Leaders In AI Summit Austin 2026

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Leaders In AI Summit Austin

DAY 1: 1 PM -6 PM
DAY 2: 9 AM-6 PM

February 17-18th

Omni Austin Hotel Downtown

Featured Speakers

Sean McCall

Chief Data Officer

Rameshwar Balanagu

Chief Enterprise Architect

Vino Kingston

Data & AI Transformation Strategy and Integration Leader

Michael R. Boone

Trustworthy AI Product Manager

Kumar Melam

Director, Data Science & Enterprise AI

Tomáš Burkert

Head of Innovation @ TrainAI

Anh Selissen

Chief Information Officer

Sailesh Bharathwaaj

Head Of AI Center of Excellence

Leaders In AI Austin
‍Day 1 Agenda

Begins at Noon

Hotel Lobby Front Desk

Hotel ARRIVALS & Room block

If you are traveling in for Day 1, we strongly encourage attendees to stay at the Omni Austin Downtown Hotel. We have coordinated early hotel access for Day 1 attendees ahead of the workshop, making it easy to arrive, settle in, and stay onsite for the full experience.
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Guests arriving before standard hotel check-in will be able to check in early when available or store luggage with the hotel staff and head directly to the workshop sessions. Staying onsite allows you to move seamlessly between sessions, networking, and the evening Think Tank Dinners.
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We have secured a limited room block at a preferred rate for Summit participants. Availability is first come, first served, and booking through the official room block helps support the event experience.
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For hotel details and reservations, please visit the Hotel Room Block section linked above this agenda.

Begins at 1:00 PM

Leaders In AI Registration Desk @ Executive Ballroom

Day 1 Workshop Check-In & Registration

Welcome to Day 1 of the Leaders in AI Summit Austin 2026.
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This check-in marks the start of a small, highly focused Pre-Summit Workshop designed for leaders who are actively shaping how AI is governed, deployed, and scaled inside their organizations. We will be meeting at the Leaders In AI Registration Desk at the front of the Omni Austin Downtown Hotel Executive Ballroom.
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If you have a confirmed Day 1 workshop pass, please arrive during this window to check in, receive your materials, and get settled before we begin promptly at 2:00 PM. The afternoon is structured to build progressively, starting with governance fundamentals and moving into deeper, more technical discussion.
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Day 1 is intentionally limited in size to allow for candid conversation, real case studies, agentic architecture examples, and true executive level networking. If you believe you should have access to the Day 1 workshop but have not yet received confirmation, please contact the Institute for AI Transformation team using the Contact Us link at the top of this page prior to arrival.
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Once checked in, you’ll move directly into the session room for the opening workshop on Governance in AI Deployment, setting the foundation for the rest of the day.

1:30 PM - 1:40 PM

Main Stage - Executive Ballroom

Opening Remarks

Kick off Day 1 the Leaders In AI Summit with opening remarks from Robert Jaggers, CEO of the Institute for AI Transformation, as he introduces the themes and priorities for the day ahead. This brief session will lead into our opening panel, setting the focus for impactful discussions to follow.

1:45 PM - 2:30 PM

Main Stage - Executive Ballroom

Workshop

Bridging The Gap:
How to Design for the Human Factors That Impede AI Adoption

Agentic systems are fundamentally different from copilots and generative tools. Once AI can take actions, coordinate workflows, and operate across systems, it stops being a feature and starts behaving like a participant in the organization. That shift is already happening inside enterprises today.
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This opening session uses agents as the lens to examine what breaks first when intelligence starts acting: accountability, control, and governance. Through live discussion and real enterprise examples, we will explore how agentic architectures change decision ownership, where leaders lose visibility, and why traditional oversight models struggle once agents move beyond recommendation into execution.

What You Will Learn:

Defining “Agentic” in Enterprise Terms:

How to distinguish agents from copilots, automation workflows, and where the real step-change begins.

How Agents Reshape Decision Ownership:

Why accountability becomes unclear when agents trigger actions across tools and teams, and how leaders should rethink escalation and control.

How to Evaluate Agent Readiness Before Scaling:

A practical way to assess whether your data, processes, and governance are ready for agentic systems in production.

Sean McCall

Chief Data Officer

2:30 PM - 3:15 PM

Atrium

Opening Networking Break

This break includes a combination of open networking and pre-scheduled one-to-one meetings between select attendees and Summit partners. These meetings are a core part of the Day 1 workshop experience and are designed to connect executives with organizations actively supporting and shaping enterprise AI deployment.
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Participation in these meetings is part of how the Summit operates and enables the Institute to host small, high-touch workshops, executive discussions, and closed-door sessions throughout the event. Not all attendees will be scheduled for meetings during this break, but those selected should expect direct outreach and coordination on-site.

3:15 PM - 4:00 PM

Main Stage - Executive Ballroom

Workshop

Operating Agentic AI at Scale:
Designing Guardrails Without Slowing the Business

Once agentic AI systems begin acting across workflows, the challenge is no longer experimentation, it’s clearly control in production. Leaders need visibility into how AI behaves, confidence that guardrails are enforced, and the ability to intervene when systems drift, fail, or evolve.
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This session focuses on how enterprises are operationalizing control for agentic AI using real-time visibility, enforceable guardrails, and clear operating procedures. Credo AI will walk through how organizations are governing AI behavior in production without slowing teams down or reintroducing manual bottlenecks.

What You Will Learn:

Making Agent Behavior Visible in Production:

How leading organizations monitor, audit, and understand what AI systems and agents are actually doing over time.

Designing Guardrails That Actually Hold:

How teams enforce permissions, constraints, and escalation paths as agents act across data, tools, and workflows.

Operationalizing Governance Without Friction:

How governance becomes part of the AI lifecycle through observability, controls, and SOPs...not policies sitting on a shelf.

Moderator

Derek Mccoy

Vice President, Americas

4:00 PM - 4:50 PM

Executive Ballroom

Roundtable

Executive Roundtable:
Responsible AI: Governance, Ethics, and Safety

As AI technologies continue to evolve, robust data governance and ethical AI practices are more important than ever. This roundtable will delve into the development and implementation of data governance frameworks, privacy and compliance issues, and ethical considerations in AI deployment. Participants will discuss how to ensure AI safety and build public trust through responsible AI usage.

What You Will Learn:

Developing Internal Governance Frameworks:

Discover how to build governance structures that balance innovation with accountability. Learn to create internal guidelines that empower teams to innovate responsibly while maintaining strategic control.

Identifying Gaps in AI Roadmaps:

Uncover overlooked areas in your organization's AI roadmap, including potential governance gaps. Gain insights on how to address these challenges to strengthen your AI initiatives.

Cross-Functional Collaboration:

Understand the importance of involving diverse teams in AI projects. Learn how cross-departmental collaboration enhances risk mitigation, aligns objectives, and strengthens governance.

4:50 PM - 5:00 PM

Main Stage - Executive Boardroom

Present Your executive roundTables Findings

5:00 PM - 6:00 PM

Atrium

Closing Event

Cocktail RECEPTION

Beverage Menu:

Premium Spirits:

‍Tito’s Vodka

Balcones Whiskey

Tequila 512

Gosling's Rum

Hendrick’s Gin

Craft Beers:

Karbach Ranch Water

Karbach Love Street

Elegant Wines and Champagne:

‍Sauvignon Blanc: Kim Crawford

Prosecco: Lunetta

Chardonnay: La Crema

Pinot Noir: Mark West

Cabernet: Columbia Crest - Grand Estates

6:00 PM - 9:00 PM

Perry's Steakhouse - Vault Room

Intimate Think Tank Dinner - Invite Only

Perry’s Steakhouse - Vault Room (Short Walk From Workshop)

The Think Tank Dinner is a private, invitation-only gathering of senior executives, speakers, and partners.

Attendance is limited and separate from the Day 1 workshop. Participation requires explicit confirmation in advance. Walk-ins cannot be accommodated.

This dinner is designed for in-depth discussion and peer exchange in a small-group setting. Guests not confirmed for the dinner should plan to depart following the cocktail reception.

Think Tank Dinner - Night 1

Architecting Intelligence: How Modern Platforms, Data, and Agents Work Together

RSVP Your Seat Here

Leaders In AI Austin 2026
Day 2 Agenda

8:30 AM - 9:00 AM

Omni Austin Downtown Executive Ballroom

Arrivals & REGISTRATION

We will be meeting at the Leaders In AI Registration Desk at the front of the Omni Austin Downtown Hotel Executive Ballroom.
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If you have a confirmed Day 2 Main Summit Day VIP Pass, please arrive during this window to check in with your QR Code so you can receive your materials, and get settled before we begin promptly at 9:00 AM for our first panel discussion.

9:00 AM - 9:10 AM

Main Stage

Opening Remarks

Kick off the summit with opening remarks from Robert Jaggers, CEO of the Institute for AI Transformation, as he introduces the themes and priorities for the day ahead. This brief session will lead into our opening panel, setting the focus for impactful discussions to follow.

9:10 AM - 9:50 AM

Main Stage

Opening Panel

The Enterprise AI Playbook for 2026:
What Leaders Must Decide, Fund, & Stop

In an era of rapid disruption, organizations that neglect the human dimension of transformation fall behind. This dynamic panel of CXOs will reveal how people-centered approaches ignite progress, unite teams, and reinforce company culture. You’ll uncover practical methods to secure stakeholder buy-in, dismantle resistance, and foster an adaptable mindset that embraces ongoing evolution. Expect candid discussions on real-world success stories, alongside proven frameworks that keep your workforce energized and your organization moving forward.

Key Learning Objectives for the Audience

Active Buy-In & Alignment:

Explore the complexities of building stakeholder consensus—particularly when up to 70% of large-scale change initiatives fail due to insufficient engagement. Panelists will discuss how to secure cross-functional support, reduce friction, and unify teams to accelerate growth.

Embedding Agility & Resilience:

Examine the critical need for adaptable cultures ready to embrace new processes. Panelists will provide insights on developing resilience at every level of the organization, ensuring a confident response to market shifts and fostering an environment that propels innovation.

Measuring & Sustaining Adoption:

Discover how to track the impact of transformation efforts well beyond the launch phase. Panelists will share approaches for maintaining momentum through transparent metrics, iterative improvements, and leadership commitment—transforming early wins into lasting results.

Sean McCall

Chief Data Officer

Rameshwar Balanagu

Chief Architect Officer

Donna Bauer

VP, AI & Data

Vino Kingston

Data & AI Transformation Strategy & Integration Leader

Moderator

Bruce Monaco

Co-Founder / Head of Research

9:50 AM - 10:30 AM

Main Stage

Featured Panel

Data Storytelling:
The Executive Skill Set That AI Can’t Replace

This panel will examine how human expertise and training data play a pivotal role in shaping Generative AI systems. This panel will explore how human input—through methods like reinforcement learning and hybrid architectures—refines model accuracy, addresses bias, and improves ethical compliance. Industry leaders will share strategies for balancing automation with human oversight to enhance decision-making processes, scale responsibly, and ensure that AI systems remain aligned with organizational and societal values.

Key Learning Objectives for the Audience

Refining AI Outputs with Human Expertise:

Understand how human-in-the-loop systems improve the quality, accuracy, & reliability of GenAI by integrating human judgment into training & decision-making processes.

Scalable and Ethical AI Oversight:

Explore strategies for implementing human-in-the-loop practices that address bias, hallucinations, and ethical risks while maintaining efficiency and scalability in AI systems.

Advancing AI Governance and Leadership:

Learn how human oversight frameworks, including reinforcement learning and hybrid architectures, can empower leaders to ensure responsible and trustworthy AI deployment at scale.

Sailesh Bharathwaaj

Head of AI Center of Excellence

Michael R. Boone

Manager, Trustworthy AI

Rajesh Janu

Director of Agentic Trust

Moderator

Bruce Monaco

Co-Founder / Head of Research

10:30 AM - 11:30 AM

Atrium

Opening Networking Break

11:30 AM - 12:00 PM

Main Stage

Featured Panel

Transforming Healthcare:
From AI Pilots to Clinical-Grade Systems

Healthcare organizations are under pressure to deploy AI at scale while operating in one of the most regulated, data-constrained environments in the enterprise. Leaders are moving past experimentation and asking harder questions: where AI truly improves outcomes, where risk increases, and how systems can be trusted inside clinical and operational workflows.

This panel brings together healthcare data and AI leaders to discuss how organizations are operationalizing AI across care delivery, supply chains, and enterprise operations. The focus is not on future promises, but on what is working today — how leaders are navigating data access, governance, and validation to move AI from pilots into production without compromising safety, compliance, or performance.

Key Learning Objectives for the Audience

- Deploying AI in Data-Constrained Clinical Environments:

How healthcare organizations are using synthetic data, model tuning, and controlled access strategies to innovate while protecting patient privacy and meeting regulatory requirements.

Making AI Trustworthy for Clinical and Operational Use:

How leaders validate, monitor, and govern AI systems so outputs can be trusted by clinicians, operators, and executives — not just data science teams.

Scaling AI Without Disrupting Care Delivery:

How enterprises are integrating AI into real workflows, reducing friction for clinicians and staff while ensuring reliability, accountability, and measurable impact.

Kumar Melam

Director, Data Science & Enterprise AI

Mohan Krishna

Business Intelligence & Data Analytics Leader

Mayank Kumar

Director, Data Science & Enterprise AI

Moderator

Bruce Monaco

Co-Founder / Head of Research

12:00 PM - 12:25 PM

Main Stage

Case Study

human-validated synthetic data generation

Which LLMs actually reduce cost and risk when deployed at enterprise scale for data generation?

TrainAI by RWS will share findings from its human-validated synthetic data generation study which compares the performance of 8 leading LLMs on content generation, conversation generation, text normalization and translation performance, against each other as well as against human-generated content.

Results reveal where AI meaningfully reduces production effort, where hidden quality gaps drive rework, and why model choice must follow use case and language footprint. Attendees will gain a practical framework to evaluating LLMs and understanding where humans-in-the-loop can truly add value, so they can deploy AI globally with greater confidence.

Key Learning Objectives for the Audience

Understand Where Synthetic Data Actually Delivers ROI

Learn which types of data generation tasks meaningfully benefit from LLM-driven synthetic data, where AI reduces production effort, and where hidden quality gaps still create downstream cost and rework.

Scalable and Ethical AI Oversight:

Gain a practical framework for comparing LLM performance across content generation, conversational data, normalization, and translation—understanding why model choice must align to specific use cases and global language requirements.

Define the Right Role for Humans-in-the-Loop

Understand where human validation materially improves quality, reliability, and risk management in synthetic data pipelines, and where human oversight adds little value at scale.

Tomáš Burkert

Head of Innovation @ TrainAI

12:25 PM - 1:00 PM

Atrium

Lunch Hosted By the
institute for ai transformation

1:00 PM - 1:50 PM

TABLES 1-8

Executive Roundtable Discussions

Executive Roundtables Topic 1

AI Governance, Risk, And Compliance:
Enabling Scale Without Slowing Momentum

As AI becomes embedded in core business processes, leaders are being asked to manage risk and accountability without stalling progress. Governance is evolving from static policy into an ongoing operational function that must adapt as models, data, and use cases change.

Topic 1 Discussion Points:

Measuring Tangible Benefits:

Techniques for quantifying direct financial gains from AI initiatives, such as cost reductions, increased revenue, and efficiency improvements.

Evaluating Intangible Benefits:

Methods for assessing intangible benefits like improved customer satisfaction, enhanced decision-making capabilities, and innovation acceleration.

ROI Frameworks:

Overview of various frameworks and models used to calculate AI ROI, including Total Cost of Ownership (TCO) and Value-at-Risk (VaR) assessments.

Aligning AI with Business Goals:

Strategies for ensuring that AI projects are closely aligned with organizational objectives and key performance indicators (KPIs).

Executive Roundtables Topic 2

Hybrid AI Infrastructure:
Balancing Cloud, Edge, And Cost

Preparing your business for the future involves adopting and integrating AI technologies that can scale and evolve with emerging trends. This roundtable will focus on strategies for building scalable AI infrastructure, optimizing AI performance, and navigating multi-cloud environments.

Topic 2 Discussion Points:

Infrastructure Optimization:

Explore strategies for building and scaling AI infrastructure that can handle growing data and processing demands efficiently.

Performance Enhancements:

Discuss methods for optimizing the performance and efficiency of AI workloads, including leveraging edge computing and hybrid cloud solutions.

Enterprise Integration:

Examine best practices for integrating AI seamlessly across various enterprise functions, from R&D to supply chain management.

Navigating Multi-Cloud Environments:

Learn how to effectively manage AI operations across multiple cloud platforms, ensuring flexibility, security, and cost-effectiveness.

Executive Roundtables Topic 3

The Human Layer Of AI:
Adoption, Trust, And Organizational Change

Beyond models and infrastructure, AI success increasingly depends on how people interact with intelligent systems. Leaders are navigating new dynamics around trust, decision ownership, and changing roles as AI becomes part of everyday work.

Topic 3 Discussion Points:

Framework Development:

Learn how to develop and implement robust data governance frameworks that ensure data quality, integrity, and accessibility.

Privacy and Compliance:

Address the complexities of data privacy and compliance, and explore strategies for maintaining regulatory standards in AI initiatives.

Ethical AI Deployment:

Engage in discussions on mitigating biases in AI models, ensuring transparency, and promoting ethical AI practices.

AI Safety:

Discuss best practices for ensuring AI safety, including risk management strategies and the development of safety protocols.

Executive Roundtables Topic 4

Agentic AI At Scale:
From Experiments To Enterprise Impact

As enterprises move beyond AI pilots, agentic systems are emerging as a new layer of intelligence across workflows, applications, and decision making. While experimentation is widespread, scaling agents introduce new challenges around reliability, coordination, and organizational trust.

Topic 4 Discussion Points:

Infrastructure Optimization:

Explore strategies for building and scaling AI infrastructure that can handle growing data and processing demands efficiently.

Performance Enhancements:

Discuss methods for optimizing the performance and efficiency of AI workloads, including leveraging edge computing and hybrid cloud solutions.

Enterprise Integration:

Examine best practices for integrating AI seamlessly across various enterprise functions, from R&D to supply chain management.

Navigating Multi-Cloud Environments:

Learn how to effectively manage AI operations across multiple cloud platforms, ensuring flexibility, security, and cost-effectiveness.

1:50 PM - 2:30 PM

Main Stage

Present Your executive roundTables Findings

2:30 PM - 3:30 PM

Session Location

Afternoon Networking Break

3:30 PM - 4:00 PM

Main Stage

Closing Panel

Hard-Earned Wins:
What It Really Takes to Operationalize Enterprise AI

Enterprise AI adoption isn’t about quick wins or one-off pilots — it’s about the hard-earned lessons that transform experimentation into real business impact. This fireside chat cuts through the hype to explore what it actually takes to drive adoption across a complex organization. From standing up sandbox environments and leveraging synthetic data, to building frameworks for use case intake and collaborating with Finance on productivity-based ROI, this session offers practical insights on scaling responsibly. You’ll learn how to activate employees through grassroots programs like Office Hours and Hackathons, use AI to augment — not replace — teams, and unlock the hidden value of unstructured documents. Leaders will leave with actionable strategies for navigating cultural resistance, aligning stakeholders, and embedding governance that evolves alongside innovation.

Key Learning Objectives for the Audience

Breaking Through Adoption Barriers:

Learn how to create structured, low-risk experimentation environments using sandbox setups, obfuscated/synthetic data, and use-case intake frameworks to identify real value opportunities.

Human-in-the-Loop at Scale:

Explore how AI can augment — not replace — employees, expanding team capabilities through tools like Copilot and intelligent automation that empower generalists and specialists alike.

Governance You Can Use:

Walk away with a real-world perspective on how to assess vendors, stay aligned with shifting policy landscapes, and embed governance into everyday AI operations.