People, Culture &amp; Leadership

The AI Context Engineer: How the Modern Data Team Is Changing

WisdomAI's Geetesh Iyer explains why AI analytics pilots fail at scale, why semantic layers aren't enough, and the rise of the AI context engineer.

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.

The AI Enterprise Conference · November 6, 2026

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.

The AI Enterprise Conference · November 6, 2026

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.

The AI Enterprise Conference · November 6, 2026

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.

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.

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.

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.

AI Data Governance at Speed: Governance by Design, Not as a Blocker

Leaders from Quest Software, ADP, WellStar and Carter's explain how to scale AI data governance with trust scores, risk reviews and hub-and-spoke teams.

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.

Wendy's FreshAi: Lessons From Generative AI in the Drive-Thru

Wendy's Will Croushorn on how FreshAi handles 95% of drive-thru orders, why word choice is data, and how a 'sorry' metric cut friction by 60%.

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.

Trusted AI at Scale: Walmart's Super Agents, AT&T's AI Board and More

Leaders from Walmart, AT&T, Kellanova and TelevisaUnivision discuss building trust in AI agents, governance boards, model upgrades and agent sprawl.

How to Detect Shadow AI and Replace It With Tools Employees Want

Airia's Dave Horton and Rahul Parwani explain why AI bans fail, how to detect shadow AI in layers, and how AI champions drive sanctioned adoption.

Why Data Democratization Fails, and How Enterprises Close the Gap

AtScale, T-Mobile and Mars data leaders on why self-service data efforts stall, hub-and-spoke governance, data literacy and AI's pressure on readiness.

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.

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.

Responsible AI: How TD Bank, TelevisaUnivision and Vertex Build Trust

TD Bank, TelevisaUnivision, Vertex and Truist leaders on LLM privacy risks, AI ethics boards, explainability, generative AI security and data minimization.