Why Testing AI Like a Smartphone is a Mistake – And What Consumer & Retail Companies Should Do Instead

Imagine you’re evaluating a brand-new smartphone, but instead of exploring its camera, apps, or AI-driven features, you judge it solely by how well it makes phone calls. That would be absurd, right? I was inspired by a recent post by Ethan Mollick making this comparison and this is exactly how many companies approach testing AI today—focusing on narrow, outdated benchmarks rather than exploring its potential for transformational innovation.

The latest generation of AI models, like Claude 3, aren’t just incremental improvements; they represent a new kind of intelligence. Companies that insist on evaluating AI based on how well it replicates existing tasks are missing the point. Instead, the real question should be: What completely new possibilities does AI unlock that we haven’t even imagined yet?

Beyond the Obvious: AI’s Untapped Potential in Consumer Products & Retail

Most consumer products and retail (CPR) companies use AI today for well-defined, transactional tasks—demand forecasting, personalized recommendations, chatbots for customer service. But what if AI could completely redefine how products are designed, sold, and experienced?

1. AI as the Ultimate Product Designer

Rather than simply optimizing existing product lines, AI could help create entirely new ones. Imagine an AI system that understands emerging trends before they even become trends, analyzing billions of data points from social media, cultural shifts, and historical purchasing patterns. It could predict the next big flavor in snacks, the next must-have beauty product, or even an entirely new category of apparel that blends sustainability, tech, and fashion.

What if your next bestselling product wasn’t invented in a boardroom, but by an AI spotting an unfulfilled consumer desire?

2. AI as a Hyper-Personalized Shopping Companion

Retailers already use AI to suggest products, but what if AI anticipated needs before the customer even realized them?Imagine an AI that detects subtle changes in a consumer’s purchasing patterns and proactively curates a personalized shopping experience.

For example, a grocery store app powered by AI could notice that a customer has been buying more plant-based products and suggest a meal plan, complete with a dynamically generated shopping list and exclusive promotions. A fashion retailer’s AI could detect a shift in personal style and proactively send personalized outfit ideas, styled virtually on the consumer’s avatar.

This isn’t recommendation—this is anticipation and curation at an entirely new level.

3. AI as a Retail Store’s ‘Invisible Employee’

What if every store had an AI system that acted like an invisible yet hyper-aware sales associate? Instead of static digital kiosks or basic self-checkout, AI could adapt the physical store in real time based on foot traffic, sales data, and even micro-expressions from shoppers.

• Dynamic Shelf Arrangements – AI could analyze in-store behavior and instantly suggest changes to shelf layouts, optimizing for impulse purchases or helping customers find products faster.
• Emotion-Responsive Retail – AI-powered cameras could detect frustration in customers (e.g., struggling to find an item) and trigger proactive interventions, such as an automated chatbot offering instant directions or summoning a human associate.
• Automated Localized Promotions – Instead of generic discounts, AI could create hyper-personalized promotions in real time—offering a discount on an umbrella just as the weather shifts to rain, or adjusting pricing dynamically based on in-store behavior.

This would be a store that evolves minute by minute, based on real human behavior.

4. AI as the Sustainability Guardian

Sustainability isn’t just a buzzword—it’s a survival strategy for brands. AI could take sustainability efforts from incremental to radical by redesigning supply chains in real time.

• AI could analyze global logistics in real time, optimizing for the lowest carbon footprint rather than just the lowest cost.
• Instead of predicting demand based on sales history alone, AI could integrate climate data, geopolitical risks, and consumer sentiment shifts to create supply chains that are both resilient and ethical.
• AI could generate hyper-localized, zero-waste product lines by dynamically adjusting manufacturing based on real-time demand signals from a specific city or even a specific store.

In essence, AI could turn sustainability from a cost center into a competitive advantage.

A Call to Experiment: What If We’re Asking the Wrong Questions?

Many companies are still stuck testing AI like they’d test a smartphone’s call quality—focusing on whether it’s marginally better at the same old tasks. But AI isn’t just a tool to optimize existing workflows—it’s a force that enables entirely new ways of thinking, designing, and interacting with consumers.

The real question isn’t “How well does AI do what we already do?” It’s: “What could we do if we thought about AI completely differently?”

Consumer products and retail companies have an opportunity—not just to improve margins or optimize ads—but to redefine the very nature of commerce.

So, instead of asking how AI can make forecasting 5% better or reduce call center costs, ask:

• What if AI could design my next best-selling product from scratch?
• What if AI could create a shopping experience that feels like magic?
• What if AI could predict the next cultural shift before it happens?
• What if AI could make sustainability effortless and profitable at the same time?

The companies that dare to ask these questions—the ones willing to experiment, explore, and embrace the weird, uncharted possibilities—will be the ones that define the future.

So don’t just test AI. Play with it. Challenge it. Dream with it.

Because the biggest mistake isn’t overhyping AI. It’s underestimating what it could become.