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      Brief

      The Future of Consumer Products in the Age of AI

      The Future of Consumer Products in the Age of AI

      To move from “hype” to “hyper returns,” consumer products companies need to scale AI and build bold new competitive advantages.

      By Rajesh Narayan, Joao Valadares, and Holger Kömm

      • min read
      }

      Brief

      The Future of Consumer Products in the Age of AI
      en
      Executive Summary
      • Today’s leading consumer products companies (CPs) face performance challenges that are likely to be worsened by the next wave of digital technology.
      • To win in the age of AI, CPs must boldly reinvent how they innovate, make, sell, and compete.   
      • CPs that scale AI could expand EBITDA by 3–5 percentage points—enough to offset rising costs, fund innovation, and protect competitive positioning.
      • Most CPs recognize this urgency—but need a new approach to scale AI with meaningful results.

      A decade of disruption has eroded traditional CP advantages

      Over the past five years, stagnant volumes and declining pricing power have led to a sharp slowdown in topline growth across the consumer products sector. Rising material and labor costs are squeezing margins, and it’s become harder to pass price increases on to cost-conscious consumers.

      Historically, large consumer products companies (CPs) could weather these pressures by leaning on their scale, supply chains, and brand strength. But those historical advantages are no longer enough.

      Over the past decade, successive waves of digitization have eroded the power of scale. During the first wave of change, enterprise process automation helped CPs entrench scale benefits, and bigger players became more efficient. In the second wave, new digital channels emerged, lowering barriers to entry and enabling smaller brands to connect with consumers at scale—without huge capital outlays or big footprints.

      As a result, digital-first insurgents—adept at direct-to-consumer, omnichannel platforms and social media—have used technology to capture an outsized share of growth. Meanwhile, retailers seeking new revenue streams have fueled a surge in private label brands, rivaling the appeal of branded counterparts.

      The next wave of disruption is now accelerating. The third wave’s predictive, generative, and agentic AI systems are becoming intelligent, autonomous, and interconnected—not just digitizing activities and decisions but executing them with minimal human input. Emergent AI capabilities are reshaping the sector again, transforming how value will be created, captured, and competed for.

      Will the next wave of disruption capsize big CPs?

      As the pace of technological advancement picks up, it’s fundamentally shifting how the ecosystem operates and competes.

      Today’s technology is a significant leap ahead from the “cutting-edge” AI capabilities of three years ago. Predictive, generative, and agentic AI form a powerful combination, unlocking intelligence and autonomy at scale—for both businesses and consumers.

      The CP sector is experiencing this wave of disruption in three separate but simultaneous shifts:

      1. Agentic AI is reshaping consumer journeys.

      Agentic search is already redefining how consumers discover and choose products. An increasing number of consumers are turning to AI chatbots—not algorithmic searches—for product recommendations. For example, they might ask AI for a laundry detergent suited to their family size, washing machine, and environmental preferences. For now, AI tools are answering the queries based on product specifications and third-party reviews, without regard for SEO, paid search ads, branding, or negotiated shelf space (see Figure 1).

      Figure 1
      ChatGPT rarely repeats brands when asked to recommend the cheapest or healthiest options
      Source: Bain analysis

      2. AI is augmenting workforce capabilities. 

      Soon, humans will supervise large workforces of agents that analyze vast data sets, generate insights, and automatically execute thousands of micro-decisions a day.

      Ultimately, teams may become leaner as they leverage digital and AI platforms to accelerate work, make decisions, and scale. Some CPs may evolve into hybrid operators, using AI and partnerships to unlock speed without losing control over differentiating functions.

      3. AI is lowering competitive barriers. 

      AI won’t just supercharge CPs. Private labels and AI-native insurgents will leverage the same tools, intensifying competition and diluting traditional CP advantages. New players will be nimble and lean, leveraging shared data, open APIs, and plug-in architecture to adapt and scale with minimal overhead.

      Combined, these shifts mean the basis of competition is shifting, and battles to win share of the profit pool are intensifying. As a result, satisfying an agent's algorithm with user-generated content and markers of product quality is becoming increasingly important. As retailers and big tech players launch agentic shoppers, competition to own the customer journey and share of the profit pool is likely to further intensify.

      In this new landscape, product quality, discoverability, flexibility, and speed overpower historical CP advantages such as branding and shelf space. High-quality, proprietary data and real-time insights are becoming more critical sources of competitive advantage across the ecosystem. And so is adaptability to welcome a new type of talent: the AI agent.

      What will it take to win? Reinventing the enterprise

      In this new world, scale will still hold value. CPs will need to leverage their scale to invest in new technical capabilities—and bold new ways of working—to anticipate shoppers’ needs and respond with exactly the right products, at the right prices, at the right times.

      Reinvention will require new operating models that move fast enough to win, plus agility and efficiency from end-to-end. Scale CPs are currently exploring five “bold bets” to win:  

      • As barriers to entry continue to fall and new entrants develop and launch products even faster, R&D teams must dramatically compress innovation cycles. Scale CPs must shrink their timelines from months to weeks or days to keep up and remain relevant.

      • When agents act on behalf of consumers, marketing and brand teams will be required to optimize their products for agent-driven discovery rather than human-driven.

      • Sales teams must build tools to succeed in agent-to-agent negotiations. Key account managers will only handle exceptions—aided by real-time data on price-promo-assortment mixes.

      • Auto-regulated supply chains will be required to stay competitive on cost, continuously rebalance supply and demand, and fine-tune replenishment, pricing, substitutions, and production.

      • Intelligent back-office AI agents will be needed to unlock the next era of radical productivity improvements for end-to-end workflows. CPs have only seen incremental improvements since the 2000s, when ERP-enabled automation and standardization last drove radical improvements.

      Most CPs see the urgency but remain stalled

      Top-performing CPs recognize technology’s role in value creation in earlier waves of disruption. Today, CP leaders spend 1.2 times more on technology than laggards, and they invest more in differentiating capabilities, such as “change” initiatives, data, and AI (see Figure 2).

      Figure 2
      CP leaders invest more in customer-facing technologies, data, and AI

      Notes: Digital refers to the full digital budget, including data and AI; foundation includes ERP, support functions, and tech

      Source: Bain Consumer Products Digital Leadership Survey (n=52)

      AI’s evolving capabilities could further widen the gap between leaders and laggards. CPs that crack the code on scaling AI are likely to see faster innovation cycles, dynamic pricing, fine-tuned supply chains, and stronger margins. They can reshape P&L and unlock new sources of value, while everyone else races to catch up.

      Many CP leaders understand this—and AI is moving much higher on strategic agendas. Yet poor data foundations, lack of talent, and unclear ROI still stall AI initiatives. Nearly half of CPs (48%) are still in the “exploratory stage” of AI maturity, and almost none have successfully scaled it across their organizations (see Figure 3).

      Figure 3
      Despite being a “top priority,” most CPs have not delivered AI at scale

      Note: “No formal vision or use cases” refers to not seriously engaged with AI yet, “exploratory stage” refers to some pilots or isolated experiments underway, but no clear strategy or goal, “defined strategy and roadmap” refers to clear AI vision with prioritized use cases and a roadmap, though execution is still maturing, and “integrated and scaled strategy” refers to AI vision, roadmap, and value model are embedded in business planning, with aligned data, tech, and talent enablers

      Source: Bain Consumer Products Digital Leadership Survey (n=52)

      There are strong incentives for clearing these hurdles. As the ecosystem shifts, CPs who fail to leverage AI risk becoming irrelevant in this wave of disruption. More immediately, scaling AI could improve operating margins by 3–5 percentage points—enough to offset cost pressures, fund innovation, and strengthen competitive positioning.

      How to lead the transformation—and win

      To win this era of AI, CPs must:

      • Focus on business ambitions, not tech experiments. It’s easy to get dazzled by a million-dollar-return use case and lose sight of the bigger picture. However, AI builds must be linked to broader business value. Require leaders to define their “big bets” and create a path of use cases to get there. Then deliver, scale, and repeat.

      • Don’t use AI to patch bad processes. Leaders should embrace AI as an enabler for business reinvention, redesigning processes to maximize value creation in a touchless world.

      • Invest in effective operating models and governance. AI transformation requires collaboration among teams that haven’t historically worked closely. Leaders must clearly communicate a vision and guardrails to ensure that business, technology, and data teams operate as one.

      • Build the right foundations. Data, technology, and talent have never been more important. Without foundational data systems and skills, CPs will never be able to scale or capture the ROI they’ve committed to. Some of the talent needs are clear—but many roles are still being discovered and defined. Prepare to fight for and invest in scarce resources.

      • Boldly take costs out. Leaders will define clear indicators of success and link them to clear actions for capturing value. And they’ll keep taking costs out—whether that means retiring legacy systems or cost centers, reducing headcount, or shrinking footprints.

      In short, companies that successfully scale AI treat it as a business transformation: grounded in strategy, enabled by the right foundations, and sustained through operating discipline.

      The payoff? AI will finally live up to the hype and deliver hyper returns.

      The authors would like to acknowledge and thank the broader team that has contributed to developing the point of view, including Patricia Ottevanger, Elise Haak, Sarah Yates, Cassie Forman, Pieter Janssens, Duilio Matrullo, and Nikhil Ojha.

      Authors
      • Headshot of Rajesh Narayan
        Rajesh Narayan
        Partner, London
      • Headshot of Joao Valadares
        Joao Valadares
        Partner, Lisbon
      • Headshot of Holger Kömm
        Holger Kömm
        Partner, Munich
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