For CTOs of SMEs: Prepare Your Site for AI Mode and Shopping Agents

Is your Google traffic declining and your SEO conversion not closing? AI Mode and shopping agents are taking over the purchase path. It’s time to prepare your service for 'actions', not just content. Below is a ready-to-use framework for an agent-ready web for SMEs.

AI Mode and Agents with Actions: What Changed After 2026

After Google I/O 2026, the direction is clear: Google has implemented AI Mode — an experience where users converse in full sentences, and the result is a summary with actionable options. Gemini 3.5 promotes the 'intelligence with action' approach. Amazon announces Alexa for Shopping, and Alibaba is designing chips for agents. An agent (an automated task executor) not only reads the page; it can also buy, reserve, and compare.

The prompt (command for the model) becomes the interface. If your service does not provide clear entry points for actions, the agent will choose a competitor that does. Traditional SEO and mere RAG are not enough: you need a layer of actions and AEO/GEO signals.

Conclusion: Without action-ready content and APIs, you become just a source for quotes, not a transaction destination.

Content Layer: schema.org to Feed Agents

Start with JSON-LD. Agents parse structured data and look for Actions related to an object (e.g., Product/Offer) through the target property, which indicates the EntryPoint (urlTemplate, httpMethod, contentType). Mark not only Product/Offer/FAQ/HowTo but also Actions with target=EntryPoint to suggest how to make a purchase or request a quote.

AEO (Answer Engine Optimization) provides clear answers. GEO (Generative Engine Optimization) refers to signals that facilitate generative engines in selecting your offer. Both focus on precise, machine-readable context.

Key elements below – treat them as an implementation checklist.

• Product: name, description (brief + features), image, brand, sku, gtin, material, size, aggregateRating.
• Offer: price, priceCurrency, availability (InStock/OutOfStock), url, validFrom, shippingDetails, hasMerchantReturnPolicy (MerchantReturnPolicy).
• FAQPage: 8–15 questions with complete answers to purchasing and implementation intents; link to offers/services.
• HowTo: steps for installation/return/configuration; helps agents plan post-purchase.
• ContactPoint: areaServed, openingHours, contactType=sales/support, telephone/email; for local results, add GeoCoordinates.
• Action (on Product/Offer) + target (EntryPoint):
• - QuoteAction → EntryPoint (httpMethod=POST, contentType=application/json, urlTemplate=/api/quote?sku={sku}&qty={qty}). Result: total, currency, tax, shipping, leadTimeDays, termsUrl, expiresAt; actionPlatform=DesktopWeb

Actions Layer: API Contracts for quote/availability/cart

Agents require low-latency, predictable operations. By 'low-latency', we mean: minimum steps and states (no cookies/redirects/JS), simple authorization (short-lived token in the header), and a clear format. 'Predictable' = consistent field schemas and types, deterministic errors, idempotency, and stable latency/SLA. Define narrow, idempotent endpoints and keep JSON simple and stable. Add OpenAPI and link to it in documentation and in schema.org/EntryPoint.

Treat security like in payments: limit the scope of actions, shorten tokens to minutes, and adjust limits per agent and per IP. Telemetry must allow you to track which queries result in actions and revenue.

• Endpoints:
• - /api/quote (POST) — input: sku, qty, postalCode, country; output: subtotal, shipping, tax, total, currency, leadTimeDays, expiresAt, quoteId.
• - /api/availability (GET/POST) — sku, qty, location → status: InStock/Backorder/Preorder, restockDate.
• - /api/cart (POST AddAction) — cartId, lineItems[].sku, qty → cartId, items[], subtotal, currency, expiresAt.
• LLM-friendly contract:
• - deterministic responses; fixed keys; no HTML; numbers as number, money as number + currency.
• - idempotency-key in the header for retries; locale and currency as explicit parameters; error messages short and machine-readable (code, message).

AEO/GEO Signals, Testing, and Telemetry

After implementing the tags and endpoints, check if agents can actually see and use them. Test in AI Mode and with agents from major providers, and funnel results into a data warehouse.

Telemetry and throttling are crucial for maintaining margins and stability. Monitor which intents result in actions and where agents get stuck; improve text, schema, or API contract accordingly.

• AEO/GEO signals: clear H1/H2, Q&A, short paragraphs, canonical links, hreflang, contact information, return policy, reviews; all in HTML (not images).
• Validation: Rich Results Test, schema.org validator, OpenAPI linter; manual 'prompting' in Gemini 3.5: 'Add SKU X to cart at store Y'.
• Telemetry: Agent Share of Traffic, Agent CTR (read→action), Action Success Rate, Quote→Order Rate, average leadTimeDays, revenue from agents.
• Throttling and security: token bucket per IP and per agent, 429 + Retry-After, geographical rules, anomaly blocking (Cloudflare Turnstile/Firewall).

30/60/90 Day Plan for CTOs of SMEs

You don’t need to rebuild everything at once. Below is a sequence that works for SMEs and mitigates risk.

• 0–30 days: audit intents and pages (top 20% of SKUs/services); implement JSON-LD for Product/Offer/FAQ/HowTo on at least 10 key pages; add ContactPoint and MerchantReturnPolicy; draft OpenAPI (spec for /quote, /available

Agents buy where they can perform actions frictionlessly. Ensure your schema.org includes Action/EntryPoint, secure endpoints, and telemetry. This is the fastest route to reclaim conversions from AI Mode. If you'd like, I can review your service and API, then outline priorities for 30/60/90 days — a brief consultation is all it takes to get started.