AI Strategy &amp; ROI

Context Over Compute: How a Semantic Layer Improves AI ROI

AtScale's Mark Palmer explains why context, not bigger models, drives AI ROI, and how semantic layers and accuracy testing cut errors.

Why AI Initiatives Get Stuck, and How Leaders Can Move Them Forward

Analytic Vizion's Nelson Davis says stalled AI initiatives are rarely a technology problem, and shares five questions to restore alignment.

Crum & Forster's 5 Lessons for Scaling Enterprise AI in Insurance

Crum & Forster leaders share how 91% employee AI adoption, unified data and embedded governance turned AI pilots into results.

Why the Enterprise AI Stack Needs a Control Plane for Agents

Xnode's Hemakumar Velugula explains why AI agents need data-layer access controls, unified policy and cost limits to reach production.

The Self-Funding AI Strategy: How Verisk Lets AI Pay for AI

Revefi's Girish Bhat and Verisk CDO Louis Dimodugno explain how cutting data and AI waste can fund new AI work, plus a 4-step playbook.

AI-Ready Data: Why Enterprises Are Bringing AI to Their Data

Everpure's Kaycee Lai explains what AI-ready data means, why unstructured data blocks production AI, and how to run AI where data lives.

AI Governance as Growth Strategy: SAS on Closing the AI Trust Gap

SAS's Reggie Townsend shares survey data on why 97% of people override AI and the five governance behaviors that set AI leaders apart.

AI Cost per Outcome: How Enterprises Prove Value as AI Spending Grows

Leaders from New Balance, Mastercard, Omnicom, Earnest and Crum & Forster on measuring AI value, cost per outcome, token usage and AI platforms.

Enterprise AI Agents: Validation Tax, Context and Scaling Past the Pilot

Tokio Marine, Morgan Stanley and Fedcap leaders on scaling AI agents: the validation tax, human on the loop, enterprise context and when to use workflows.

How AI Is Replacing Traditional BI, and Why Context Is the New Job

PromptQL's Adam Malone explains why text-to-SQL and semantic layers stall, and why analysts' future work is teaching AI how the business works.

Agentic AI With Mistral AI Studio: Why Enterprises Should Own Their AI

Mistral AI's Aaron Delp explains how to pick a first agentic AI use case, run a 3-4 week pilot and build governed workflows in Mistral AI Studio.

Why AI Pilots Fail to Scale, and How Enterprises Get to ROI

Snowflake, Revefi and Coca-Cola AI leaders explain why AI pilots stall, how to choose what to scale, and the 70-20-10 rule.

Building Enterprise AI Agents With Mistral: Right-Sized, Custom Models

Mistral AI's Aaron Delp demos no-code agents, OCR with MCP search and an FDA submission workflow, and explains model right-sizing and Forge.

AI Infrastructure at Scale: Semantic Layers, GPUs and Inference Costs

AtScale and Rhino Federated Computing leaders explain the infrastructure layers, governance and inference cost controls production AI and agents need.

AI Prototype to Production: What Makes Enterprise AI Apps Production-Ready

DataHub, Precisely, Snowflake and Fivetran leaders explain why AI prototypes stall, what enterprise-grade means, and why governance must start on day one.

Why AI Projects Fail: 4 Practical Fixes From Data Fluency to Trusted Data

Elder Research practitioners share four fixes for stalled AI projects: leadership data fluency, value-based prioritization, trusted data and data SLAs.

Measuring AI ROI: How to Tie Every Use Case to a Business OKR

Leaders from The Home Depot, Mars Wrigley and Equifax explain how to measure AI ROI, balance speed and cost, and set executive expectations.

AI Change Management: Building Trust and Upskilling the Workforce

Leaders from Coca-Cola, UnitedHealth Group, Clorox and Randstad Enterprise share how they build trust in AI, ease job fears and upskill employees.

The AI Production Gap: Why Bad Data, Not Models, Blocks AI at Scale

Syncari's Jack Smith explains why integration sprawl, data lakes and legacy MDM stall AI pilots, and how a centralized agentic MDM layer helps them scale.

Why AI ROI Stalls: Eight Analytics Gaps Leaders Can Diagnose

Elder Research's Jennifer Schaff explains eight gaps that erode AI ROI, from strategy misalignment to data literacy, with client stories and questions.

What Successful AI Teams Do Differently: Lessons From 120 AI Projects

Nanonets CEO Sarthak Jain shares lessons from 120 AI projects: plan a 6-18 month ramp, design for human intervention, fix data first and go bottom-up.

Human-Centered GenAI: Why Trust, Not Models, Decides Pilot to Production

Snorkel AI's Dennis Panos explains why GenAI pilots fail on trust, and how expert-built evaluations and data development move systems into production.

High-Performance Data Infrastructure for AI: Aerospike's Cost Case

Aerospike CTO Srini Srinivasan explains how hybrid memory cuts AI infrastructure costs and why agentic AI multiplies real-time database load.

How AI Enables More Human Leadership: Three Keystone Habits for Leaders

Analytic Vizion CEO Nelson Davis says AI raises the value of empathy, curiosity and judgment, and shares a matrix for when to automate decisions.

The AI Maturity Journey: Machine Learning, GenAI and Agents in One Workflow

KMS Technology CTO Guy Merritt explains how ML, generative AI and agents fit one workflow, and why AI coding gains vary from 3x to a slowdown.

Choosing AI Use Cases That Pay Off: A Data Executive's Guide to ROI

Leaders from AtScale, Snowflake, Denodo, Fivetran and Revefi on telling AI hype from value, build vs. buy, board pressure and use cases with proven ROI.

Scaling Enterprise AI: Why Trust and Monitoring Decide What Ships

AtScale, Monte Carlo and Revefi leaders on why AI pilots stall, how MCP makes queries deterministic, which KPIs prove value and how to govern fast.

Data Lakehouse Architecture for AI: Governance, Cost and Migration

Fivetran, General Mills and Webster Bank leaders explain how data lakehouses, Apache Iceberg and open catalogs support governed, cost-effective AI.

What Is an AI Factory? NVIDIA and HPE on Scaling Enterprise AI

NVIDIA and HPE leaders explain AI factories: compute, networking and software as a relay team, private cloud AI options, liquid cooling and AI strategy.

Low-Code and No-Code AI: Democratizing AI Without Losing Governance

Leaders from Informatica, ADP, LTK and Baptist Health South Florida explain how low-code AI speeds experimentation and what guardrails it needs.

The Hidden Costs of AI: Scaling ML From Notebook to Production

Tecton, Mosaic Health and JPMorgan Chase leaders explain the people, pipeline and premature-optimization costs of scaling ML to production.

Scalable RAG Systems: Cutting Cost and Securing Enterprise Retrieval

Tecton, Nexla and Novartis experts on scaling RAG: batch vs. real-time serving, smaller models, index sync, chunk-level access control and evaluation.

From Prototype to Production AI: Cutting Tech Debt and Train-Serve Skew

Tecton, Emory Healthcare and BBDO leaders on moving AI to production: tech debt, standardization, train-serve skew, automation and governance.

Future-Proof AI Infrastructure: Self-Hosted LLMs, Governance and Lock-In

SandboxAQ, Alteryx and Plotly engineers on self-hosted vs. cloud LLMs, governed AI access, data quality testing and avoiding vendor lock-in.

AI Risk and Reward Across Industries: Lessons From NORC, IHG and AT&T

NORC, IHG and AT&T leaders on AI risk in regulated industries, showing business value, governance sandboxes, fairness tools and scaling AI with quality.

RAG Use Cases: How UPS, TSYS and Shipt Put Retrieval-Augmented AI to Work

UPS, TSYS and Shipt leaders on retrieval-augmented generation: a digital twin operations copilot, internal use cases, RAG risks and prioritizing GenAI.

AI ROI Across the Project Life Cycle: Business Cases, Data and Cloud Costs

Bank of America, Carelon Health, Lockton and PRGX leaders on AI business cases, the three E's of ROI, data bottlenecks and controlling cloud costs.

Future of Enterprise AI: Nike, ADP and Yum! Brands on Human Oversight

Nike, ADP and Yum! Brands leaders on the future of enterprise AI: human in the loop, data strategy, governance as enablement and AI-first culture.

Generative AI Use Cases Beyond Chatbots: Lessons From Media and Retail

Leaders from Dollar General, Scripps, TelevisaUnivision, Vertex and PRGX on generative AI use cases beyond chatbots, plus security, validation and ROI.

AI Transformation From Hype to Reality: Norfolk Southern, Equifax, Baptist

Elder Research, Norfolk Southern, Equifax and Baptist Health on AI hype vs. reality, model drift, AI governance councils, talent and use cases that work.

AI Strategy Starts With Data Strategy: Southern Company, Clorox, Tecton

Southern Company, Clorox, Morgan Stanley and Tecton on aligning data and AI strategy: data quality, features as code, scaling pilots and real-time data.

ALIGN AI Executive Summits · June 8, 2026

Scaling Enterprise AI Means Treating It Like Software, Not Spectacle

At ALIGN AI Executive Summit ATL, leaders tackle the biggest questions around scaling AI that works for enterprise success and high ROI.