The South's Largest
Data + AI Trade Show

October 1, 2026 | ATL

Built for Fortune 500 Trailblazers

COLLIDE is where decision-makers from the South's (U.S.) largest enterprises and leading-edge solutions and service providers come together to build the foundations of the AI-driven era.

Connect with enterprise data + AI leaders

Scale and govern AI responsibly at scale

Benchmark with peers at roundtables and dinners

Featured 2026 Speakers

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

COLLIDE » Data Science Connect

Sergey Fogelson

VP, Head of Data Science

COLLIDE » Data Science Connect
COLLIDE » Data Science Connect

Anqi Zou

SVP, Head of Fair & Responsible Banking Analytics

COLLIDE » Data Science Connect
COLLIDE » Data Science Connect

Ram Kumar

Sr. Director - Networks, Automation and Analytics

COLLIDE » Data Science Connect
COLLIDE » Data Science Connect

Jyoti Mohapatra

General Manager - Data & AI Architecture

COLLIDE » Data Science Connect
COLLIDE » Data Science Connect

Charity Burroughs

VP, Data Governance & Quality Oversight Leader

COLLIDE » Data Science Connect
COLLIDE » Data Science Connect

Danny Portman

Head of AI Engineering, VP Data Science

COLLIDE » Data Science Connect
COLLIDE » Data Science Connect

Pavan Emani

SVP Engineering Leader,
Gen AI & ML

COLLIDE » Data Science Connect
COLLIDE » Data Science Connect

Abdullah Bokhari

Director, Enterprise Data Engineering

COLLIDE » Data Science Connect
COLLIDE » Data Science Connect

Malathi Bandlamudi

AVP Software Engineering

COLLIDE » Data Science Connect
COLLIDE » Data Science Connect

Sameer Goyal

Director Data Analytics & Software Engineering

COLLIDE » Data Science Connect
COLLIDE » Data Science Connect

Nathan Ghadirifard

VP, Business Data & Architecture

COLLIDE » Data Science Connect
COLLIDE » Data Science Connect

Keyur Vyas

Sr. Director,
Software Engineering

COLLIDE » Data Science Connect

More Speakers TBA Soon!

Save Your Spot Now

All-Access Pass
(IN-PERSON)

$499 $999

Skip the application process and secure your in-person, all-access pass to the COLLIDE Data+AI Conference by registering today with our “Super Early Bird” discount.

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

– All general and breakout sessions, including presentations and panels

– Breakfasts, lunches, and networking receptions

– Exhibit Hall

– Private networking app

complimentary pass
(IN-PERSON)

FREE $999

COLLIDE Data+AI Conference 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 data or AI-related products or services

2. You work at a non-vendor organization with 250+ employees

3. You hold a senior-level executive or technical position

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

Media Pass (FREE)

If you’re a journalist, influencer, or media professional actively reporting on AI and data-centric subjects, apply for our complimentary Media Pass! 

To be eligible, you must currently be engaged in journalism, influencing, or media activities, specifically focused on AI or data-oriented topics.

All applications will be reviewed by our team, and acceptance is highly selective.

COLLIDE » Data Science Connect

Venue

Sandy Springs Performing Arts Center

Opened in 2018 and located less than 15 miles from Midtown Atlanta, Sandy Springs Performing Arts Center is a best-in-class performance venue and conference center.

Featuring two large theaters with stunning acoustics and lighting, as well as spacious, well-lit, atrium-style exhibitor halls, the venue is the ideal space to highlight your brand.

Surrounded by a four-acre city park, restaurants, retail, and world-class hotels, the venue serves as the visually-stunning centerpiece of one of Metro Atlanta’s top live-work-play developments.

Why They Keep Coming Back

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.
COLLIDE » Data Science Connect

This Year's Content Pillars

COLLIDE » 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
COLLIDE » 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
COLLIDE » 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
COLLIDE » 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