Beyond the Hype Cycle – Defining the 2026 Enterprise Blueprint

• Which technologies are the proven drivers of revenue generation and operational efficiency?
• Address critical, enterprise-wide risks in data governance, AI ethics/bias, and security vulnerabilities that dominate C-suite discussions
• How are CxO’s structuring their teams and budgets to shape the next era of business transformation, rather than simply supporting it?

Kevin Bock

Chief Health Information Officer

Northwell Health

Suresh Kandula

Chief Technology Officer, Integrated Services

Ford Motor Company

Louie Celiberti

Managing Director

Guggenheim Partners

Florence Hudson

Executive Director

Columbia University

Alex Gutman

Chief Technology Officer

Gilbane Building Company

Kristi Rogers

Senior Director, Strategic Relationships

New York Power Authority

Building Production-Ready Agentic AI — Why a Control Plane Matters

Agentic AI promises autonomy, but most organizations remain stuck in pilot mode. Generative models alone can’t deliver the reliability production demands—agents can hallucinate, misread context, and amplify small errors across complex workflows. Without a unifying control plane, scaling agentic AI leads to unpredictable outcomes. Join Dynatrace’s Wayne Segar to learn what it takes to run agentic AI in production. Discover how end-to-end observability, deterministic real-time context, and a centralized control plane enable reliable autonomy—while balancing human oversight, feedback loops, and automation at scale.

Wayne Segar

RVP of Field CTO and AI Innovation

Dynatrace

AI-Ready Data Infrastructure: Scale Smarter, Run Faster, No Compromises

• Where is your biggest AI data bottleneck today - scale, speed, or reliability?
• Integrate vector search and transactional workloads in one resilient database 
• Leverage pgvector for AI-driven applications directly within CockroachDB
• Combine high-throughput transactional data with AI workloads without sacrificing ACID guarantees
• Architect data infrastructure that’s always-on, globally distributed, and fault-tolerant
• Simplify pipelines, reduce complexity, and accelerate AI adoption

Mark Johnson

Senior Manager of Sales Engineering

Cockroach DB

From AI Hype to Enterprise Impact: Scaling AI with a Modern Data Foundation

• Moving from fragmented data to AI at scale by modernizing data platforms on Google Cloud and operationalizing AI using Vertex AI, Gemini models, and MLOps by design
• Embedding AI into data‑driven enterprise workflows, where governed, high‑quality data—not standalone models—powers decision‑making and automation
• Why data governance, responsible AI, and Zero Trust security are prerequisites for scaling AI adoption with confidence and speed
• Persistent’s role in engineering AI‑ready data platforms, integrating AI into existing data architectures, products, and operational processes
• Measuring success through business outcomes—faster insights, lower TCO, and operational impact—rather than model performance alone

Ajay Yadav

Vice President of Sales

Persistent Systems

The AI-Native Adversary: Is Your Security Program Accelerating, or Already Behind?

AI-native adversaries compress the cloud kill chain to minutes. Every downstream bet, AI initiatives, data platforms, cloud-native architecture, rests on a security program that most companies haven't redesigned to match that tempo. This executive session grounds executives in how attackers actually operate today, then pressure-tests one question: is your program accelerating fast enough, or already behind?

• How AI-enabled threat actors actually operate in the cloud today, from initial access to lateral movement in under ten minutes.
• Where human-gated programs are already failing the tempo test and which decisions CISOs are beginning to delegate at AI.
• The accountability question coming from every board: can you prove your program works against the adversary that exists now?

Conor Sherman

CISO in Residence

Sysdig

Advancing Digital Resilience for the Agentic Era

As agentic applications reshape digital ecosystems, data volume and complexity are skyrocketing. This shift is fueling cross-domain threats that exploit fragmentation and make it harder than ever to stay ahead. To address the challenges posed by AI, organizations need to think about digital resilience in new ways – supercharging security and observability with AI, ensuring security and observability for AI, and protecting themselves from new threats posed by AI.

Peter Sprenger

Field CTO

Splunk

From Data Silos to Intelligent Enterprise Analytics: Breaking the Integration Paralysis

Most large enterprises manage 900+ applications across their technology portfolio, creating information silos that fundamentally limit organizational intelligence. While executives recognize this challenge, many remain paralyzed by the scale and complexity of integration, ETL efforts. This discussion explores how AI can serve as the "universal connector" - not requiring wholesale system replacement, but creating an intelligent overlay that bridges disparate data sources. We'll discuss how to move from analysis paralysis to progressive value creation through AI-powered data unification and insights. Key Discussion Points:

• How do you make your data AI ready?
• What are the most effective architectural patterns and technologies (e.g., data fabric, data mesh, modernized data warehousing) for breaking down existing data silos?
• What frameworks and technologies have been most useful for ETL, data prep - what is the ‘analytics and data stack’ for AI?
• AI as semantic bridge vs. traditional ETL approaches
• Measuring business impact beyond technical metrics - Cultivating Data Literacy and Cross-Functional Collaboration for AI Success

Alejandro Cantu

Director, Product Strategy — AI & Data

MindsDB

AI Colleagues—Transforming the Back Office with Enterprise-wide Agentic AI

See why companies like Coca-Cola, Nestlé, Sony, and MongoDB trust AI Colleagues to transform IT, HR, Finance/Procurement. In this session, watch AI Colleagues in action—employees talk with them just like human teammates to get answers, complete tasks, and execute back office workflows across ServiceNow, SAP, Workday, Oracle, UKG and more.

• What are AI colleagues? See them in action
• What back office functions (IT, HR, Finance, Procurement) are best performed by AI colleagues?
• What savings companies can expect from deploying AI colleagues?
• What are the common challenges companies face when implementing AI colleagues for the back office?
• Why not develop these in-house, using “free tools”?
• Why not just commission the AI agents on offer from the various system-of-record providers?

Adit Jain

Co-Founder & CEO

Leena AI

Five critical mistakes to avoid when deploying AI for customer experience

AI has moved from experimentation to expectation in customer experience. CIOs are under pressure to deliver impact fast while navigating complex systems, fragmented data, and competing priorities. The upside is clear: smarter automation, more productive agents, and better customer outcomes. The reality is often more uneven. In this workshop presentation, Cresta's Field CTO Deepank Sharma will share candid perspectives on what it really takes to deploy AI for CX in large enterprises. Drawing from real-world Fortune 500 implementations, we will explore where initiatives go off track and why. From early decisions to execution, small missteps can compound into stalled rollouts or solutions that never scale. Attendees will leave with a clearer lens on how to approach AI in CX, anticipate hidden risks, and set their teams up for outcomes that deliver.

Deepank Sharma

Field CTO

Cresta

Beyond the Model

Your data supply chain is your only real AI moat and it needs Trusted Knowledge Infrastructure to work. Every CxO learned a brutal lesson during the global supply chain crisis: it doesn't matter how sophisticated your factory is if your supply chain can't deliver the right parts, to the right place, at the right time. AI has the exact same problem. LLMs are the most extraordinary reasoning factories ever built — but they're running on a broken supply chain. The knowledge feeding them is stale, fragmented, ungoverned, and disconnected from your proprietary reality. The critical difference: in a traditional business, when the supply chain fails, the assembly line stops. You know you have a problem. In AI, the line doesn't stop — it starts producing counterfeit goods with total confidence. It plates them beautifully and ships them to your customers. Everyone has access to the same models. The model isn't your moat. Your moat is what you feed it — and the infrastructure that ensures what you feed it needs to be accurate, governed, and real-time. That's Trusted Knowledge Infrastructure: the logistics layer that turns your proprietary data into your AI's unfair advantage.

Ash Ashutosh

CEO

Pinecone

Separating Hype from Impact: What Works, What Fails, and Why

• Identify AI use cases that consistently deliver real business value
• Understand the technical factors behind success and failure
• Clarify AI’s strengths and limitations to guide strategic decisions
• Equip C-suite leaders with criteria for selecting high-impact AI initiatives

Alaa Moussawi

Chief Data Scientist

New York City Council

Agentic Orchestration: Moving AI Agents from Experiments to Enterprise

Every enterprise is investing in AI. The models work. The pilots prove value. But for most organizations, that value stays trapped — locked inside individual use cases, disconnected from the end-to-end processes that actually run the business. The missing layer isn't more AI. It's orchestration. This intimate, executive-level roundtable brings together senior leaders from financial services, life sciences, consumer goods, and beyond to tackle the real challenge head-on: how do you move AI agents from isolated experiments to coordinated, production-grade systems — without sacrificing governance, auditability, or speed? Expect a candid, peer-driven conversation. No slides. No product demos. Chatham House Rule applies. Questions we'll explore:

• Where are your AI agents creating real value today — and where are they stalling at the boundary between systems?
• What's actually blocking production deployment: technology, governance, organizational structure, or something else entirely?
• If you were designing an orchestration layer from scratch — one that connects agents, workflows, people, and compliance — what would it need to do?
• What would it take to turn your systems of record into systems of intelligence?
• Which process in your organization would benefit most from agentic orchestration — and what's stopping you from starting there?

Mark Hoffman

Managing Director, Strategic Accounts

BP3

You Don't Have an AI Problem. You Have a Data Problem.

• Get a framework for thinking about data quality at the moment of use — not just at ingestion
• Learn what questions you should be asking your data & AI teams right now to ensure you have the foundational infrastructure right

Alex Krupey

Senior Director of Customer Experience

Qualytics

Everything Is Hackable: Rethinking AI Risk, Ethics & Global Safety Standards

• Trust, identity, privacy & security as core design principles
• Securing the entire AI ecosystem through equipment, data and people
• The expanding risk surface of modern technologies
• Why global standards & collaboration are essential

Florence Hudson

Executive Director

Columbia University

“AI Colleagues” for the Back Office - How to Architect, Securely Deploy, and Govern Agentic AI at Enterprise Scale

A comprehensive, open agentic AI architecture can empower CIOs to accelerate enterprise-wide AI adoption. Agentic AI technologies are poised to streamline workflows, ensure access control and governance, and minimize hallucinations—to deliver on the promise of agentic AI. In this session, you’ll explore how to:

• Define the architectural approach behind a unified agentic AI layer
• Abstract complexity, drive efficiencies, and accelerate time to business outcomes
• Enforce access control and governance

Adit Jain

Co-Founder & CEO

Leena AI

The Agentic Enterprise Starts With Your Data: How Leaders Unlock the Knowledge Trapped in Documents, Emails, and Files

• Most companies are sitting on their most valuable data — and their AI can’t access it
• The real reason AI projects fail to deliver executive-level impact
• What the shift to agentic AI means for your data strategy — and how to get ready
• A practical starting point for executives ready to move from AI experimentation to AI that works

Simon Coombs

Head of Solutions Architecture

Unstructured

180 Days to Value – Architecting the Next 6-Month IT Strategy for Data, AI & Cyber Resilience

• Understand the new challenges and opportunities for talent management in a hybrid work environment.
• Learn to build a resilient and agile technology workforce that can adapt to rapid change.
• Explore strategies for attracting, retaining, and upskilling talent in a competitive market.

Louie Celiberti

Managing Director

Guggenheim Partners

Svetlana Grigoryeva

Director of Applications & Development

Hughes Hubbard & Reed

Amit Basu

Vice President, Chief Information Officer & Chief Information Security Officer

International Seaways, Inc.

Shipali Jangra

Director, Digital Product Management

American Express (Amex)