Leaders In AI Summit Nashville 2026
Our Summit's
Leaders In AI SUmmit Nashville
Day 1:
12:45 PM - 6 PM
Day 2:
9:00 AM - 6 PM
August 18th-19th
Gaylord Opryland Resort & Convention Center
Featured Speakers
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Leaders In AI nashville
2026 Agenda
Begins at 12:45 PM
Gaylord Opryland Resort & Convention Center
Pre-Summit Workshop Hotel Check-In
We recommend checking in at Gaylord Opryland Resort & Convention Center before 12:30 PM to give yourself time to settle in and get oriented ahead of the day’s programming. While there’s no formal check-in window and we understand travel schedules may vary, early arrival is encouraged to ensure a smooth start.
For any questions regarding your stay or early check-in assistance, please contact the Gaylord Opryland Resort & Convention Center front desk directly or connect with our team onsite.
Begins at 1:00 PM - 1:30 PM
Leaders In AI Summit Registration Desk
Registration & Networking
Upon arrival between 1:30 PM and 2:00 PM, please proceed directly to our registration area to check in. Simply provide your name and confirmation details at the welcome desk, where you'll receive your event badge and session materials. Once checked in, you’ll have time to meet fellow attendees and orient yourself before sessions begin promptly at 2:00 PM. Our onsite team will be available throughout the registration window to assist with any questions or special requests.
1:30 PM - 2:30 PM
Gaylord Opryland Resort - Main Stage
AI Deployment Workshop
Sovereign AI in the Age of Agents:
Architecture, Control, and the Economics of Autonomy
Sovereign AI has become one of the most discussed concepts in enterprise technology. But what does sovereignty actually mean when your AI systems are autonomous agents? Agents consume tokens at 15-50x the rate of chatbots, make decisions regulators will scrutinize, and interact with your enterprise data in ways most architectures were never designed for. This workshop presents a five-dimension framework for sovereign AI in the agentic context: compute sovereignty, token sovereignty, data sovereignty, decision sovereignty, and operational sovereignty.
Each dimension maps to specific architecture decisions, from right-sizing across the full infrastructure stack to preparing enterprise data for agent-native consumption. Grounded in token economics analysis showing up to 18x cost advantages through infrastructure ownership and real-world deployment architecture from regulated industries, this session gives enterprise leaders a practical framework for maintaining control as agentic AI moves into production environments.
What You Will Learn:
- The Five Dimensions of Sovereign AI for Agents:
Sovereign AI in the agentic context requires control across five dimensions: compute, token economics, data, decision governance, and operations. You will get a practical framework that maps each dimension to specific architecture decisions and organizational capabilities, with particular focus on regulated industries like financial services and healthcare.
- Token Sovereignty as a Scaling Enabler:
Agentic AI workflows consume 15-50x more inference tokens than chatbots, making token economics the primary constraint on deployment scale. You will learn how infrastructure choices (on-prem vs. cloud, model routing, share dinference pools) create up to 18x cost advantages per million tokens and give organizations the degrees of freedom to scale agents without runaway costs.
- Data Readiness for the Agentic Enterprise:
Just as SEO gave way to GEO (optimizing contentfor AI-driven search), enterprise data must be restructured for agent-native consumption. You will learn how agentic AI changes the way data is accessed, retrieved, and acted upon, and what steps organizations should take now to prepare their internal datasets for a world where agents, not analysts, are the primary data consumers.
Jason Hamp
Commercial AI Technologist
Moderator
Bruce Monaco
Co-Founder / Head of Research
2:30 PM - 3:15 PM
Atrium Outside Main Stage
Afternoon Networking Break
3:15 PM - 4:00 PM
Gaylord Opryland Resort - Main Stage
AI Deployment Workshop - Part 2
Bridging The Gap: How to Design for the
Human Factors That Impede AI Adoption
The first workshop explored the technical foundations of enterprise agentic AI. This session shifts the focus to the people, leadership, and organizational changes required to realize business value at scale. As AI becomes embedded across every business function, organizations must rethink how teams work, leaders make decisions, and employees collaborate with intelligent systems.
We’ll explore practical strategies for accelerating enterprise adoption through operating model redesign, AI literacy, workforce enablement, and executive leadership. Attendees will leave with a framework for building AI-ready organizations that can adapt quickly, scale responsibly, and turn AI investments into lasting business outcomes.
What You Will Learn:
Building an AI-Ready Workforce:
Learn how leading organizations are reskilling employees, developing AI literacy, and empowering teams to confidently integrate AI into their everyday work.
- How Agents Reshape Decision Ownership:
Explore how operating models, business processes, and decision-making structures are evolving as AI becomes embedded across the enterprise.
- Leading Enterprise AI Transformation:
Discover practical leadership strategies for driving adoption, overcoming organizational resistance, and creating a culture that enables continuous innovation and measurable business impact.
Sean McCall
Chief Data Officer
Moderator
Bruce Monaco
Co-Founder / Head of Research
4:00 PM - 4:45 PM
TABLES 1-8
Executive Roundtable Discussions
Executive Roundtables Topic 1
AGENTIC AI ARCHITECTURES:
BUILDING THE AUTONOMOUS ENTERPRISE
As enterprises deploy AI agents into production, success depends on far more than selecting a foundation model. This discussion explores enterprise context, Model Context Protocol (MCP), APIs, orchestration frameworks, and production architectures required to build secure, reliable, and scalable agentic AI systems.
Topic 1 Discussion Points:
- Enterprise Context, Memory & Retrieval:
Explore how organizations are leveraging RAG, vector databases, knowledge graphs, enterprise memory, and real-time business context to improve agent reasoning, accuracy, and decision quality.
- MCP, APIs & Enterprise Integration:
Discuss strategies for integrating AI agents with enterprise applications through Model Context Protocol (MCP), APIs, tool calling, enterprise connectors, and secure data access frameworks.
- Agent Orchestration, Observability & Governance:
Examine the architectures, orchestration frameworks, monitoring capabilities, and governance practices required to coordinate multi-agent systems and operate autonomous AI reliably at enterprise scale.
Executive Roundtables Topic 2
THE ECONOMICS OF ENTERPRISE AI:
Cost, Value & Strategic Decisions
As AI adoption accelerates, organizations are navigating increasingly complex investment decisions across infrastructure, models, software, data, and talent. This discussion explores how enterprises are managing total cost of ownership, reducing shadow AI and fragmented technology investments, modernizing legacy IT environments, and measuring long-term business value from AI.
Topic 2 Discussion Points:
- Total Cost of Ownership & AI Investment:
Explore the full financial impact of enterprise AI, including infrastructure, software, data modernization, implementation, governance, and long-term operational costs.
- Enterprise Procurement & Vendor Strategy:
Discuss approaches for evaluating AI platforms, foundation models, infrastructure providers, and strategic technology partnerships while reducing duplication, managing risk, and avoiding vendor lock-in.
- Business Value, ROI & Token Economics:
Examine how organizations are measuring AI investments through business outcomes, productivity gains, token consumption, inference costs, utilization, and long-term enterprise value.
Executive Roundtables Topic 3
HYBRID AI INFRASTRUCTURE:
COMPUTE, LATENCY & ENTERPRISE SCALE
Enterprise AI infrastructure is rapidly evolving as organizations balance public cloud, private infrastructure, edge computing, and sovereign AI environments. This discussion explores workload placement, compute optimization, latency requirements, and the infrastructure strategies required to deploy AI reliably at enterprise scale.
Topic 3 Discussion Points:
- Workload Placement & Infrastructure Strategy:
Explore how organizations are evaluating cloud, on-premises, edge, and sovereign AI environments while optimizing workload placement based on cost, security, latency, performance, and regulatory requirements.
- Compute, Memory & Performance Optimization:
Discuss strategies for maximizing GPU utilization, addressing HBM memory constraints, optimizing networking and storage, and improving both training and inference performance across enterprise AI workloads.
- Enterprise AI Operations & Scalability:
Examine the operational frameworks, observability, resiliency, and infrastructure automation required to scale production AI workloads while balancing reliability, latency, availability, and cost.
Executive Roundtables Topic 4
Enterprise AI Transformation:
People, Process & Change Management
Successfully scaling AI requires organizations to rethink how people work, how decisions are made, and how business processes are designed. This discussion explores the leadership, operating models, workforce strategies, and change management practices required to turn AI investments into lasting business outcomes.
Topic 4 Discussion Points:
- Operating Model Transformation:
Explore how organizations are redesigning business processes, operating models, governance structures, and decision-making to embed AI across core business functions.
- Enterprise Adoption & Workforce Enablement:
Explore strategies for driving enterprise-wide adoption while aligning AI initiatives with business objectives and measurable outcomes.
- Leadership, Talent & Change Management:
Examine how executive leadership, organizational culture, change management, and cross-functional alignment are accelerating AI transformation while reducing resistance and sustaining long-term adoption.
4:45 PM - 5:00 PM
Gaylord Opryland Resort - Main Stage
Present Your executive roundTables Findings
5:00 PM - 6:00 PM
Gaylord Opryland Resort Bar
After-Party
Cocktail Hour
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
Old Hickory Steakhouse - Inside Gaylord
Intimate Think Tank Dinner - Invite Only
Directly After Day 1 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 & Day 2 Main Summit. 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.
8:30 AM - 9:00 AM
Gaylord Opryland Resort & Convention Center
Arrivals & REGISTRATION
Start your Leaders In AI Summit experience by checking in at the Leaders in AI Summit hosted at the luxurious Gaylord Opryland Resort & Convention Center in Nashville, Tennessee. Our VIP Registration Team will greet you in the lobby with your VIP badges and a complimentary gift bag. Enjoy artisan coffee, tropical fruit, and pastries while you prepare for an exciting day of insights and exclusive networking.
9:00 AM - 9:10 AM
Gaylord Opryland Resort - 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
Gaylord Opryland Resort - Main Stage
Opening Panel
THE RACE FOR ENTERPRISE AI:
AGENTS, INFRASTRUCTURE & EXECUTIVE DECISIONS
AI initiatives hold the promise of transformation, yet many organizations struggle to move beyond pilot phases, leaving potential value unrealized. Research shows that the majority of AI pilots stall due to misaligned goals, resource limitations, and insufficient cross-functional buy-in. These challenges often lead to delayed ROI, wasted investments, and reduced stakeholder confidence. This panel will uncover the key reasons why pilots fail and offer actionable strategies to build scalable, enterprise-wide AI frameworks that deliver meaningful results.
Key Learning Objectives for the Audience
- Identify Core Barriers to Scaling AI:
Understand the most common pitfalls in AI pilot projects, including resource inefficiencies, skill shortages, and organizational misalignment.
- Develop an effective Enterprise-Wide Framework for AI:
Gain insights into embedding AI initiatives within business units, fostering ownership, and aligning projects with strategic goals to achieve production-ready success.
- Deliver ROI Through Scalable AI:
Gain insights into optimizing resource allocation, aligning AI investments with measurable outcomes, and sustaining stakeholder confidence.
Sean Mccall
Chief Data Officer
Travis Nixon
Chief Data and AI Officer
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Pietro Fabiani
Enterprise AI Leader for FSI & Manufacturing
Moderator
Bruce Monaco
Co-Founder / Head of Research
Jason Hamp
Commercial AI Technologist
9:50 AM - 10:30 AM
Gaylord Opryland Resort - Main Stage
Featured Panel
The Enterprise AI Playbook for 2027:
What Leaders Must Decide, Fund, & Stop Doing
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.
Steven Darrah
General Manager Enterprise Solution Sales
Chaitanya Garikapati
Head of Data & Analytics
Wendy Abbott
Senior Director, AI Foundry
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Peter Manta
AI Strategy & Practice Director
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Moderator
Bruce Monaco
Co-Founder / Head of Research
10:30 AM - 11:30 AM
Atrium
Opening Networking Break
11:30 AM - 12:10 PM
Gaylord Opryland Resort - 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.
Justin T. Collier, MD
Healthcare CTO, North America
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Chad Zoretic
Managing Director | Practice Leader
Kumar Melam
Director, Enterprise AI & AI Governance
Moderator
Bruce Monaco
Co-Founder / Head of Research
12:10 PM - 12:55 PM
Atrium
Lunch Hosted By the
institute for ai transformation
12:55 PM - 1:20 PM
Gaylord Opryland Resort - Main Stage
Featured Panel
Guardians of the Digital Galaxy:
Navigating Cybersecurity in the AI Era
In the critical panel 'Guardians of the Digital Galaxy: Navigating Cybersecurity in the AI Era,' we explore the intersection of AI and cybersecurity, a domain where digital threats evolve as rapidly as the technologies to counter them. This session charts the transformation from early digital defense systems to today's battle against sophisticated AI-powered cyber threats, highlighting AI's dual role as both a formidable ally and a potential adversary in cybersecurity.
As AI systems evolve beyond passive assistants into autonomous technologies capable of executing workflows, coordinating decisions, and interacting directly with customers, organizations are entering a new era of agentic commerce. The challenge is no longer simply implementing AI tools, but determining how autonomous systems can operate responsibly across customer experiences, transactions, service environments, and enterprise workflows.
Key Learning Objectives for the Audience
- AI as Both Asset and Threat:
A comprehensive understanding of the dual role of AI as both a formidable asset and a potential threat in the realm of cybersecurity.
- Risk Management in High-Stakes Industries
Strategies that are most effective in high-stakes industries, such as healthcare or finance, to ensure AI safety is not compromised by the pursuit of innovation.
- Emerging Threats and Trends:
Insights into the latest AI-driven cybersecurity threats and trends that are shaping the security landscape.
Conrad Bell, Jr
SVP, Chief Information Security Officer
Dana Reed
Field Chief Technology Officer
Bryan Mylius
CISO, VP Information Technology Operations and Infrastructure
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Moderator
Bruce Monaco
Co-Founder / Head of Research
1:20 PM - 2:10 PM
TABLES 1-8
Executive Roundtable Discussions
Executive Roundtables Topic 1
AGENTIC AI ARCHITECTURES:
BUILDING THE AUTONOMOUS ENTERPRISE
As enterprises deploy AI agents into production, success depends on far more than selecting a foundation model. This discussion explores enterprise context, Model Context Protocol (MCP), APIs, orchestration frameworks, and production architectures required to build secure, reliable, and scalable agentic AI systems.
Topic 1 Discussion Points:
- Enterprise Context, Memory & Retrieval:
Explore how organizations are leveraging RAG, vector databases, knowledge graphs, enterprise memory, and real-time business context to improve agent reasoning, accuracy, and decision quality.
- MCP, APIs & Enterprise Integration:
Discuss strategies for integrating AI agents with enterprise applications through Model Context Protocol (MCP), APIs, tool calling, enterprise connectors, and secure data access frameworks.
- Agent Orchestration, Observability & Governance:
Examine the architectures, orchestration frameworks, monitoring capabilities, and governance practices required to coordinate multi-agent systems and operate autonomous AI reliably at enterprise scale.
Executive Roundtables Topic 2
THE ECONOMICS OF ENTERPRISE AI:
Cost, Value & Strategic Decisions
As AI adoption accelerates, organizations are navigating increasingly complex investment decisions across infrastructure, models, software, data, and talent. This discussion explores how enterprises are managing total cost of ownership, reducing shadow AI and fragmented technology investments, modernizing legacy IT environments, and measuring long-term business value from AI.
Topic 2 Discussion Points:
- Total Cost of Ownership & AI Investment:
Explore the full financial impact of enterprise AI, including infrastructure, software, data modernization, implementation, governance, and long-term operational costs.
- Enterprise Procurement & Vendor Strategy:
Discuss approaches for evaluating AI platforms, foundation models, infrastructure providers, and strategic technology partnerships while reducing duplication, managing risk, and avoiding vendor lock-in.
- Business Value, ROI & Token Economics:
Examine how organizations are measuring AI investments through business outcomes, productivity gains, token consumption, inference costs, utilization, and long-term enterprise value.
Executive Roundtables Topic 3
HYBRID AI INFRASTRUCTURE:
COMPUTE, LATENCY & ENTERPRISE SCALE
Enterprise AI infrastructure is rapidly evolving as organizations balance public cloud, private infrastructure, edge computing, and sovereign AI environments. This discussion explores workload placement, compute optimization, latency requirements, and the infrastructure strategies required to deploy AI reliably at enterprise scale.
Topic 3 Discussion Points:
- Workload Placement & Infrastructure Strategy:
Explore how organizations are evaluating cloud, on-premises, edge, and sovereign AI environments while optimizing workload placement based on cost, security, latency, performance, and regulatory requirements.
- Compute, Memory & Performance Optimization:
Discuss strategies for maximizing GPU utilization, addressing HBM memory constraints, optimizing networking and storage, and improving both training and inference performance across enterprise AI workloads.
- Enterprise AI Operations & Scalability:
Examine the operational frameworks, observability, resiliency, and infrastructure automation required to scale production AI workloads while balancing reliability, latency, availability, and cost.
Executive Roundtables Topic 4
Enterprise AI Transformation:
People, Process & Change Management
Successfully scaling AI requires organizations to rethink how people work, how decisions are made, and how business processes are designed. This discussion explores the leadership, operating models, workforce strategies, and change management practices required to turn AI investments into lasting business outcomes.
Topic 4 Discussion Points:
- Operating Model Transformation:
Explore how organizations are redesigning business processes, operating models, governance structures, and decision-making to embed AI across core business functions.
- Enterprise Adoption & Workforce Enablement:
Explore strategies for driving enterprise-wide adoption while aligning AI initiatives with business objectives and measurable outcomes.
- Leadership, Talent & Change Management:
Examine how executive leadership, organizational culture, change management, and cross-functional alignment are accelerating AI transformation while reducing resistance and sustaining long-term adoption.
1:45 PM - 2:30 PM
Gaylord Opryland Resort - Main Stage
Present Your executive roundTables Findings
Up next, each roundtable will share their key takeaways with the full audience. Please designate one representative from your table to go on stage and briefly present your group’s findings and discussion highlights.
2:30 PM - 3:30 PM
Atrium
Afternoon Networking Break
3:30 PM - 4:10 PM
Gaylord Opryland Resort - Main Stage
Featured Panel
Data Readiness for the Agentic Enterprise:
Building the Trusted Foundation for Enterprise AI
Enterprise AI is entering a new phase. As organizations move beyond copilots toward autonomous agents capable of executing real business processes, success now depends on trusted enterprise data, effective governance, and production ready AI architectures rather than simply selecting the right foundation model.
This executive panel explores how leading organizations are preparing for agentic AI through stronger data readiness, governance frameworks, enterprise context, and human oversight. Join senior AI, data, and technology leaders as they discuss the architectural decisions, governance strategies, and operational best practices required to deploy trusted AI systems that scale securely, deliver measurable business value, and earn enterprise wide confidence.
Key Learning Objectives for the Audience
- Building Trusted Enterprise Data Foundations:
Learn how leading organizations are preparing enterprise data for AI by improving data quality, governance, metadata, lineage, and enterprise context so intelligent agents can operate with confidence.
- Balancing Speed, Control & Human Oversight:
Explore practical governance models for deploying agentic AI, including human-in-the-loop, human-on-the-loop, policy guardrails, risk management, compliance, and responsible decision-making at enterprise scale.
- Operationalizing Agentic AI Across the Enterprise:
Understand the infrastructure, orchestration, APIs, enterprise integrations, and operational practices required to securely deploy AI agents into production while maintaining observability, auditability, and continuous governance.
Lee Roland
Generative AI Specialist and Architect
SANCHIT SRIVASTAVA
Senior AI Manager - Data Analytics
Jacob Vetter
Director, Fraud AI & Data Science
Moderator
Bruce Monaco
Co-Founder / Head of Research
4:10 PM - 4:50 PM
Gaylord Opryland Resort - Main Stage
Featured Panel
Navigating the Human element of 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.
Justin Bumpus
Senior Vice President of IT
Mitch Hodus
Sr. Director IT Architecture, Infrastructure & Operations
Moderator
Bruce Monaco
Co-Founder / Head of Research
4:50 PM - 5:00 PM
Gaylord Opryland Resort - Main Stage
Closing Remarks
5:00 PM - 6:00 PM
Gaylord Opryland Resort Bar
After-Party
Cocktail Hour
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
Hal's the Steakhouse - Nashville
Intimate Think Tank Dinner - Invite Only
Directly After Day 2 Main Summit
The Think Tank Dinner is a private, invitation-only gathering of senior executives, speakers, and partners.
Attendance is limited and separate from the Day 2 Main Summit. 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.
Leaders in AI Nashville 2026
Think Tank Dinners
Leaders In AI Nashville 2026: Night 1 Dinner Room A
Race for Enterprise AI:
Agents, Infrastructure & Executive Decisions
Leaders In AI Nashville 2026: Night 1 Dinner Room B
Open Models, Enterprise Control:
Infrastructure, Trust & Choice in the Agentic AI Era
Leaders In AI Nashville 2026: Night 2 Dinner
From Investment to Impact:
Rethinking AI Infrastructure for Cost, Performance, and Enterprise Scale
Summit Location
Gaylord Opryland Resort
2800 Opryland Dr, Nashville, TN 37214
info@iaitransform.com
Let’s TRANSFORM
HUMANITY together
Join us for an exclusive intimate event experience like no other.