, Sep 1): Speakers and Topics
September 1, 2026
AI Enterprise Conference 2026 took place on Tuesday, September 1, 2026 at Pier Sixty on Chelsea Piers in Manhattan. This page keeps the lineup, topic map and pass pricing as they were announced before the event, for...
AI Enterprise Conference 2026 took place on Tuesday, September 1, 2026 at Pier Sixty on Chelsea Piers in Manhattan. This page keeps the lineup, topic map and pass pricing as they were announced before the event, for reference or for planning a future visit.
Data Science Connect built the day for senior data and AI leaders from Citi, BlackRock, Morgan Stanley, and Broadridge: one day of governance and production content, heavily finance-tilted. The in-person pass was priced at $749, and a $999 apply-to-attend pass was free for qualified non-vendor enterprise leaders.
I track this event because production, not pilots, is the 2026 gate
I follow enterprise data and AI conferences because the governance patterns and platforms executives argue about on stage tend to surface in my AI tool reviews within a few months. The AI Enterprise Conference 2026 was one of the cleaner signals. Its audience was the people deciding how AI gets bought, governed, and shipped inside large companies, with a heavy New York financial-services tilt this year.
The 2026 theme read “AI for Enterprise: From Pilots to Production.” That framing matches the actual gap. Most large organisations have run a pilot; far fewer have moved one into governed production.
The room of chief data officers, model-risk leads, and MLOps directors was there to close that gap. Disclosure worth stating up front: zplatform.ai was a listed media partner on the event site, so read this as coverage from inside the orbit, not a neutral outsider.
The event in one table
| Detail | Value |
|---|---|
| Date | Tuesday, September 1, 2026 |
| Hours | 9:00 a.m. to 4:00 p.m. |
| Venue | Pier Sixty, Chelsea Piers, Manhattan |
| Format | In-person, single-day |
| Organiser | Data Science Connect |
| Theme | AI for Enterprise: From Pilots to Production |
| Speakers announced | 20-plus data and AI leaders (checked 2026-08-24, datasciconnect.com) |
| Passes | $749 in-person, free apply-to-attend for qualified enterprise leaders |
The venue upgrade mattered this year
Pier Sixty sits on the Hudson at Chelsea Piers, a purpose-built ballroom space with waterfront light and enterprise-grade audiovisual. For a day built around stage content and a networking floor, a waterfront ballroom beats a windowless convention hall on every axis that matters, including how tired you are by 3 p.m.
The Manhattan location was strategic. New York is the centre of US financial services, and the 2026 roster was banked accordingly. JFK, LaGuardia, and Newark cover flights from almost anywhere; Chelsea Piers is a short cab or subway from Midtown.
What the 2026 lineup looked like
The event listed 20-plus senior data and AI leaders, with more promised closer to September (checked 2026-08-24, datasciconnect.com). Featured names:
- Joshua Ainsley, Senior Director, Head of Data Science at New Balance
- Srini Masanam, Global Head of Data Quality and Governance at Citi
- Lu Ai, VP, Data Governance and Innovation Leader at QBE
- Sai Teja Akula, Senior Director, AI, ML and Data Science at Broadridge
- Ken Zhang, Distinguished Engineer, Global Head of GenAI, Data Science and Engineering
- Alexey A. Smurov, SVP, Head of LOB Model Risk Management
- Dhagash Mehta, Head of Applied Machine Learning Research for Investment Management
- Carlos Peralta, VP, Data Platforms and MLOps
The pattern to notice: alongside the engineering and MLOps leaders, the roster ran unusually deep in governance, model-risk, operational-risk, and data-quality titles. That was the differentiator.
Plenty of AI events cover production and governance in the abstract. Far fewer put model-risk leads from major banks in one room. For anyone whose AI roadmap has to clear a model-risk committee before it ships, this was a room of peers facing the same gate.
The topic map, minus the marketing
The organiser split the programme into four pillars and a broader topic map, and the substance under it lined up with the real concerns of an enterprise data function. The content that mattered:
- AI as a system. Evaluation and observability. LLMOps and GenAIOps. Agents treated as systems, not features. Context engineering beyond classic RAG.
- Data foundations and knowledge retrieval. The unglamorous data work that decides whether any AI initiative ships. Enterprise knowledge grounding.
- Governance, risk, and security. The defining pillar for this finance-heavy audience. Model risk, operational risk, and the compliance path AI has to walk in regulated industries.
- AI economics. Measuring ROI and controlling cost of AI workloads. Build versus buy on platform strategy.
Sessions leaned on real deployments and case studies rather than model demos, including agentic AI moving into governed production. For teams past the demo stage and fighting reliability problems in production, this pillar block was the core of the day.
What the passes cost
There were three passes. I checked pricing on 2026-08-24 against the official site.
| Pass | Price | Who it’s for |
|---|---|---|
| All-Access (in-person) | $749 (was $499 early bird, regular $999) | Anyone without the free-pass qualification |
| Apply to Attend | Free ($999 value) | Qualified non-vendor enterprise leaders |
| Media Pass | Free, application-only | Journalists actively covering AI and data |
The $499 early bird had already closed by then. As of 2026-08-24 the in-person pass sat at $749, marked down from a $999 standard price on datasciconnect.com.
The free pass was the one worth chasing. It had three criteria: the applicant’s company was not a vendor selling data or AI to end-users, the applicant worked at a non-vendor organisation with 250-plus employees, and held a senior executive or technical position.
Applicants completed a form, and the team reviewed and confirmed. The vendor exclusion was the point of the format: it was designed to keep the buyer-to-seller ratio in attendees’ favour, so the room would be enterprise buyers rather than vendors selling to each other.
Who the organiser said attends
The official “Who Attends” section named the enterprises whose data and AI leaders the event draws, and it confirmed the finance-heavy read. The companies listed for 2026 included JPMorgan Chase, Goldman Sachs, Morgan Stanley, BlackRock, American Express, MetLife, New York Life, Blackstone, and Citigroup on the financial-services side, plus Pfizer, Bristol Myers Squibb, Takeda, CVS, and Northwell Health from healthcare, and Estée Lauder, Colgate-Palmolive, Tiffany & Co., Wayfair, Verizon, SiriusXM, Fox, WarnerMedia, UPS, and LinkedIn from consumer, media, and tech (checked 2026-08-24, datasciconnect.com).
Sponsors at time of check: IBM, Teradata, SAS, and Fulcrum Digital at the Presenting tier; Rubrik and Datatonic at Diamond; Revefi, Midships, Safe Intelligence, and Lineaje at Platinum; Coalesce at Gold, with more listed as coming.
Who the day suited
For a leader who qualified for the free pass and lived in the Northeast, this was close to automatic. The only cost was a train or a short flight and one day of calendar. The peer benchmarking value against a room of CDOs and model-risk leads at large banks and insurers was hard to buy anywhere else for that price.
At the $749 in-person rate, the value depended on what an attendee wanted out of the day. For governance-heavy, production-focused content with a finance lean and vendor-controlled networking, $749 was fair against the alternative.
For hands-on technical training, this was the wrong event. It was a strategy and networking day by design, not a workshop where you leave with new code.
The one attendee I would have talked out of coming was a solo founder hoping to run early-stage tool evaluation, for whom peer access to enterprise buyers is not the bottleneck. Cheaper picks live in my best AI tools for business roundup.
How AI Enterprise Conference compared with COLLIDE
Both events come from Data Science Connect and share the theme. The difference was geography and industry lean.
| Factor | AI Enterprise (NYC) | COLLIDE (Atlanta) |
|---|---|---|
| Date | September 1, 2026 | October 1, 2026 |
| Venue | Pier Sixty, Chelsea Piers | Sandy Springs, Atlanta |
| Lean | Finance-heavy, Northeast | Broader Southern enterprise |
| Passes | $749 / free apply-to-attend | Same structure |
The AI Enterprise Conference was the fit for banking, insurance, and asset management, or for anyone based in the Northeast. For the Southeast or a broader trade-show feel, COLLIDE in Atlanta follows a month later, on October 1, 2026.
How registration worked
The path split by pass. Non-vendor enterprise, 250-plus employees, senior role: the free apply-to-attend form came first, then confirmation from the team.
Vendor or non-qualifying: direct registration at the $749 in-person rate. Media: the media-pass form on datasciconnect.com. Registration ran through the official event page.
Prefer a smaller executive-roundtable format over a trade show? The ALIGN AI Executive Summit NYC is Data Science Connect’s higher-end sibling in New York, with a $2,499 pass and a senior-only bar.