ALIGN AI
Executive Summit CHI

July 15, 2026 | CHI

Connect with Enterprise Execs

ALIGN AI Executive Summits—the exclusive forum for enterprise data + AI leaders

Featured 2026 Speakers

Data + AI decision-makers from the world's top enterprises​

ALIGN AI Summits » Data Science Connect

Abhishek Yadav

Associate Director, Business Intelligence

ALIGN AI Summits » Data Science Connect
ALIGN AI Summits » Data Science Connect

Kelly O'Brien

VP of Product Strategy, Commercial Card

ALIGN AI Summits » Data Science Connect
ALIGN AI Summits » Data Science Connect

Ernesto Rodriguez

Senior Product Manager (Ai & Digital Solutions)

ALIGN AI Summits » Data Science Connect
ALIGN AI Summits » Data Science Connect

Prakash Rao

Director, Global Digital Strategy, Cardiac Rhythm Management

ALIGN AI Summits » Data Science Connect
ALIGN AI Summits » Data Science Connect

Elena Garvey

IT Director - Data Analytics & Business Insights

ALIGN AI Summits » Data Science Connect
ALIGN AI Summits » Data Science Connect

Jim Maskeri

Director - AI & Automation

ALIGN AI Summits » Data Science Connect

More speakers coming soon

Save Your Spot Now

Skip the Application

Skip the application process and secure your all-access pass to the exclusive ALIGN AI Summit of your choice by registering today for $2,499. These passes are available for a limited time and will sell out!

Registration includes in-person access to all summit features including:

– All general sessions, including presentations, and executive panels

– Invitation to at least one executive roundtable

– Breakfast, lunch, and networking reception

– Exhibit Hall

Apply to Attend for Free

ALIGN AI Summit free passes – for qualified attendees only – are highly limited and 100% free.

You may qualify if you meet all 3 criteria below:
1. Your company is not a vendor and has no sales interest in end-users of AI-related products or services
2. You work at a non-vendor organization with 5K+ employees
3. You hold a senior-level position (director-level and up)

After you complete the registration form, we will be back in touch to let you know if you have been selected.

ALIGN AI Summits » Data Science Connect

Venue

City Winery Chicago | West Loop

The ALIGN AI Executive Summit will be taking place in the heart of Chicago’s historic West Loop, at City Winery Chicago.

City Winery offers a stunning blend of rustic charm and modern sophistication—a true “urban wine country” experience. With its exposed brick, warm wood interiors, and working winery on-site, this venue provides a refreshing atmosphere for the summit. It’s the perfect backdrop for sparking creative conversations, fostering genuine connections, and enjoying world-class hospitality while we shape the future of data and AI.

2026 Events Theme

AI for Enterprise:
From Pilots to Production

Enterprise AI is entering a new phase. In 2026, it’s no longer about access to models or experimentation—it’s about building systems that are scalable, governed, secure, and tied to real business outcomes. As organizations move from pilots to production, success depends on operationalizing AI with confidence.

Our events explore what it truly takes to make AI work inside the enterprise—from systems and governance to data foundations and economics. From context engineering and agentic workflows to platform strategy and measurable ROI, we focus on the realities leaders must address now.

Our point of view is simple: enterprise AI is no longer a model conversation. It is a systems, governance, and value conversation.
ALIGN AI Summits » Data Science Connect

This Year's Content Pillars

ALIGN AI Summits » Data Science Connect

Pillar 1: AI as a System

Enterprise AI is no longer about deploying a model. It is about operating a system.

This pillar explores the shift from isolated AI capabilities to full production systems that require evaluation, observability, context management, release discipline, and resilience over time. It includes the move from traditional RAG toward broader context engineering approaches that incorporate retrieval, orchestration, tool use, and emerging protocols such as MCP within a larger enterprise architecture. The focus is not just intelligence, but reliability.

Key discussion points:
— Context engineering beyond classic RAG
— Evaluation, observability, and AI system reliability
— LLMOps and GenAIOps for production environments
— Agents as systems, not just features
— Enterprise knowledge architecture and grounded AI
ALIGN AI Summits » Data Science Connect

Pillar 2: Governance That Runs

In 2026, governance must move from policy decks to runtime enforcement.

As regulation tightens and enterprise exposure grows, governance can no longer live only in committees, documentation, or static controls. This pillar focuses on how organizations make governance operational through technical controls, monitoring, auditability, security engineering, and cross-functional accountability. It reflects the growing reality that enterprise AI must be not only innovative, but provable, defensible, and trustworthy.

Key discussion points:
— Runtime governance and policy enforcement
— AI risk, security, and model accountability
— Privacy, sovereignty, and data rights
— Audit readiness and evidence generation
— Governing agents, autonomy, and human oversight
ALIGN AI Summits » Data Science Connect

Pillar 3: The Economics of AI

AI is now a portfolio decision, not a side experiment.

As organizations scale usage, leaders are under pressure to demonstrate impact while managing cost. This pillar examines the economics of enterprise AI: how to prioritize use cases, measure value, understand cost-to-serve, and create discipline around infrastructure, tooling, vendor spend, and human oversight. The goal is to move beyond vague transformation language toward credible ROI and durable operating models.

Key discussion points:
— Measuring AI ROI in real business terms
— FinOps for AI and cost governance
— Use case prioritization and portfolio strategy
— Productivity, performance, and value realization
— Sustainable scaling and long-term economics
ALIGN AI Summits » Data Science Connect

Pillar 4: The Enterprise Foundation

AI maturity is still constrained by data maturity, platform choices, and organizational design.

This pillar focuses on the underlying foundation that makes enterprise AI possible. That includes AI-ready data, metadata, lineage, semantics, interoperability, platform strategy, and the operating models that determine who owns AI and how it scales. It also addresses the organizational realities behind enterprise adoption: workforce readiness, cross-functional alignment, and the tension between centralized control and distributed innovation.

Key discussion points:
— AI-ready data foundations and semantic consistency
— Data governance and AI governance convergence
— Platform strategy, interoperability, and lock-in
— Operating models for data and AI leadership
— AI literacy, adoption, and organizational readiness

Topics to Expect

— Agentic AI Platforms
— Enterprise AI Applications
— Copilots & Workflow Automation
— Context Engineering & Orchestration
— Model Context Protocol (MCP) & Tooling

— LLMOps / GenAIOps Platforms
— AI Evaluation & Testing
— Prompt & Context Management
— AI Observability
— AI System Monitoring & Debugging

— Data Platforms (Lakehouse, Warehouse, Hybrid)
— Data Engineering & Pipelines
— Data Quality & Data Observability
— Metadata, Lineage & Cataloging
— Unstructured Data & Content Operations

— Retrieval Systems & Vector Databases
— Enterprise Search & Knowledge Management
— Knowledge Graphs & Semantic Layers
— Context & Retrieval Optimization

— AI Infrastructure & Compute (GPU, Inference)
— Model Serving & Inference Optimization
— AI Platform Engineering
— Scalability, Latency & Performance Optimization

— AI Governance Platforms
— Model Risk Management
— AI Security (Prompt Injection, Data Leakage, etc.)
— Privacy Engineering & Data Protection
— Compliance & Regulatory Technology

— FinOps for AI
— Cost Optimization & Usage Monitoring
— AI ROI Measurement & Value Tracking
— Vendor & Model Cost Management

— Interoperability & Data Sharing
— API & Integration Platforms
— Data/AI Ecosystem Strategy
— Vendor Consolidation vs Best-of-Breed

— AI Operating Models (Centralized vs Federated)
— AI Product & Platform Teams
— Workforce AI Enablement & Literacy
— Change Management & Adoption

Why They Keep Coming Back

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