73% of shoppers are already using AI in their shopping journey (Riskified, 2025). AI agents are browsing, comparing, and buying products on behalf of consumers. Shopify launched Agentic Storefronts. Google rolled out the Universal Commerce Protocol. ChatGPT added instant checkout. The shift is real, and it’s accelerating.
But here’s what the hype cycle isn’t telling you: 50% of consumers are cautious about letting AI agents autonomously handle purchases from start to finish (Bain & Company, 2025). And merchants should be cautious too.
Agentic commerce introduces risks that traditional ecommerce never had to deal with: AI agents that hallucinate product details, fraud networks targeting autonomous purchasing, customer relationships being intermediated by third-party AI, and regulatory frameworks that haven’t caught up to the technology.
This guide covers the 8 biggest risks Shopify merchants face in the agentic commerce era and provides specific mitigation strategies for each. The goal isn’t to scare you away from AI commerce. It’s to help you participate with your eyes open.
For a full overview of what agentic commerce is and how it works, start with our comprehensive guide before diving into the risks.
The State of AI Shopping in 2026
Before diving into risks, here’s where we are. AI-powered shopping isn’t theoretical anymore. It’s generating real transactions.
| Metric | Data Point | Source |
|---|---|---|
| Shoppers using AI in shopping | 73% | Riskified (2025) |
| Consumers cautious about autonomous purchases | 50% | Bain & Company (2025) |
| Consumers who trust retailer AI 3x more than third-party AI | 3x trust gap | Bain & Company (2025) |
| Consumers who’ve completed an AI-referred purchase | Only 13% | Riskified (2025) |
| AI referral traffic for some retailers | Up to 25% | Bain / Similarweb (2025) |
| Consumers trusting AI to influence purchases | 36% | Riskified (2025) |
The picture is mixed. Consumers are experimenting with AI shopping, but trust is low and conversion from AI referrals is still in early stages. For merchants, this means the risks below are real but manageable if you act now.
Risk 1: Data Privacy and Security
The risk: AI shopping agents need access to extensive customer and product data to function. Your inventory, pricing, product details, and potentially customer preferences flow through multiple systems: your Shopify store, the AI platform (OpenAI, Google, Perplexity), and third-party integrations. Each handoff creates a new attack surface.
AI-related privacy incidents surged 56% in the past year (Stanford AI Index, 2025). Only 47% of people globally trust AI companies to protect their personal data (IAPP, 2025). And 75% of consumers will not purchase from companies they don’t trust with their data (Thunderbit, 2025).
What this means for your Shopify store: When you connect to AI agent platforms via Agentic Storefronts or UCP, you share product data, inventory levels, and pricing. Without clear data governance, this information could be used to train AI models, shared with competitors, or exposed in breaches. The average cost of a US data breach reached $10.22 million in 2025 (IBM, 2025).
How to protect yourself:
- Audit exactly what data you share with each AI platform
- Implement data minimization: share only what’s necessary for the transaction
- Create clear data processing agreements with AI providers
- Monitor for unauthorized use of your product data
- Separate customer PII from product/transaction data in AI integrations
For a detailed look at what data AI agents need from your store and how to manage it safely, our data readiness guide covers the full picture.
Risk 2: AI Hallucinations in Product Recommendations
The risk: AI agents may confidently recommend your products with incorrect specifications, wrong pricing, fabricated features, or inaccurate availability. The customer buys based on the AI’s promise. The product arrives different from what was described. You get the return, the chargeback, and the negative review.
Top AI models now hallucinate less than 1% of the time for simple queries, but that rate jumps to over 15% when analyzing complex statements (Vectara Leaderboard, 2025). Product descriptions with multiple specifications, compatibility requirements, and variant options are exactly the kind of complex content where hallucinations spike.
71% of consumers abandon a brand after one bad AI interaction (Industry Research, 2025). If ChatGPT tells a customer your product has features it doesn’t have, the customer blames your store, not ChatGPT.
The RAG solution: Retrieval-Augmented Generation can cut hallucinations by 71% when used properly (Industry Research, 2025). This means providing AI agents with structured, accurate product data (JSON-LD, detailed product feeds) so they generate recommendations from your actual catalog instead of guessing.
How to protect yourself:
- Ensure your product data is structured, complete, and machine-readable
- Use JSON-LD schema markup on all product pages
- Keep product feeds accurate and synced in real-time
- Regularly test how AI agents describe your products (ask ChatGPT, Perplexity about your products)
- Set up alerts for customer complaints about product descriptions not matching
Risk 3: Fraud and Manipulation
The risk: Fraudsters are adapting fast. Visa detected a 450% increase in dark web posts mentioning “AI Agent” over just six months (Visa, 2025). Malicious bot-initiated transactions increased 25% (40% in the US) in the same period. AI-powered bot traffic surged 300% over the past year (Akamai, 2025).
The fraud threat in agentic commerce is different from traditional ecommerce fraud:
- Counterfeit merchants are engineered to exploit AI agents, tricking them into sending customers to fake stores
- Stolen or manipulated agents can make unauthorized purchases at scale using harvested credentials
- Malware can distort user preferences, resulting in transactions that follow the rules but don’t reflect user intent
- 78% of financial institutions expect fraud will increase significantly due to agentic commerce (Accenture, 2025)
Consumers lost $12.5 billion to fraud in the past year, and nearly 60% of companies reported increased losses from 2024-2025 (Experian / Fortune, 2026).
How to protect yourself:
- Update fraud detection systems to distinguish legitimate AI agents from bots
- Implement agent identity verification (look for Visa TAP, UCP authentication features)
- Create separate risk profiles for AI-initiated vs human-initiated transactions
- Monitor for AI agent credential theft and impersonation
- Track chargeback rates on AI-referred orders separately from direct orders
Risk 4: Losing Your Customer Relationship
The risk: When AI agents intermediate purchases, merchants lose direct contact with customers. The customer never visits your website, reads your content, or joins your email list. You become an invisible supplier competing on price and fulfillment speed.
81% of retail executives predict generative AI will weaken brand loyalty by 2027 (BCG, 2025). This isn’t speculation from outsiders. It’s the industry’s own leadership acknowledging the risk.
When an AI agent handles the purchase:
- You lose session data, behavioral signals, and browsing patterns
- Cross-sell and upsell opportunities disappear (the agent buys exactly what was asked for)
- Email list growth stalls (the customer never sees your opt-in)
- Loyalty program enrollment drops (the agent doesn’t sign up for rewards)
- Return customer rates decline (the agent may choose a different store next time)
Consumers trust retailers’ on-site AI agents 3x more than third-party agents (Bain & Company, 2025). This is actually good news for merchants: building your own AI experience gives you a competitive advantage over third-party agent platforms.
How to protect yourself:
- Build direct customer relationships through channels agents can’t intermediate (communities, subscription boxes, exclusive memberships)
- Create unique value propositions that agents can’t easily commoditize
- Maintain parallel direct-to-consumer channels alongside AI agent channels
- Invest in your own on-site AI experience (higher trust than third-party)
- Track what percentage of revenue comes from AI-referred vs direct traffic
Risk 5: Platform Dependency
The risk: Merchants are becoming dependent on AI platforms (ChatGPT, Google, Perplexity) for customer access, repeating the pattern of past dependency on Google SEO and social media algorithms.
AI now accounts for up to 25% of referral traffic for some retailers (Bain / Similarweb, 2025). Multiple competing protocols exist: UCP (Shopify/Google), MCP (Anthropic), A2A (Google), ACP. There’s no guarantee which will dominate.
The dependency pattern:
- New platform emerges with massive reach
- Merchants optimize for that platform to capture traffic
- Platform changes algorithm or pricing model
- Merchants lose traffic overnight
- Merchants scramble to adapt or diversify
We’ve seen this with Google SEO, Facebook organic reach, and Instagram shopping. Agentic commerce is following the same trajectory, but faster and with higher stakes because AI agents can redirect purchasing decisions instantaneously.
How to protect yourself:
- Don’t put all your eggs in one AI platform basket
- Maintain strong direct traffic channels (email, SMS, organic search)
- Make your store data machine-readable across all protocols (UCP, MCP, A2A)
- Monitor which AI platforms drive your traffic and diversify
- Build brand recognition that transcends any single platform
Risk 6: Price Manipulation
The risk: AI-powered pricing algorithms can autonomously engage in price discrimination, collusion, and manipulation. On the merchant side, your repricing tools might undercut you into unprofitability. On the consumer side, AI agents shopping for customers might exploit pricing inconsistencies.
AI pricing algorithms can autonomously sustain collusive pricing without explicit agreement or communication between competitors (NBER, 2025). Instacart’s AI pricing tools charged different users different prices, with the same basket varying by approximately 7% (CNBC, 2025).
Consumer-side AI agents could counter merchant-side AI pricing, creating an “arms race” of algorithms where neither side benefits but both sides invest heavily.
How to protect yourself:
- Set absolute price floors and ceilings in any AI pricing tool
- Monitor for algorithmic pricing patterns that could trigger antitrust scrutiny
- Avoid personalized pricing based on individual customer data
- Track competitor pricing trends for signs of algorithmic collusion
- Stay informed on new pricing regulations (NY, CA, federal)
Risk 7: Legal and Regulatory Uncertainty
The risk: Existing consumer protection, contract, and data privacy laws were designed for human decision-makers, not AI agents. When an AI agent makes an erroneous purchase, halluccinates product features, or fails to communicate terms, the liability allocation is unclear.
Key regulatory developments:
- FTC “Operation AI Comply” targets deceptive AI claims with multimillion-dollar penalties
- EU AI Act (phasing in through 2026) lacks specific provisions for autonomous purchasing agents
- Multiple US states are enacting AI governance statutes with enforcement beginning 2025-2026
- No clear framework exists for allocating liability between consumers, merchants, and AI providers
Contract formation uncertainty is a real issue: if an AI agent accepts terms on behalf of a consumer, is that legally binding? If the agent was manipulated or hallucinated the terms, who is liable?
85% of financial institutions believe their current systems are insufficient to handle high-volume autonomous agent transactions (Accenture, 2025). If the financial infrastructure isn’t ready, merchants will bear the friction costs.
How to protect yourself:
- Review and update terms of service for AI-initiated transactions
- Clarify return/refund policies for AI agent purchases specifically
- Consult legal counsel on AI-specific liability provisions
- Consider cyber insurance covering AI-related fraud and data breaches
- Document AI agent authorization requirements (for chargeback defense)
- Monitor evolving regulations: FTC, EU AI Act, state-level AI laws
Risk 8: Brand Control Erosion
The risk: AI agents strip away the brand experience. Your carefully crafted Shopify store with its photography, storytelling, and curated experience becomes irrelevant when an AI agent summarizes your product as a line item in a comparison table.
When agents handle discovery and purchase:
- Merchants lose control over how products are presented, described, and compared
- Brand storytelling disappears (agents don’t read your “About Us” page)
- Product photography becomes less relevant (agents parse data, not visuals)
- Customer experience differentiation collapses to price and fulfillment speed
- Agents may split multi-item purchases across retailers for best individual prices
87% of financial institutions believe trust will be the most significant barrier to agentic payments adoption (Accenture, 2025). For merchants, the trust challenge is twofold: consumers need to trust AI agents to buy on their behalf, and merchants need to trust that agents represent their products accurately.
How to protect yourself:
- Invest in machine-readable brand signals (structured data, verified reviews, product schema)
- Ensure product descriptions are comprehensive enough that AI represents your products accurately
- Implement UCP/protocol compliance to control how your brand appears in agent interfaces
- Create experiences that agents can’t replicate (in-store events, unboxing experiences, community)
- Build brand recognition strong enough that consumers specifically request your products through agents
How to Protect Your Store: A Mitigation Framework
The risks above are real, but they’re manageable. Here’s a prioritized framework based on immediate impact and implementation difficulty.
Tier 1: Do This Now (Low Effort, High Impact)
Structured product data. Make sure your product titles, descriptions, pricing, and availability are accurate, complete, and machine-readable. Add JSON-LD schema markup. This single step reduces hallucination risk, improves AI agent accuracy, and positions you for every AI platform simultaneously.
Audit your data sharing. Review what data you’re sharing with AI platforms. Remove anything unnecessary. Implement data minimization as a default policy.
Monitor AI representations. Regularly search for your products on ChatGPT, Perplexity, and Google AI Mode. Check if the AI describes them accurately. Flag errors.
Tier 2: Do This Quarter (Medium Effort, High Impact)
Separate AI analytics. Track AI-referred traffic, conversion rates, and chargeback rates separately from direct traffic. This gives you visibility into the actual performance and risk profile of agentic commerce for your store.
Update legal frameworks. Review terms of service, return policies, and privacy policies for AI-initiated transactions. Add explicit language about AI agent purchases.
Implement human-in-the-loop oversight. Set transaction limits requiring human approval for high-value AI agent orders. Create override capabilities and escalation paths.
Tier 3: Do This Year (Higher Effort, Strategic Impact)
Diversify channels. Don’t let AI referral traffic exceed 30-40% of total revenue. Maintain strong direct channels: email, SMS, organic search, paid search.
Build agent-resistant brand value. Create customer experiences that AI agents can’t replicate: communities, loyalty programs with experiential rewards, personalized post-purchase follow-ups.
Fraud infrastructure upgrade. Update fraud detection to distinguish legitimate AI agents from malicious bots. Implement agent identity verification as it becomes available through Visa TAP and UCP authentication.
Legal preparation. Establish cyber insurance covering AI-related incidents. Build compliance documentation for evolving regulations. Create a response plan for AI-related fraud or data incidents.
Frequently Asked Questions
What is the biggest risk of agentic commerce for Shopify merchants?
Loss of customer relationships. When AI agents handle discovery through purchase, merchants lose direct contact, email signups, behavioral data, and cross-sell opportunities. This threatens long-term customer lifetime value more than any single fraud incident.
How do I protect my store from AI agent fraud?
Separate AI-initiated transactions from human ones in your analytics. Monitor chargeback rates on AI-referred orders. Update fraud detection to distinguish legitimate agents from bots. Implement agent identity verification as platforms make it available.
Will agentic commerce make my brand irrelevant?
Not if you prepare. Build machine-readable brand signals (structured data, verified reviews). Create experiences agents can’t replicate (communities, unboxing, in-store). Ensure your product data is accurate enough that agents represent you correctly.
Should I block AI agents from my Shopify store?
No. Blocking agents means losing access to a growing shopping channel. Instead, control what data agents can access, ensure accuracy of that data, and monitor how agents represent your products. Participate on your terms.
How do AI hallucinations affect my store?
When an AI agent misrepresents your product (wrong features, wrong price, wrong availability), the customer blames you. You face returns, chargebacks, and negative reviews for problems the AI caused. RAG with structured product data reduces hallucinations by 71%.
What regulations apply to agentic commerce?
FTC Operation AI Comply targets deceptive AI practices. The EU AI Act phases in through 2026. Multiple US states are enacting AI governance laws. No comprehensive agentic commerce regulation exists yet, but the legal landscape is evolving fast.
Is my customer data safe with AI platforms?
AI-related privacy incidents surged 56% last year. Only 47% of people trust AI companies with personal data. Share only what’s necessary for transactions. Create data processing agreements. Separate customer PII from product data in AI integrations.
How much of my traffic should come from AI agents?
Keep AI referral traffic below 30-40% of total revenue to avoid dangerous platform dependency. Maintain strong direct channels (email, organic, paid). Diversify across multiple AI platforms rather than relying on one.
What’s the chargeback risk with AI agent purchases?
Friendly fraud chargebacks already comprise 75% of all disputes. AI agent purchases add authorization ambiguity (did the consumer actually approve this purchase?). Document AI agent authorization flows and keep records for chargeback defense.
How do I get started with agentic commerce safely?
Start with accurate product data (structured, machine-readable). Monitor how AI agents describe your products. Track AI-referred traffic separately. Update legal terms for AI purchases. Then gradually enable deeper AI integrations while monitoring performance and risk metrics at each stage.
About Akash Radadiya
