By Lizbeth Hoyos Pena, Customer Success Manager, Suzy

The picky shopper meets AI

I’m a very picky shopper – no joke.

When I went to buy sunglasses recently, I had a checklist that would make most salespeople sweat. The arms couldn’t be too broad or tight because they’d trigger a migraine! The lenses needed to be polarized to prevent glare and reduce eye strain. I also needed full coverage. And, of course, they had to fit into a very specific price range. You see what I mean – I don’t just shop, I audit.

That’s why I couldn’t help thinking: AI could probably do this better.

Then there was the time I lost a makeup product a friend had gifted me. I remembered it perfectly – a rectangular case with red packaging and gold lettering – but I had no idea what brand it was. I spent hours typing every possible description into Google with no luck. Out of curiosity, I described it to ChatGPT, and within minutes, it found the exact product.

That seamless accuracy made me realize something important: AI already understands the kind of shopper I am – and it’s setting a new standard for what consumers expect.

For consumers like me, AI makes shopping easier and faster. For brands, it’s redefining what it means to be seen. The retail experience is no longer reactive;

it’s predictive.

The retail AI revolution

Retailers are rewriting the rules of commerce with AI at the center of everything they do.

Walmart recently announced an AI-first shopping experience in partnership with OpenAI, letting customers plan meals, build grocery lists, and find products through natural conversation instead of keyword searches.

Target now adjusts promotions in real time using AI models that track inventory, local events, and even weather.

Sephora continues to dominate beauty tech through Color iQ and BeautyGPT – systems that recommend shades, routines, and products customized to each shopper’s tone and texture.

Even Amazon and Kroger are using predictive AI to anticipate when consumers will run out of staples and reorder automatically.

AI has moved from behind-the-scenes optimization to front-of-house experience. It’s influencing not only what people buy, but how they feel while buying it.

‍

How AI Is transforming every stage of retail

AI’s impact spans the entire shopper journey – from discovery to decision to delivery.

Discovery: Retail search is becoming conversational. Voice assistants and visual AI let consumers describe what they want (“a polarized pair of sunglasses under $150 with narrow arms”) instead of scrolling through filters. Algorithms learn each shopper’s language over time, shortening the path to purchase.

Decision: Machine-learning models now personalize recommendations down to micro-moments. In apparel, AI predicts fit using body-scan data; in grocery, it curates recipes based on dietary needs. Emotional AI is even reading facial cues to gauge delight or hesitation at in-store kiosks.

Delivery: Predictive logistics anticipate when consumers will reorder, while AI chatbots manage post-purchase service. Retailers like Best Buy use AI-driven support to troubleshoot tech issues before a human ever needs to step in.

For shoppers, it feels frictionless. For brands, it means every stage of the funnel has new data – and new pressure to keep up.

‍

The human side of AI shopping

For all its efficiency, AI retail is still about emotion – because shopping, at its core, is deeply human.

According to Accenture’s 2025 Consumer and AI Report, 64% of global shoppers say they “love” when AI helps them discover products that fit their preferences, but 53% have stopped using an app or site when personalization felt “too invasive.”

That tension – between convenience and creepiness – defines the future of retail.

AI has taught consumers to expect instant relevance. But empathy and trust still drive loyalty. Brands that use AI to listen, not just sell, will stand apart.

And even as AI gets more powerful, it can still miss the nuances that matter most. It might know I love polarized sunglasses, but it doesn’t yet know that I only buy them after trying five pairs to see how they feel. It can find my favorite red-and-gold makeup product, but it doesn’t know that I’m drawn to it because it reminds me of a gift from a friend. Those small human details – context, memory, emotion – are where true brand connection lives. That’s why insight remains the safety net beneath every great AI-powered experience.

Generationally:

• Gen Z embraces AI but demands ethics. They expect brands to use tech transparently and represent diverse voices (Deloitte, 2025). 
• Millennials crave convenience and time-saving experiences — but still expect authenticity in tone and storytelling.
• Gen X and Boomers are slower adopters but value reliability. They appreciate AI that simplifies, not overwhelms (Pew Research, 2024) .

As personalization becomes universal, trust becomes the differentiator.

‍

When Retailers Move Faster Than Brands

Retailers are innovating faster than most brands can follow. Bain & Company found that leading retail chains now run over 50 AI experiments per month – testing pricing, promotions, and digital touchpoints at unprecedented speed.

Brands, meanwhile, often operate in quarterly cycles – analyzing what did happen instead of what is happening.

Picture this: Walmart tweaks local beverage prices overnight after detecting a heatwave. The beverage brand supplying that product waits until next quarter’s business review to analyze sales data. By then, shopper behavior – and shelf space – has already shifted.

This creates a speed gap: retailers operate in real time; brands respond in retrospect.

And in an algorithmic retail environment, that delay can mean invisibility. AI recommendation systems decide which products are shown, which get discounted, and which disappear into the scroll abyss.

The good news? Retailers are increasingly inviting brands into the process – opening shared dashboards, data partnerships, and co-innovation hubs. The future of retail isn’t a competition; it’s a collaboration. Brands that share insights, test side-by-side with retailers, and align on experimentation cycles will close the gap faster than those waiting for quarterly reviews.

‍

The Global View

AI adoption looks different across continents.

• Asia: Alibaba and JD.com use generative AI to design pop-ups that restock automatically based on trending searches.
• Europe: Retailers such as Carrefour and Tesco prioritize responsible AI under GDPR, turning transparency into a marketing advantage.
• Latin America: In Brazil and Mexico, WhatsApp-based chatbots handle real-time sales, blending commerce with conversation.

For brands expanding globally, understanding these regional differences in AI acceptance – and designing insights accordingly – is essential.

‍

Brand Playbook: How to win the AI race

1. Feed the algorithm smart data
AI is only as intelligent as the data it ingests. Provide retailers with verified, insight-rich information – like validated product claims or emotional drivers. Become the data source that improves their models.

2. Move from research to real time
Platforms like Suzy let brands test packaging, creative, or claims overnight. What once took months now takes hours – matching the cadence of retailer experimentation.

3. Humanize personalization
Let consumers feel seen, not scanned. Pair quantitative precision with qualitative storytelling.

4. Collaborate, don’t compete
Retailers aren’t adversaries; they’re amplifiers. Share data, co-create activations, and align around mutual goals like sustainability or convenience.

5. Design for emotion
Efficiency drives purchase; emotion drives loyalty. Build moments of surprise or empathy into digital journeys.

‍

Brand case studies: AI in action

Unilever is testing generative AI to create localized ad copy across hundreds of SKUs, cutting production time by 40 %. But before deploying, the company uses real-time consumer feedback – collected through agile tools – to ensure tone and humor resonate in each market.

Coca-Cola’s “Create Real Magic” campaign used OpenAI to let fans design personalized artwork on packaging. It wasn’t about automation – it was about participation. The brand translated AI novelty into emotional engagement.

Nike leverages AI for co-creation through its By You platform. Shoppers design sneakers that reflect their style; AI predicts trending combinations and adjusts inventory accordingly. It’s personalization that feels collaborative, not prescriptive.

Across categories, the pattern is clear: AI enables creativity at scale, but insight ensures it connects.

‍

The human + AI equation

At its best, AI doesn’t replace human creativity – it enhances it. The real power lies in how brands merge machine speed with human understanding.

This balance is what separates the good from the great:

• AI can map a customer journey, but only insights can tell you where to connect.
• AI can write copy, but only human empathy can make it resonate.
• AI can optimize performance, but only real voices can make it personal.

Brands that lead in 2026 and beyond will be those that make AI an extension of empathy – not an efficiency tool.

‍

How Suzy powers brands in the AI era

This is where Suzy shines — helping brands stay human in an automated world.

Suzy Signals uncovers how consumers are responding to new AI-driven shopping behaviors – from chatbot fatigue to excitement about “predictive retail.”

Suzy Speaks allows brands to hear consumers in real time. Instead of just reading survey responses, teams can literally listen to how people talk about retail AI – their tone, emotion, and expectations.

Brands use Suzy to:

• Validate AI-driven personalization before it goes live.
• Test tone and creative for brand chatbots.
• Segment insights by generation, location, or culture to ensure personalization feels authentic everywhere.
• Close the loop between consumer sentiment and performance data.

By combining speed and empathy, Suzy gives brands an AI advantage rooted in human truth.

‍

What’s next for retail AI

2026 will mark the shift from AI-assisted to AI-expected retail.

• Voice commerce 2.0: Assistants evolve from reactive search to proactive planning (“You’re running low on sunscreen – same brand?”).
• Emotion AI: Cameras and microphones analyze tone and expression to personalize experiences in real time.
• AI-designed stores: Sensors and heat maps reconfigure layouts dynamically based on shopper flow.
• Sustainability optimization: Algorithms forecast demand precisely, reducing overproduction and waste.

For brands, these advances mean new ways to serve – not stalk – the consumer.

‍

Closing Thought: Technology Predicts, Insight Connects

As a picky shopper, I used to think only a patient salesperson could decode my quirks – the narrow sunglass arms, the need for polarized lenses, that one red-and-gold rectangular makeup product I refused to give up on. Now, AI can do it in seconds.

But speed alone doesn’t create satisfaction. What wins loyalty is when technology meets understanding – when a recommendation feels right because it fits me. AI may predict what I’ll want next. But the brands that win my trust are the ones that listen, learn, and deliver experiences that feel genuine.

That’s where Suzy plays a vital role – bridging the gap between automation and authenticity, speed and sensitivity, data and understanding. By giving brands access to real-time human insight, Suzy helps them make technology

Because in the end, AI may drive the transaction, but insight drives the connection. And in the new AI-powered retail landscape, connection is what makes brands unforgettable.

‍