The retail world was reborn at record speed with three unstoppable forces.

New shelves quickly emerged. Agentic, social, and quick commerce are already radically changing the way consumers shop; now shoppers discover what they want to buy before getting to a retail shelf, via social pages, AI agents, and the like—and more buy products in the same channel. Agentic commerce alone will influence about $1 trillion in US consumer spending by 2030—16% of total US retail sales and about 56% of total US e-commerce. One recent study found that 70% of China’s shoppers made a social commerce purchase in the past 12 months. 

Retailers strategically reinvented their business model. By 2035, nearly half of all retailer profits will come from “beyond trade”—spanning retail media networks, marketplaces, payments, and data (see Figure 1). US retail media spending hit $58.8 billion in 2025. Meanwhile, the global private brand market is projected to reach $1.6 trillion by 2034, as consumers buy private brands not just for price but also for quality. 

Figure 1

And retailers gained a major head start in data and tech. Retailers’ efforts and investments have enabled them to obtain better consumer data than CPGs have. They now make millions of segmented pricing, promotion, and assortment decisions instantaneously, and already leverage AI agents for negotiation.

While these trends are universal across countries, channels, and categories, they’re at different stages of maturity. For example, China leads the way in social commerce, while India leads in quick commerce. Retail business model reinvention is happening faster in the US than elsewhere.

Next-channel disruption is now heaviest in categories like beauty products, where social commerce and online influencers play an expanding role. Yet today’s least disrupted categories will eventually feel the effects. For example, confectionary and impulse categories have been viewed as protected, but these have already been disrupted in China by social commerce, quick commerce, and the new snacking channel.

Winning retailers have been extremely agile over the past several years in how they have transformed to capture these trends—their future was under threat from new digital-native competitors. As a result of their rapid and bold response, retailer market caps have gained positive momentum compared with those of consumer products companies.

Now there is a growing risk for CPGs to become irrelevant in this new reality. Consumer products’ share of retailer profits already is low, and consumers’ embrace of private brands is a sign that shoppers are becoming less brand conscious. At the same time, retailers’ technology investments now give them rapid access to exclusive consumer insights. A third force compounds the threat: AI agents now sit between CPGs and consumers. Nearly half of US shoppers already lean on AI to shop, and most are ready to let it buy for them. Agents don't see brand equity—they reward concrete, review-backed attributes and discount vague positioning. If an agent doesn't select you, you don't exist. The most important customer in CPG may soon be an algorithm. 

But CPGs that adapt their commercial model now can not only remain relevant but also strengthen their leadership and leapfrog competitors.

Winning CPGs take four big pragmatic bets.

Win on the next shelf. This means intentionally shifting resources to where consumer demand is growing the fastest and capturing future control points. While top retailers and insurgent brands have heartily embraced next-shelf commerce, many large CPG playbooks are insufficient in this new world, in which the “shelf” is an algorithm and the “store” is a livestream or app. Leading companies pick one next shelf and go all in. Every next-shelf channel they enter is simultaneously a revenue bet and an intelligence asset that requires dedicated capability building. Some winners see next-shelf growth in excess of 50%.

L'Oréal increasingly treats creator and social content as a full-funnel commerce channel—driving discovery as well as acquisition and conversion—and measures creators against commercial outcomes. The company works directly with OpenAI to feed product detail pages and SKU-level information for thousands of products via a direct data feed into ChatGPT, optimizing for generative engine optimization (GEO). Maybelline New York will bring its ModiFace-powered virtual makeup try-on technology directly into ChatGPT, allowing consumers to discover and test makeup looks through conversational AI—and then buy on the spot. 

Reinvent how to work with retailers. The best consumer products companies make themselves indispensable to a retailer's growth agenda. Their focus is on targeting what’s core to the retailers—data, retail media, and category growth, for example—developing the right capabilities to do so and rebasing trade terms and investments accordingly. In Mexico, Procter & Gamble shifted its relationship with retailers from a supplier-client dynamic to data-driven strategic partnerships, and from short-term tactical planning to longer-term joint business planning. Working with retailers, it cocreated advanced programs that use AI to analyze top customer data in the digital journey for mutual benefit. Its efforts in Mexico have enabled Procter & Gamble to capture 60% of category growth in that market, according to the company.      

The expectation from retail partners is that 80% of the joint business planning discussions should now be about consumer and shopper data through clean team setup, retail media, category growth, traffic generation, co-manufacturing of private brands, and other joint initiatives—and less so about pricing, promotions, and assortment decisions that can now be automated. 

By building a global beauty tech data platform, L'Oréal has turned its data infrastructure into a commercial asset with its retail partners—leveraging proprietary data to bring a perspective on key drivers for category growth in the next years and putting marketers directly into customer conversations so that retail media is jointly optimized as a growth lever.

Reimagine frontline ways of working with tech and AI. Commercial AI empowerment is a business transformation across processes designed to fundamentally change capabilities and ways of working to improve decision making and drive growth while managing costs.

In modern trade, retailers are already digitalizing and agentifying most of their commercial processes—from pricing to negotiations—to improve efficiency and effectiveness. This is forcing CPGs to accelerate their own AI-enabled commercial transformation. Key account managers and the field force will move from making pricing, promotion, and assortment scenarios for joint business planning and negotiations to managing the agents that do. It’s a massive change in capabilities that can enable decisions that are more consistent, fact-based, precise, and agile—accelerating growth and profitability. The improvement augments key account managers, and the time saved can be reinvested in category growth discussions and strategic relationship building with customers.

In traditional trade, the challenge is in delivering growth at scale in a fragmented environment. Millions of small-format stores across Asia, Africa, and Latin America represent an enormous opportunity that has historically required more feet on the street to capture. The new model is fundamentally different. AI now synthesizes outlet-level data and micro market dynamics to give each rep a prioritized call plan, resulting in fewer wasted visits and human capital that finally performs at its true potential. Reps can spend more time on the strategic tasks that deliver growth.

The CPGs that are most successful will be those that view the challenge as a business transformation, not primarily an AI and tech transformation. They will invest in capability building and change management, looking for ways to improve end-to-end processes, remove silos, and establish a unified growth engine spanning insights generation, negotiation, and in-outlet execution.

Build a superiority moat for proprietary intelligence. This starts with identifying a core competence where the company wants to be indispensable to its consumers and customers. That could mean owning 360-degree category insights or owning the channel infrastructure to build more intimacy with consumers, for example. Companies like AB InBev and Procter & Gamble show what it takes.

AB InBev made a deliberate, long-term bet: that its digital route to market could outperform its physical one, and that technology, AI, and data were the way to own its customer relationships in a way competitors simply could not replicate. The brewer now uses the data obtained through BEES, its business-to-business e-commerce and digital platform, to generate previously unattainable consumer insights for pricing and promotion decisions.

P&G built first-party data collection directly into its products, with connected devices like the Oral-B iO smart toothbrush and Lumi by Pampers feeding usage data into brand apps, which P&G consolidates on Google Cloud. That gives the company a unified view of the consumer across brands and channels, empowering its innovation agenda and ability to bring differentiated insights to customers.