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The conversational queries powering agentic commerce are more expensive than traditional keyword searches. For this technology to be profitable for retailers, it must generate new sales that wouldn't have otherwise happened, rather than simply cannibalizing existing purchase channels.
The true value of AI in commerce isn't in automating the final click to buy, as checkout is largely a solved problem. The significant user need is leveraging AI for deep research on high-consideration purchases. Facilitating the transaction is less valuable than providing trustworthy, comprehensive information.
With AI enabling precise control over media spend, key performance indicators are changing. Brands now move beyond simple Return on Ad Spend (ROAS) to more sophisticated metrics like incremental ROAS and contribution margin, reflecting a new emphasis on profitable growth rather than just volume.
AI-driven search, or "agentic commerce," disproportionately benefits Shopify's smaller, independent merchants. Unlike traditional search, which favors brands with large ad budgets, AI agents match buyers with products based on specific intent and merit. This gives specialized, long-tail businesses a better chance to be discovered and compete against large retailers.
A key challenge for agentic AI products is their business model. Unlike chatbots that incur costs per request, agentic systems that run continuously in the background have non-zero marginal costs, making freemium or low-cost models difficult to sustain.
An AI founder reveals a single agentic action like clicking "add to cart" can cost 25 cents in API calls. This forces AI companies to build with a focus on profitability per user action from the start, a stark contrast to the "grow now, monetize later" model common in social media.
Agentic commerce isn't just a substitute for existing online shopping. It can unlock new spending from high-income individuals whose primary barrier to consumption is time, not money. By automating purchasing, agents reduce this "time cost of consumption," potentially adding new, incremental dollars to the economy.
As AI agents shift e-commerce from high-margin cost-per-click models to lower-margin commissions, search platforms will likely retaliate. They will make free, direct, and unpaid traffic more difficult to acquire, forcing a higher volume of transactions into their paid ecosystem to compensate for the lower per-transaction revenue.
Amazon has attached a specific, massive financial value to its AI assistant, Rufus. It's projected to generate over $10 billion in new sales annually by increasing conversion rates by 60%, proving the immediate and substantial ROI of embedding AI into the e-commerce customer journey.
The primary financial risk of agentic commerce to e-commerce companies is not the transaction fee but the potential loss of high-margin retail media advertising revenue. Since many retailers derive most or all of their profit from on-site ads, agents threaten their core business model.
The role of AI is evolving from passive analysis (e.g., predicting inventory) to active creation. 'Agentic' AI will build assets like brand books, websites, and apps from scratch, enabling unprecedented levels of operational efficiency and lean team structures.