Walmart, ChatGPT, and the Rise of Agentic Shopping: How AI Is Rewriting Retail ROI

Nidhi Raj
17 Oct 20254 mins read
AI/ML
GenAI
Languages, frameworks, tools, and trends

When Walmart announced it would let customers shop directly through ChatGPT using Instant Checkout, most saw it as another AI headline. In reality, it marked the beginning of a new consumer era—one where discovery, decision, and checkout collapse into a single conversational experience.

For decades, online shopping started with a search box. Now, people are beginning their shopping journeys inside AI assistants—and increasingly completing them there too.

“For many years, online shopping has been limited to a search bar and a long list of results. That’s about to change.”
Doug McMillon, CEO, Walmart Inc.

Discovery now happens inside AI

Recent Similarweb data indicates that 20% of Walmart’s referral traffic now originates from ChatGPT, representing a 15% increase from July. Etsy, Target, and eBay are seeing similar patterns. That means one in five Walmart customers is discovering products without ever visiting Walmart.com—AI assistants are becoming the new front door to retail.

This changes how brands must think about visibility and readiness. If AI-driven ecosystems are where consumers start, then product data has to be structured for AI consumption—clean, compliant, and machine-readable.

This is the world of AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization): the next frontier beyond SEO.

Two new imperatives for every retailer

  1. Optimize data for AI discovery.

If ChatGPT, Gemini, and other assistants are the new search platforms, your data must be ready for them. AI systems don’t “crawl” like traditional search engines—they reason. That means they need structured, contextual data: product attributes, availability, price, usage claims, and even compatibility tags.

Turing Intelligence helps enterprises clean, tag, and govern their product data so that AI models can interpret and recommend their catalog safely and accurately. We align your data schema with the way generative engines think—so your products remain findable and compliant as AI-driven discovery scales.

Goal: Make your proprietary data AI-visible, policy-compliant, and context-rich.

  1. Redefine on-site experiences around AI-native expectations.

Once users land on your site—because they already know your brand—they expect the same fluid, personalized experience they just had inside ChatGPT.

They expect to:

  • Ask questions in natural language.
  • Get context-aware recommendations.
  • Complete checkout conversationally.

Walmart’s integration has reset the bar for every retailer. And this is where Turing’s proprietary intelligence delivers unmatched value.

How Turing makes AI retail safe, personal, and measurable

Turing Intelligence helps enterprises bridge these two realities—optimizing for AI-driven discovery and delivering governed on-site experiences that mirror the natural, contextual flow consumers now expect.

Our proprietary intelligence framework unites governed data, decision architecture, and human oversight—the three pillars that make AI retail scalable, compliant, and profitable.

Governed data as your foundation

Every decision begins with clean, structured, and compliant data:

  • Customer 360s unify purchase history, identity, and consent.
  • Product graphs connect attributes, compatibilities, and claims.
  • Feature stores supply low-latency signals for personalization.
  • Policy layers encode pricing, promo, and compliance rules.

This architecture enables AI systems to act in real time without breaking trust, tone, or margin discipline.

Proprietary agentic experiences: Your next advantage

Once your data foundation is sound, we help you design your own conversational commerce experiences—mirroring the fluidity of ChatGPT, but governed by your brand’s rules.

Each agent skill operates safely inside an inspectable, measurable framework:

Compare

  • Evaluates ingredients, formats, and price per use
  • Sourced from verified product data

Bundle

  • Builds goal-based sets (sleep, endurance, skin health)
  • Respects pricing, region, and offer ceilings

Explain

  • Surface usage and ingredient guidance
  • Pulled from approved content

Apply loyalty

  • Calculates optimal discount or reward
  • Within compliance and margin thresholds

These aren’t chatbots—they’re governed decision engines designed for safety, scale, and measurable business impact.

The outcomes of governed intelligence

Across production deployments, Turing Intelligence consistently delivers quantifiable results:

  • 45% faster decision cycles through real-time automation.
  • 25–30% lower operational costs via data lineage and model reusability.
  • 30%+ lift in engagement and attach rates from predictive personalization.
  • 90–95% data accuracy across analytics and decision workflows.

The takeaway: Governance isn’t red tape—it’s what makes retail AI fast, compliant, and accountable. Our clients prove that discipline beats flash every time.

We don’t build chatbots. We build governed intelligence. Systems that act within your rules, grounded in your data, measured by your KPIs.

What this means for the future of retail

Walmart’s ChatGPT integration isn’t the endgame—it’s the starting signal. As multimodal AI systems evolve, users will expect the same conversational ease everywhere—from discovery inside assistants to checkout on brand sites.

To compete, enterprises must:

  • Structure data for AI visibility (GEO/AEO).
  • Build governed conversational experiences on-site.
  • Maintain explainability and human oversight across both layers.

Those that master this duality—AI-visible data + AI-native experiences—will own the next era of retail.

Talk to a Turing Strategist to:

  • Audit and optimize your product data for AI readiness (GEO/AEO).
  • Design your first governed, conversational shopping experience.
  • Deliver measurable ROI within 90 days.

Explore Turing Intelligence for Retail

Nidhi Raj

As Head of Solutioning at Turing, I lead the vision and delivery of cutting-edge AI solutions across retail/CPG, supply chain, and consumer-focused industries. A data scientist by passion and practice, I specialize in translating deep insights into transformative platforms—designing advanced analytics and recommendation systems built on top of multi-agent architectures to drive efficiency and efficacy. My work has enabled the organizations to seamlessly harness the power of artificial intelligence, from dynamic supply chain control towers to context-aware decision systems.

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