This Week In AI: Walmart Sets Fashion Trends Before They Ever Happen

#1 Google launched Agent2Agent

The Story: It’s Monday morning. As an AI-powered recruiter you work smarter, not harder. You log into your company’s dashboard on your phone. It tells you three critical roles have been sourced, vetted, and scheduled for interviews—all without a single direction from you.

What happened? First your AI agent reviewed your client’s needs. Next, another AI agent culled candidates off LinkedIn using live market data. Yet another AI agent background-checked those candidates, clearing the top picks.

Importantly, none of these agents were built by the same company. In the past this would be a problem. They wouldn’t be able to “talk” to each other.

Not anymore—enter Agent2Agent (A2A), Google’s new open protocol.

Why It Matters: A2A gives AI agents a shared language. Suddenly, bots can communicate and collaborate across platforms like never before. Welcome to the Internet for AI workers. AI agents from Salesforce, PayPal, SAP, and 50 others can now sidestep the old Tower of Babel problem.

To put it another way: They now speak the same operational tongue.

Moving forward, agents won’t just automate tasks within their own spheres. They will form multi-agent swarms much like The Avengers, solving

complex, cross-platform problems in real time. Just don’t let them drop the Infinity Stones into the wrong hands.

#2 Walmart Supercharges Fashion Trends—Courtesy of AI

The Story: What if future fashion could be predicted with AI oracle abilities? Here’s how it will work. A major clothing label like Sonoma decides it cannot waste any more money as clothes linger for ages on packed racks. After all, weeks—if not months or even years—can elapse between the moment a fashion influencer drops a viral video and the time it takes to get product(s) to stores.

By then a fashion trend will have died—and with it—revenue.

This is the problem Walmart’s new AI tool, Trend-to-Product solves. It compresses design and development timelines. Now instead of waiting for fashion trends or even chasing them, the massive retailer is setting them, combining fast-fashion alacrity with data-driven precision. If we accept the premise AI now knows our tastes better than we do, it’s all about giving customers what they want—before they even know they want it.

Why It Matters: Again, Walmart’s Trend-to-Product AI Tool works proactively. How? It scours social media, search trends, and purchasing data to act as a modern fashionista Cassandra. Its crystal ball discerns patterns to predict what styles will blow up—then guides the requisite design, sourcing, and inventory decisions in double time.

Years ago, Walmart adapted and revolutionized Just-In-Time (JIT) delivery for retail, making them a global logistics powerhouse. Now, they’re evolving again to speed up conversion rates.

Their AI tool portends a next level shift in retail agility.

Clothing manufacturers can now glimpse into the future, enabling unprecedented go-to-market nimbleness. Imagine cutting your timetable from six months to six weeks. It mitigates the risk of overproduction and unsold inventory—long the albatross around so many retailers’ necks. More, it enables hyper-responsiveness to consumer behavior, enabling businesses to capitalize on fashion’s fickleness with minimal lag.

Where will predictive analytics go next?

My money’s on entertainment. What if prescient AI could suggest the next big movie based on scouring the zeitgeist for a wave before it crests?

#3 AI Gets a Seat at the Top: White House Demands Federal AI Leaders

The Story: Everyone knows government moves at glacial speed. That’s why no one at the Department of Transportation expected their backlog of infrastructure grant applications to get through review without it taking months. And months.

That was until a newly appointed Chief AI Officer took the reins.

We’ll call him Chuck. In the name of efficiency, Chuck rolled out an AI protocol that slashed review times by 80%. Suddenly, applications were flying by, getting stamped good-to-go or unapproved in weeks, if not days.

Meanwhile, across town, the Department of Health and Human Services had its own systemic problems. Medicaid fraud patterns continue to proliferate, escaping the notice of human workers doing their best to spot such trickery.

That was until a newly appointed Chief AI Officer took the reins.

We’ll call her Becky. Becky directed AI’s powers of pattern detection to super use, detecting scams and cons that once evaded human notice.

Why It Matters: Fictional for now, these breakthroughs aren’t isolated—they’re part of a sweeping White House directive. Every federal agency must now have a Chief AI Officer. Meant to modernize government operations and cut red tape, it reminds me of another story I published this week on how the corporate sector is also using AI to go on the compliance offensive: Overwhelmed By Compliance? AI Could Save Your Business.

Now that government is busy unlocking the kind of efficiency private industry is also tackling, it’s important to ask the question: how long until the public starts to demand AI leaders over human politicians?

That’s not as farfetched as you might think.

Last year Eric Schmidt, Henry Kissinger and Craig Mundie published Genesis: Artificial Intelligence, Hope, and the Human Spirit, examining how AI will empowers humanity to address its monumental challenges in novel ways.

The authors wonder when people will abdicate more authority to AI as it becomes increasingly intertwined in every aspect of life. “Today’s human leaders should prepare to be the first in a line of human sovereigns to face the struggle of locating a balance between leveraging the advantages—and, in some cases, the need—for AI in governance without going so far as to succumb to total dependency, instead finding the proper synthesis between the extremes of despotism and anarchy, merging the will of humans, the knowledge of machines, and the wisdom of history.”

Caution is still needed.

While AI’s ability to fix government inefficiencies is impressive, we must be cautious not to over-rely on it. More, we need to ensure its ethical deployment. We don’t want a situation where generations from now, citizens cannot recall a time where AI wasn’t running everything.

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That’s it for this week. Tune in next for the latest developments. In the meantime, here’s to making us all smarter in the Intelligence Age.

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