AI is in the news every day, and local retail stores large and small may be sick of hearing it, and perhaps even dismissing it as just another fad.
We hope they don't but for those who are paying attention here is an overview and how they can start being more involved and not fall behind too much.
p.s. This also apply to brands.
WHY LOCAL RETAILERS AND BRANDS SHOULD PAY ATTENTION TO AI
Local retailers should pay attention to agentic AI in shopping because it represents a major shift in how consumers discover, evaluate, and purchase products. While many retailers are still adapting to e-commerce, agentic AI isn't just another channel—it’s a new way of shopping that bridges the digital and physical worlds. Here’s why they should care:
1. Consumers Are Shifting to AI-Driven Shopping
- Shoppers are moving from search-based discovery (Google, Amazon) to AI-assisted discovery, where AI agents proactively find products based on preferences, context, and real-time needs.
- As consumers become comfortable with AI-powered assistants, they’ll expect retailers to support these experiences.
2. AI Levels the Playing Field Against Big Retailers
- Local retailers often struggle to compete with large e-commerce platforms that have massive ad budgets.
- AI shopping agents can surface smaller retailers in consumer recommendations based on location, quality, and availability—helping them compete without spending heavily on ads.
- This is a chance for local retailers to leapfrog e-commerce complexity and get discovered without needing extensive digital marketing expertise.
3. AI Bridges Online & Offline Commerce
- Unlike traditional e-commerce, agentic AI can connect online searches to in-store visits by directing shoppers to local inventory.
- AI can help customers navigate stores or facilitate live video shopping, making the in-store experience more engaging.
- Local retailers can benefit from AI-driven foot traffic, where shoppers visit based on real-time recommendations.
4. AI Can Increase Sales & Customer Retention
- AI agents can personalize recommendations better than static websites, helping customers find the right product faster.
- AI-driven experiences reduce friction, making it easier for customers to purchase from local retailers instead of defaulting to Amazon.
- AI can act as a personal shopping assistant, remembering customer preferences and suggesting relevant products—leading to repeat sales and brand loyalty.
5. Preparing for AI Now Prevents Playing Catch-Up Later
- Just as social media and e-commerce reshaped retail, AI-driven shopping will become the new normal.
- Early adopters will have an edge, while late adopters may struggle to adapt once consumers expect AI-driven experiences.
- By preparing now, retailers can future-proof their business rather than scrambling to catch up when AI shopping becomes mainstream.
6. AI Agents Help Retailers with Operations Too
- AI can assist with demand forecasting, inventory management, and customer support, helping small retailers operate more efficiently.
- Local retailers often lack the manpower to answer every customer question—AI can handle inquiries about product availability, pricing, and store hours automatically.
7. Consumers Will Start Shopping Through AI-First Experiences
- Platforms like Visional are already enabling AI-driven shopping experiences, reducing the need for customers to browse traditional websites.
- Instead of expecting consumers to visit their site, retailers should focus on meeting customers where they are—inside AI shopping ecosystems.
See what Harvard Business Review says about the future of AI in shopping.
HOW LOCAL RETAILERS CAN GET READY TO USE AI, AND LEVEL THE PLAYING FIELD
A phased approach is the best path to prepare and start towards being AI-enabled next year.
Phased Approach to AI-Agent Optimization: Where to Start & How to Progress
Phase 1: Build AI Readiness (0-6 months)
✅ Goal: Ensure that your product data, customer insights, and digital presence are structured in a way that AI agents can process and use effectively.
🔹 What to Do First:
- Optimize product data for AI discovery (structured metadata, enriched descriptions, real-time inventory feeds).
- Ensure compatibility with AI-powered search and marketplaces (e.g., Google Shopping, Amazon AI, social commerce platforms).
- Improve review collection and sentiment analysis to strengthen AI-driven recommendations.
- Invest in conversational AI basics (chatbots, voice search optimization, interactive Q&A on product pages).
🔹 Why It Matters:
This foundational work ensures your products are surfaced correctly when AI agents start to gain traction. Brands that lack structured, AI-readable product data may struggle to get visibility when AI shopping becomes mainstream.
Phase 2: Test & Learn in AI Shopping Ecosystems (6-18 months)
✅ Goal: Experiment with AI-driven channels and interactions while measuring impact.
🔹 What to Do Next:
- Run AI-driven ad and product recommendation experiments (Google’s AI-powered shopping campaigns, TikTok Shop AI-driven recommendations, Amazon’s AI search results).
- Leverage AI-powered customer engagement tools (AI-assisted chat for shopping, voice commerce via Alexa/Siri/Google).
- Pilot AI-driven personalization strategies (adaptive pricing, dynamic product recommendations).
- Integrate with early AI shopping platforms that are showing traction (e.g., Klarna’s AI shopping assistant, ChatGPT-based retail integrations).
🔹 Why It Matters:
This phase helps brands identify the highest ROI areas before committing full-scale resources. By running AI-powered discovery and shopping tests, brands can gauge which strategies align best with their audience.
Phase 3: Scale AI-Driven Customer Acquisition & Shopping (18+ months)
✅ Goal: Move from experimentation to AI-first strategies in customer acquisition and commerce.
🔹 What to Do Next:
- Develop AI-powered conversational commerce experiences (in-app AI shopping assistants, live video shopping with AI enhancements).
- Enhance AI personalization with first-party data (brand-owned AI assistants trained on proprietary customer insights).
- Establish direct relationships with AI agents (work with marketplaces, social commerce, and agent-driven ecosystems to ensure strong visibility).
- Explore hybrid AI + human shopping models (AI-powered recommendations with human-guided validation via live video or concierge experiences).
🔹 Why It Matters:
By this stage, agentic shopping will likely be more mainstream. Brands that have already optimized their presence in AI-driven environments will be in a strong position, while those just starting will struggle to catch up.
HOW TO AVOID FALLING BEHIND WHILE PHASING IN AI STRATEGY
- Start with data and AI compatibility today – AI shopping agents will only recommend products that they can easily understand, categorize, and process. Brands that delay optimizing product data and discovery mechanisms will struggle later.
- Test AI-driven channels before going all in – Not all AI shopping platforms will succeed. Early testing helps brands identify which AI ecosystems are worth long-term investment.
- Monitor consumer adoption and adjust – AI shopping will evolve at different speeds across categories. Regularly track how AI discovery is impacting consumer behavior in your industry.
- Partner with AI-powered commerce leaders – Aligning with Google, Amazon, Klarna, TikTok, and emerging AI shopping assistants ensures your products are visible in AI-driven discovery platforms as they grow.
Be Early, But Be Smart
Brands and retailers that take a phased approach—starting with AI-readiness, experimenting with AI-powered discovery, and gradually scaling AI-driven commerce—will stay ahead of the curve without overcommitting resources too soon.