Analysts have characterized the recent strength in the stock market as an AI rally, but flying under the Magnificent Seven’s radar is Walmart — a company so vast that it literally has its own weatherman.

And as it turns out, the retail juggernaut’s scale and reach are proving to be tremendous assets in the AI race.

That’s because most top AI companies — like OpenAI, Microsoft, Anthropic, or Meta — operate in a primarily virtual space, processing unfathomably complex rivers of information into more digital information. AI-adjacent companies like Nvidia, Intel, and Oracle focus on providing the physical infrastructure upon which the AI machines function. Then there are the companies that are using digital intelligence to deliver physical results through automation and augmented experiences, like Tesla and Amazon.

Walmart, by contrast, has a vast and complicated set of physical challenges to solve as the largest retailer in the US — and the world. Those include everything from cleaning up spills in the dairy aisle to stocking shelves.

“We move billions of items around every month, every year,” Walmart US CEO John Furner said Tuesday at the Fortune Brainstorm Tech conference. He said the company has been developing machine learning tools and other automation projects since around 2015.

Furner said that the company’s AI models and supply chain automation help plan inventory to arrive at the right aisle at the right time, for example. One technique involves creating “digital twins” of each facility to model the movement of merchandise through the system on its way to customers.

Furner also said store associates increasingly have an AI chatbot handy via their handheld devices to help them better set priorities and help customers.

“It’s a combination of people being powered by technology. There’s a lot of judgment to retail and decision-making. And we’re in a very dynamic industry,” he said. “We think this next phase of physical AI in combination with Gen AI is going to be really helpful.”

The company’s head of e-commerce, David Guggina, told the Goldman Sachs Communicopia and Tech conference last week how AI is helping his team run experiments and fulfill orders at an increasingly rapid rate.

Guggina said his team is now able to work at breathtaking speed behind the scenes, too.

“What took a data scientist days or weeks before can now be done in minutes,” he said.

AI also helps ensure that each of the company’s 4,700 stores has the kinds of products best suited to their local markets, slashing delivery times to minutes after a customer places an order.

“We’ve just completed the third inning,” he said by way of the classic baseball game analogy. “So we’re still early with regard to our automation journey in the fulfillment network.”

These digital-to-physical uses of AI are also complemented by a myriad of “micro agents” that handle tasks like tracking local event calendars or monitoring inventory levels.

Walmart, of course, is still fine-tuning its AI approach, and there have been hiccups.

The proliferation of bespoke Walmart-made AI agents eventually started to confuse users, the company told the Wall Street Journal.

The company has rolled many of those micro agents into four “super agents” designed to assist shoppers, merchandisers, programmers, and third-party marketplace sellers.

Still, because Walmart’s 20,000-strong global tech team builds so many of these digital and physical solutions in-house, the company is emerging as an unexpected AI powerhouse.

The company snagged former Instacart exec Daniel Danker in July to accelerate its AI efforts.

It’s also deepening its partnership this month with OpenAI via a new training program for associates and enterprise access to ChatGPT tools for frontline Sam’s Club employees to help operate their warehouse stores more smoothly.

After all, while chatbots might sometimes hallucinate answers, there’s no faking a cold gallon of milk on your doorstep.

MBW Reacts is a series of analytical commentaries from Music Business Worldwide written in response to major recent entertainment events or news stories. Only MBW+ subscribers have unlimited access to these articles. The below article originally appeared in Tim Ingham’s latest MBW+ Review email, issued exclusively to MBW+ subscribers last week.

So. What are we going to do about it?

MBW reported Thursday (September 11) on some startling new statistics from French streaming service Deezer.

Important: Deezer might be a relative minnow in global streaming terms, but its catalog-ingestion patterns broadly reflect the rest of the DSP world.

Deezer said that its service is now absorbing over 30,000 new, fully-AI-made music tracks per day.

That volume accounts for 28% of the total uploads reaching the service every 24 hours.

Think on this: The 28% stat is up from 10% in January, and 18% in April.

Sorry to shriek, textually speaking, but I’m going to put this next bit in red, because someone has to.

At that rate of growth, fully-AI-made tracks will account for more than 50% of all new music hitting streaming services by the time the 2026 World Cup swings around.

So.

What are we going to do about it?

One place we can start is by refusing to swallow the nonsense.

The tech utopian argument on this topic always comes back to… let the customer decide.

Examples:

• If someone loves a 100% AI-generated track, what’s wrong with that? Why should human-made pop music automatically get elevated beyond machine-made audio?
• Also, how dare the music industry tell a tone-deaf logistics manager, expressing himself with a few clicks of a mouse on Suno, that he’s not a ‘real musician’? Haven’t your oh-so-human A&Rs and producers gotten hooked on autotune and machine-learned trickery in the studio for the past decade? Chasing half-interested and bot-driven streams to win a race of your own making?

Fair points.

But what’s this?

“Deezer has found that up to 70% of the streams generated by fully AI-generated tracks are in fact fraudulent.”

Ah. So now we know: the primary motivation for consumption of this Suno/Udio-made ‘slop’ isn’t, in fact, because it’s great.

Nor is it out of respect for an innovative new form of creative expression.

It’s because there’s a racket to be exploited.

It’s because of that most human thing: greed.

Deezer’s 70% fraud stat shows the lie to a claim from Suno’s VC investor, Lightspeed Partners, that the platform is making music “more inclusive, creative, and rewarding for everyone involved”.

More rewarding?!

Try telling that to the artist having her streaming royalties sucked away by bot-made, bot-consumed, audible tripe.

To Deezer’s credit, once its platform detects this kind of fraudulent activity, it blocks those streams from its royalty pool. The service also blocks 100% AI tracks from algorithmic recommendations and editorial playlists.

Are other music services being as vigilant? Perhaps not.

Remember that Amazon recently integrated Suno directly into Alexa, two months (!) after publicly stating that Amazon Music would “address unlawful AI-generated content”.

Wild. Like opening a liquor store outside Alcoholics Anonymous.

So. What are we going to do?

Let’s start at the start.

This isn’t about debating the creative merits of robot symphonies. It’s about wiping out a new, and rapidly escalating, form of fraud.

A good start would be cross-platform tech collaboration on anti-fraud activity, coupled with a strict set of industry anti-fraud standards at DSPs.

Beyond that, harsher financial punishments for those distributors pushing torrents of AI slop onto DSPs while promising not to do so.

Especially when that AI slop is then being rinsed by bot-farms.

Happily for those clinging on to hope for humanity… there was some good news buried in Deezer’s latest data: human listeners, real listeners, are largely rejecting AI-made music.

Deezer says that despite those 30,000 daily AI uploads, just 0.5% of streams on its platform today are of fully-AI tracks.

Omit the 70% of those streams that have been deemed fraudulent, and it means just one in every 700 plays on the service are of robot-made music.

It obviously helps that Deezer blocks fully-AI tracks from its editorial and algorithmic playlists/recommendations.

But let’s not coddle ourselves into thinking there isn’t a giant problem brewing.

In plain terms: There are now 10 million+ fully-AI tracks hitting music streaming services each year. And Deezer’s stats suggest nearly three-quarters of the plays of these tracks are from bot farms.

While we debate whether AI tunes have ‘artistic value’ (and while major record companies simultaneously sue, and negotiate with, Suno/Udio), industrial-scale fraudsters are attempting to systematically loot music’s core machinery.

Lightspeed Partners claimed last year: “Suno is shifting the world of music towards one in which more and more people can express their creativity through music.”

According to Deezer’s data, its output is also shifting the economics of music further and further into the arms of sharks, grifters, and thieves.

Music Business Worldwide

The rising popularity of Bausch + Lomb’s daily single-use contact lenses led to a massive manufacturing challenge. To keep up with demand, the company had to quickly expand capacity at two production facilities, in Ireland and New York.

The higher volume also drove Bausch + Lomb’s CEO, Brent Saunders, to embrace new AI software, which helps manufacturing workers monitor, test, and fix mechanical issues.

The technology, called Atlas and produced by Arena AI, is designed to predict machinery issues before they arise and send alerts to maintenance workers so they can diagnose errors and fix them.

Saunders said that Atlas was tested in Rochester in 2023 and, by last year, had been added to three new contact-lens production lines. “We’re seeing millions of lenses being produced that we wouldn’t have otherwise been able to produce without the Atlas AI,” Saunders told Business Insider.

Some 77% of the manufacturers plan to increase their AI investments over the next year, according to a July survey by KPMG of 183 AI manufacturing leaders across eight countries. Startups like beauty brand Prose, pet food maker Spot & Tango, and home battery producer FranklinWH are among the companies embracing AI in new manufacturing facilities that they’ve recently opened.

AI is helping startups manufacture more pet food and batteries

Dylan Munro, the chief operating officer and cofounder of Spot & Tango, said the company opened its first-ever manufacturing facility near Allentown, Pennsylvania, because the company wanted to better control the quality of the dog food it sells.

When the facility opened in late 2022, employees were responsible for manually coordinating raw materials from suppliers, scheduling production based on the availability of those ingredients, and booking trucks to coordinate the pickup and delivery of goods.

Since then, AI adoption has allowed Spot & Tango to scale its production without the need to hire more employees, according to Munro.

He told Business Insider that his company began to pilot an agentic AI tool sold by Didero, an AI supply chain management startup. The tool can log purchase orders, confirm them, and build appropriate production schedules based on ingredient availability. Meanwhile, Spot & Tango’s logistics team oversees these AI-enabled decisions.

A small group of Spot & Tango workers tested Didero’s AI tool with real-life procurement scenarios for three months before the company made it widely available to employees, said Munro. The company said this system now fully automates around 60% of purchase orders.

FranklinWH Energy Storage, which sells home batteries intended for power backup during outages, is using AI to help address customer service requests and within production, said Vincent Ambrose, the COO at FranklinWH. It added AI for the first time at a California production facility that opened earlier this year.

The facility features AI-enabled visual inspection, which uses cameras to closely monitor the production of lithium iron phosphate home batteries and flag quality issues, a procedure that workers used to do. The AI model continuously learns from production data to predict problems before they occur.

FranklinWH also produces in Asia, where AI isn’t utilized, but could be added later. “If we upgrade those facilities, I’m sure we’ll take what we’ve learned from our US manufacturing,” said Ambrose.

Automation helped Prose lower its shampoo-making costs

Arnaud Plas, the CEO and cofounder of Prose, said the company’s adoption of AI and automation has lowered the cost of manufacturing. When the company initially launched in 2017, factory-line workers assembled bottles manually, which contributed to a $5 production markup for Prose’s made-to-order, custom shampoos and moisturizers, which are developed based on customers’ hair surveys. Now, autonomous robotics is responsible for mixing Prose’s formulas.

“We wanted that incremental cost to be under $1,” said Plas.

The company achieved this goal in 2024, partly by automating formula mixing and bottle filling, but also due to the application of 200 algorithms that Prose’s machine learning and data scientists developed. These algorithms assist with the company’s demand planning, product formulations, predictive maintenance for machines, and more efficiently scheduling production, so there is less downtime needed to clean the machinery.

The company added AI and automation capabilities to a second manufacturing facility in California, which Prose opened in June. Plas said that 90% of Prose’s production now features automation and the influence of AI algorithms.

Munro, the Spot & Tango COO, said that he continues to field a lot of pitches from AI vendors promising big supply chain optimization, but approaches them with skepticism.

Munro said that some AI solutions pitched by vendors can encounter unforeseen technical challenges or slower-than-expected adoption from workers.

“We don’t want to rush to implement,” he said.