AI in Customer Experience: Why Retail is Splitting Between High-Tech and Human Touch
- Sophia Lee Insights
- Feb 26, 2025
- 5 min read
Updated: 1 day ago
This article is part of our “AI in Customer Experience” series. It explores how AI is reshaping retail in two directions, and why the future of customer experience depends on finding the right balance between intelligent automation and meaningful human connection.
AI is Reshaping Shopping—But Not for Everyone
Big retailers like Amazon, Walmart, and Alibaba are doubling down on AI-driven automation.
Recently, reports from Forbes and Supply Chain Brain highlighted how Agentic AI is taking over retail—predicting demand, adjusting prices in real-time, and even deciding what customers will buy before they know it themselves.
Companies are investing billions to make shopping faster, smarter, and more efficient. But while big brands thrive in this AI-powered future, small businesses are falling behind.
This gap in AI investment is already showing up in the shopping experience. Customers are responding differently to AI-driven shopping depending on context, convenience, and expectations around human interaction.
So, is AI in customer experience making shopping better for everyone? Or is it widening the gap between retail giants and small businesses?
A New Era of AI in Customer Experience
For over a decade, companies like Netflix, Amazon, and Spotify have used machine learning and recommendation algorithms to personalize content.
But Agentic AI executes decisions based on real-time analysis, reducing the need for human intervention.
Here’s how it changes shopping:
✅ AI-generated shopping lists – Instead of users manually searching for products, AI predicts what they need and suggests a ready-made list.
✅ Dynamic pricing – AI automatically adjusts discounts based on a shopper’s habits, location, and even the time of day.
✅ Real-time inventory optimization – AI ensures that the right products are always available, reducing out-of-stock frustrations.
This level of AI in customer experience is revolutionizing the way people shop, but not everyone benefits equally.
🏢 The AI-Powered, High-Tech Retail Model
Large retailers like Walmart, Target, and Alibaba are investing heavily in AI-driven automation to stay ahead.
Here’s how they use Agentic AI to dominate the market:
Automated inventory management – AI predicts demand and automatically reorders stock, reducing waste and increasing efficiency.
AI-driven customer service – Virtual assistants handle inquiries, reducing the need for human employees.
Automated checkout – No cashiers, no waiting. AI-powered stores like Amazon Go allow shoppers to walk in, grab items, and leave.
🚨 The Challenge? AI is Creating a Wider Competitive Gap
The catch? Large enterprises with greater financial and technological resources can integrate Agentic AI more seamlessly.
Implementing these systems requires:
💰 Significant investment – AI infrastructure, data processing, and real-time machine learning models.
📊 Extensive customer data – Smaller retailers often lack the volume of data needed to train AI effectively.
⚙️ System compatibility – Many small businesses rely on basic POS systems and struggle with the cost and complexity of upgrading to AI-powered solutions.
As a result, larger companies continue to optimize and scale more efficiently, while smaller businesses face greater barriers to AI adoption, potentially widening the competitive gap in the retail industry.
This dynamic is not about tools alone, but about how adoption decisions are structured and sequenced, a perspective explored further in Driving Clarity in Adoption: Structure, Judgment, and Timing.
🏡 Where Human-Driven Retail Still Competes
AI-driven shopping may be fast and efficient, but many shoppers still prefer human interaction.
🛍️Different Shopping Preferences
1️⃣ Tech-Driven Consumers – Love automation, fast checkout, and AI-driven recommendations. They enjoy seamless online-to-offline shopping experiences.
2️⃣ Human-Centric Consumers – Prefer local businesses, personalized service, and a sense of community. They value conversations with store owners and curated shopping experiences.
As a result, retail models are diverging under very different cost and operating constraints:
✅ High-tech, AI-driven stores – Fully automated, designed for speed and convenience.
✅ “Back-to-basics” traditional retail – Community-driven stores focusing on craftsmanship, unique products, and human interaction.
This does not mean small businesses are without options—they are competing under different constraints.
This distinction is more about how value is framed and judged in AI adoption, a line of thinking explored further in Framing AI for Value: Why Strategic Discernment Matters More Than Visibility in AI Adoption.
🔍 How Small Retailers Can Compete in the AI Age
Instead of trying to match big retailers’ AI capabilities, small businesses should focus on what AI can’t do: building deep, personal relationships with customers.
Here’s how they can leverage AI without losing their human touch:
✅ Use AI as a support tool, not a replacement – AI can help with inventory tracking and simple automation, but human connection remains key.
✅ Offer experiences, not just products – Workshops, in-store events, and personalized recommendations make shopping memorable.
✅ Highlight uniqueness – Small brands should lean into their individuality. Mass-market AI recommendations lack personality—boutique shops can stand out with carefully curated selections.
✅ Focus on storytelling – AI-driven commerce is transactional. Small businesses should build emotional connections through branding and community engagement.
By blending AI-powered efficiency with human-centered experiences, small retailers can stay relevant without becoming obsolete.
Ultimately, competing in the AI age is not about doing more with technology, but about making clearer investment choices, a consideration discussed in Why Return on Investment Should Lead Every AI Decision.
🎯 The Future of AI in Customer Experience
The rise of Agentic AI in customer experience is reshaping retail in different ways:
1️⃣ Hyper-modern, AI-powered shopping – Fast, seamless, data-driven.
2️⃣ Traditional, community-focused retail – Deliberate, personal, experience-driven.
For businesses, the key is understanding where they fit in this new landscape.
How they balance AI adoption and human interaction will shape where they compete.
Either way, the future of shopping won’t be one-size-fits-all.
References
Finley, M. Price Smart, Act Fast: Agentic AI’s Role in Retail’s Next Chapter. Supply Chain Brain, November 2024.
Marr, B. Forget ChatGPT: Why Agentic AI Is the Next Big Retail Disruption. Forbes, February 2025.
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