Disclaimer: This content represents analysis and opinion based on publicly available information as of early 2025. It does not constitute legal, financial, or investment advice. Market conditions, company strategies, and technology capabilities evolve rapidly. Readers should independently verify all claims and consult appropriate professionals before making business decisions.
The Current Transaction Gap
AI platforms have captured significant influence over product discovery and recommendation while the actual purchase transaction occurs elsewhere. Users ask ChatGPT what laptop to buy, receive recommendations, and then navigate to Amazon, Best Buy, or manufacturer sites to complete the purchase. AI owns the discovery moment but loses the user at the critical conversion point.
This gap represents both a limitation and an opportunity. The limitation is clear: AI platforms cannot monetize the transactions they influence. The opportunity is equally clear: if AI platforms can capture transactions, they access enormous value currently flowing to retailers.
According to 2025 data, ChatGPT processes over 1 billion queries daily. A recent analysis shows that shopping-related conversations within AI interfaces grew from approximately 7.8% to 9.8% of total prompts between January and June 2025. This means roughly 100 million daily shopping-related queries occur on ChatGPT alone. Even modest transaction capture rates would generate substantial revenue.
Why Transactions Remain on Retailer Sites
Several structural factors currently keep transactions on retailer sites rather than AI platforms.
Payment infrastructure exists on retailer sites. Retailers have established payment processing, fraud prevention, and checkout optimization over decades. Building equivalent infrastructure requires substantial investment and regulatory compliance.
Inventory and fulfillment connect to retailer systems. Retailers know what products are in stock, what can ship quickly, and how to handle returns. AI platforms lack this operational infrastructure.
Trust for transactions differs from trust for information. Users may trust AI for recommendations while preferring to complete purchases through familiar retailers with established customer service and return policies.
Existing user accounts create friction for platform switching. Users with saved payment methods, shipping addresses, and purchase histories on retailer sites face switching costs when asked to transact elsewhere.
Retailer relationships with manufacturers provide access to inventory and pricing that independent platforms lack.
The Transaction Capture Playbook
Despite these barriers, AI platforms have clear paths toward transaction capture. Several strategies are already emerging.
Strategy 1: Affiliate Relationships
The simplest approach maintains the current model while monetizing the referral. AI platforms generate purchase recommendations and include affiliate links that provide commission when users complete transactions on retailer sites. This captures value without capturing the transaction itself.
ChatGPT already sends substantial referral traffic to retailers. The platform could monetize this traffic more aggressively through affiliate partnerships. However, affiliate commissions are modest compared to owning the transaction.
Strategy 2: Checkout Integration
AI platforms can integrate checkout capability within the AI interface while leaving fulfillment to retailers. This captures the transaction while outsourcing logistics.
OpenAI has already moved in this direction. ChatGPT’s instant checkout feature with Walmart allows users to purchase products directly through chat. The user experience remains within ChatGPT while the fulfillment happens through Walmart. This model captures transaction data and potentially payment processing fees while leaving inventory and shipping to established retailers.
The announcement that Walmart is working with OpenAI to allow shoppers and Sam’s Club members to purchase directly through ChatGPT signals that major retailers see value in meeting users where they are rather than requiring them to navigate to retailer sites.
Strategy 3: Marketplace Development
AI platforms could develop marketplace infrastructure where multiple merchants list products and compete for AI recommendations. This mirrors the Amazon marketplace model but with AI-first discovery rather than search-first discovery.
This approach requires building merchant onboarding, product listing systems, payment processing, dispute resolution, and other marketplace infrastructure. The investment is substantial but the potential returns are proportionate.
Perplexity has moved toward this model with experimental shopping features that present products from multiple merchants within the AI interface.
Strategy 4: Private Label Products
AI platforms could recommend their own products, particularly digital goods where fulfillment is trivial. A subscription service, digital content product, or software tool recommended by AI when users express relevant needs would represent direct commerce rather than referral commerce.
This approach faces brand extension risk. Users may not trust AI platforms to provide unbiased recommendations if those platforms also sell products. The conflict of interest is obvious and could undermine the trust that makes AI recommendations valuable.
Strategy 5: Agent-Based Purchasing
Emerging AI agent capabilities could automate the entire purchase process. Users might authorize AI agents to complete transactions on their behalf, navigating retailer sites, applying credentials, and finalizing purchases without requiring user attention.
According to 2025 data, 24% of consumers are already comfortable with AI agents shopping for them, increasing to 32% among Gen Z consumers. This comfort level suggests meaningful demand for agent-based purchasing.
Agent-based purchasing could capture transaction influence even when the literal transaction occurs on retailer sites. If the AI agent controls the purchasing decision and process, the retailer becomes fulfillment infrastructure rather than the customer relationship owner.
Timeline Estimates
Different transaction capture strategies operate on different timelines.
Affiliate monetization is already happening and will intensify in 2025-2026 as AI platforms formalize retailer relationships and optimize referral flows.
Checkout integration is emerging now. The Walmart-ChatGPT partnership represents early implementation. Expect rapid expansion to additional retailers through 2025-2026 as the model proves viable.
Marketplace development requires more substantial infrastructure investment. Early experiments are underway, but full marketplace capability likely emerges in 2026-2028 timeframe.
Agent-based purchasing depends on AI agent capability maturation and user trust development. Meaningful volume likely emerges in 2027-2030 as agents become more reliable and user comfort increases.
Retailer Responses
Retailers face strategic decisions about how to respond to AI platform transaction ambitions.
Cooperation through checkout integration preserves retailer fulfillment role while ceding discovery and transaction interface to AI platforms. Retailers maintain operational business while losing customer relationship ownership. This may be preferable to losing customers entirely but represents meaningful value erosion.
Competition through AI capability development allows retailers to keep transactions on their platforms by building comparable AI discovery experiences. Amazon, Walmart, and other major retailers are investing in AI features for their own platforms. This approach preserves transaction ownership but requires sustained AI investment.
Differentiation through unique value creates reasons for users to prefer retailer transactions over AI transactions. Exclusive products, loyalty programs, bundled services, and superior customer service could motivate users to complete transactions on retailer sites even when AI platforms offer convenient alternatives.
Regulatory advocacy could attempt to limit AI platform commerce expansion through competition policy, consumer protection regulations, or other mechanisms. Retailers with lobbying resources may pursue this path alongside commercial responses.
What Changes When AI Captures Transactions
If AI platforms successfully capture significant transaction volume, several market dynamics shift.
Retailer leverage declines. Currently, retailers control customer relationships and can negotiate with suppliers, platforms, and service providers from positions of strength. If AI platforms own customer relationships, retailers become commoditized fulfillment providers with reduced negotiating power.
Product discovery dynamics change. AI recommendations become the primary path to purchase consideration rather than search results, category browsing, or advertising. Brands must optimize for AI visibility rather than traditional digital marketing.
Data concentration increases. AI platforms that capture transactions gain rich purchase behavior data that improves their recommendations and expands their competitive moat. This data advantage compounds over time.
Advertising economics shift. Current digital advertising targets users during purchase consideration phases. If AI handles consideration internally, advertising targeting points change. Pre-AI awareness advertising and post-purchase relationship advertising may become more important relative to consideration-phase advertising.
The Most Likely Outcome
Complete AI capture of transactions seems unlikely in the medium term. The infrastructure advantages that retailers possess are substantial. User trust for transactions takes time to build. Regulatory attention to AI platform expansion may create constraints.
However, significant partial capture seems highly probable. AI platforms will capture transaction influence through checkout integration partnerships, agent-based purchasing assistance, and superior discovery experiences. The value split between AI platforms and retailers will shift toward AI platforms even if literal transactions continue occurring on retailer infrastructure.
The retailers best positioned are those who build genuine AI capability rather than relying solely on existing infrastructure advantages. The history of digital disruption suggests that infrastructure advantages delay but do not prevent platform transitions. Retailers who assume their current position is secure face greater risk than retailers who invest in AI transformation.
Conclusion
AI platforms will attempt to capture the transaction point that currently resides with retailers. This attempt is already underway through affiliate monetization, checkout integration, and early marketplace experiments. More aggressive capture through agent-based purchasing and full marketplace development will follow.
The timeline spans the next 3-7 years with different strategies maturing at different rates. Affiliate and checkout integration are immediate. Marketplace and agent commerce are medium-term.
Retailers can cooperate, compete, differentiate, or advocate, with optimal strategies varying by retailer capability and market position. Complete capture seems unlikely but significant value shift toward AI platforms seems highly probable.
The most important insight is that the current state where AI influences purchases but retailers capture transactions is unstable. Both parties have strong incentives to change this arrangement. The question is not whether it changes but how and how quickly.