AI 1.0: What’s Working. What’s Not. What’s Next. (Supplier Community EXCHANGE! – May 21, 2026)

Every vendor deck makes AI sound solved. On a supplier team defending a P&L through line-review season, the reality is messier. Cynthia Bonner, Founder and CEO of Agent Army, moderates a Supplier Community EXCHANGE! panel that skips the forecasts and runs the honest pass with three people putting AI to work inside the Walmart ecosystem right now: Rishi Bhatnagar (Founder and CEO, QuaerisAI), Dennis Gatts (U.S. Sales Leader, Nfinite), and Garrison Roddey (Business Development, Traverse Group).

Bhatnagar argues the economics have flipped: the level of analytics that once cost enterprises a fortune now runs for pennies on the dollar, which changes who can compete. Gatts makes the case that when the shopper starts and finishes the transaction on a screen, your product visuals have quietly become your product, and production costs have fallen far enough to matter to your next line review. Both keep hitting the same wall on on-shelf availability: seeing the problem faster is not the same as fixing it faster. The figures they put on visual-production speed, on how many AI projects fail and why, and on what one supplier’s online sales did after a roughly $1,500 video are worth hearing in their own words.

In this conversation, you’ll learn:

• Why the biggest beneficiaries of AI may be midsize and smaller suppliers, not the enterprises that could always afford insight
• How Walmart’s own data cadence should change what suppliers demand from their on-shelf availability reporting
• What separates real AI from intelligent automation, and why chasing features can sacrifice security and governance
• Why your product visuals now function as the product itself once the shopper journey starts online
• How a roughly $1,500 video moved one supplier’s online sales, and what that signals for digital-shelf budgets
• What’s behind the estimate that a large share of AI projects fail, and the expectation-setting mistake driving it
• Why the distance between seeing an OSA gap and resolving it is the live problem AI still hasn’t closed
• How to think about platforms, prompting, and data governance before you sign off on another tool

Rather than treating AI as a forecast to be impressed by, this conversation reframes it as an operating decision suppliers are already making, tool by tool, with real money and governance risk on the line.

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