How to shape the future of AI in consumer products

Today’s business landscape is marked by rapid shifts, unpredictability, and deep interconnections. EY defines this world as NAVI — characterized by nonlinearity, acceleration, volatility and interconnectedness. Changes on the horizon range from steady evolution to transformative change, and from a cautious recalibration to a concentration of market power. This is not merely a thought experiment; companies that translate AI’s abstract potential into tangible products, business models and operational methods will emerge as leaders.

Future #1: Transform

By 2030 — AI is transforming business

In this scenario, the widespread adoption of advanced reasoning and agentic AI systems creates unprecedented opportunities for business innovation and value creation (via EY.com US). By 2030, enterprise-grade AI platforms have become robust, trustworthy and widely accessible, massively augmenting human capabilities and automating even complex workflows and activities across multiple domains. Democratizing AI enables organizations to completely reimagine how they work, creating lightweight and remarkably efficient organizational structures that enable human creativity and strategic thinking to be unleashed while unlocking latent market demand.

What it means for CP companies: Here, AI shatters the hype and reinvents society as a whole: how we live, how we work and how we shop. Agentic systems anticipate consumer needs, design products around them and run operations end to end. Consumers expect seamless, predictive experiences — and brands that cannot deliver disappear. The winners are those bold enough to rebuild their entire value chain around AI, re-engineering how products are made, moved, marketed and sold.

Key takeaway: AI becomes the operating system of the business where humans steer and AI drives.

Human to agent to automation ratio:

Future #2: Growth

By 2030 — AI is driving growth

In this future, AI capabilities advance steadily along current trajectories, driven by incremental improvements rather than major breakthroughs. Efforts to regulate the technology are outweighed by productivity gains from humans leveraging AI. By 2030, domain-specific AI agents have achieved remarkable proficiency in operational functions across finance, HR, legal and other business areas. This evolution enables new organizational models featuring highly automated back offices and AI-augmented front offices, delivering significant productivity gains and cost efficiencies.

What it means for CP companies: AI delivers — not explosively, but reliably. Agents drive greater productivity by autonomously handling routine tasks so that operations are scaled cost-effectively, while humans shift to higher-value roles in strategy and creativity. Consumers enjoy smarter personalization. The winners are companies that scale AI across the value chain from sourcing to service while still strategically leveraging the best of what humans can offer.

Key takeaway: AI augments work without replacing it and humans shift up the value chain.

Human to agent to automation ratio: 

Future #3: Constraint

By 2030 — AI is under close scrutiny

In this future of AI, adoption of the technology faces significant recalibration following a series of high-profile setbacks. By 2030, incidents such as AI trading system malfunctions impacting market stability, persistent errors in AI-powered financial reporting and medical AI misdiagnoses have led to new liability issues. Meanwhile, AI content generation has proved less commercially viable than anticipated. These challenges prompt a measured reassessment of AI regulation and AI implementation across markets.

What it means for CP companies: AI stalls as energy demands spike and regulations strangle progress. Returns on investment underwhelm and progress slows to a crawl. Consumers grow skeptical of the mechanical sameness of AI, and luxury goods boast “Not Made by AI” labels. The winners are brands that double down on human creativity and trust, optimizing traditional value chains while signaling authenticity at every touchpoint.

Key takeaway: AI underdelivers and humans remain central to value creation.

Human to agent to automation ratio: 

Future #4: Collapse

By 2030 — AI reshapes market dynamics

In this future of AI, a major technological breakthrough leads to extreme market concentration in AI capabilities. By 2030, a single entity achieves significant advantages in AI, creating powerful network effects that reshape market dynamics across all knowledge-based sectors of the economy.

What it means for CP companies: AI promised transformation but delivered exclusion. A handful of mega corporations control its benefits while for most, AI simply does not work. Models are inaccessible, data is locked, and talent is out of reach. Innovation has stalled. The majority are left with hype and no results. AI has not democratized progress; it has concentrated it.

Key takeaway: AI promised scale, but it scaled back.

Human to agent to automation ratio: 

Shaping the future — the CP strategic response

We’ve considered the impact of AI across the CP value chain and have defined possible strategic responses demanded by each of the four futures. Every CP company is different, but as a thought starter to bring this to life, we’ve explored options for a beverage company with an online presence:

Rather than waiting for clarity, leaders should act now, anchoring their AI strategy in a structured, scenario-based approach that supports long-term value creation.

We recommend a six-step process:

1. Envision

Begin with scenario planning. Use the four futures to explore how AI could reshape your business and define your ambition across multiple possible outcomes. This step aligns leadership around a shared vision and prepares the organization for a range of futures from transformation to constraint.

2. Assess

Evaluate your value chain and data readiness. Identify where AI can unlock value — whether in supply chain, marketing or customer service — and assess the maturity of your data, systems and governance. This ensures your ambition is grounded in operational reality.

3. Foundation

Before deploying AI, build the right foundation. This includes establishing cross-functional AI teams, investing in upskilling and ensuring your tech stack and data infrastructure can support scalable AI. Without this groundwork, even the best use cases may stall.

4. Activate

Launch high-impact use cases using reusable assets. Focus on quick wins that align with your vision and demonstrate tangible value. You do not need perfect data to start, but it must be relevant and sufficient to support early success.

5. Accelerate

Prove value and build momentum. Develop reusable models, pipelines and governance structures that can be applied across use cases. Establish clear KPIs like customer satisfaction or operational efficiency to track progress and guide reinvestment.

6. Implement, monitor and scale

Embed AI into workflows and operating models. Use strong governance and risk management practices to ensure responsible scaling. Monitor performance, adapt to market signals and continuously evolve your AI strategy as the future unfolds.

Conclusion: from possibility to preparedness

The future of AI in consumer products is not a single destination — it is a spectrum of possibilities. Whether we are heading toward transformation, growth, constraint or collapse, the companies that lead will be those that prepare for all four.

By envisioning multiple futures, building foundational readiness and scaling responsibly, organizations can move from abstract potential to concrete action. The six-step process outlined above provides a structured path forward, one that balances ambition with operational reality.

To guide this journey, leaders should ask:

• How can AI amplify and drive the most business value across our value chain?
• What gaps exist in our data, talent and technology foundations and how do we close them?
• How should we evolve our core systems, including ERP and global business services, to scale AI effectively?
• How can AI enable smarter, more personalized consumer experiences?
• What governance and risk frameworks are needed to ensure responsible implementation?

The future may be uncertain, but the opportunity to shape it is very real. The companies that act now — guided by foresight and grounded in strategy — will be the ones shaping what comes next. 

Summary

Facing so many potential futures with AI, consumer products companies need to adopt a structured approach to AI strategy that fosters adaptability and long-term value.