Industry March 18, 2026 6 min

Is there a play for OpenAI in agentic commerce?

Business professional using laptop and mobile devices for digital commerce and data-driven decisions

OpenAI’s failed attempt to scale “pay in chat” revealed deeper structural constraints: it can neither be a commerce platform nor operate effectively as a middleman. To be a true commerce platform, it would need to build a Shopify-like ecosystem. Even if Codex could build something in a few months, it would take years to accumulate the millions of product listings, merchant relationships, transaction histories, pricing dynamics, fulfillment systems, and customer journey data required.

OpenAI must also contend with the fact that commerce platforms can easily implement their own AI interfaces, as many already are (Alibaba Accio, Amazon Agent Mode, Walmart AI, etc.). AI is merely a new front door. If OpenAI wants to become a true agentic commerce platform, it must own or control one or more of three strategic assets:

  1. The Commerce Graph (inventory, sellers, transactions)
  2. The Customer Graph (identity, purchase behavior, lifecycle data)
  3. The Product Data Graph (high-frequency usage and intent signals)

Let’s look at some potential acquisition candidates that could revive OpenAI’s agentic commerce ambitions based on strategic fit and financial feasibility.

Strategic fit criteria

  • Strength of proprietary data moat
  • Control over demand and transaction layer
  • Monetization leverage
  • Ability to reduce platform dependency.

Financial feasibility criteria

  • Approximate market capitalization
  • Acquisition realism given OpenAI’s capital structure.
  • Financing complexity
  • Regulatory and integration risk
CandidateStrategic
Impact
Financial
Feasibility
Overall
Assessment
KlaviyoHighHighOwn the customer graph
InstacartHighModerateFast cycle replenishment
EtsyModerateModerateSecondary Marketplace
BigCommerceModerateVery HighOwn the product data pipes
Cart.comLow-ModerateHighFulfillment and commerce infrastructure

Other candidates such as eBay, Shopify, Mercari are considered too big for OpenAI to acquire.

The case for Klaviyo

Own the Customer Graph

Klaviyo is a commerce customer data and lifecycle marketing platform serving 193,000+ merchants globally. It doesn’t own a marketplace it owns the customer identity layer across marketplaces. It processes billions of behavioral events, including email engagement, SMS interactions, purchase conversions, cart abandonment, and repeat buying patterns.

In its most recent fiscal year, Klaviyo delivered approximately 32% revenue growth, expanding margins, and strong free cash flow. It supports thousands of midmarket and enterprise brands and maintains net revenue retention above 109%, reflecting deep embedding in merchant workflows.

Primary value to OpenAI:

  • Deep behavioral identity graph: Access to engagement and purchase data across hundreds of thousands of merchants.
  • High-margin SaaS monetization: Recurring revenue aligned with merchant performance and retention.
  • AI-powered personalization engine: Enables OpenAI to embed agents directly into lifecycle marketing and conversion optimization workflows.

The case for Instacart

Own Fast Cycle Replenishment

Instacart is North America’s leading grocery delivery and retail media platform, partnering with 100,000+ retail locations and serving 26+ million active customers. In 2025, it processed approximately 338 million orders, generating over $37 billion in gross transaction value (GTV).

Grocery is high-frequency commerce—weekly or biweekly—creating repeated behavioral loops rarely found in discretionary retail. Instacart also operates a growing retail media business tightly integrated with shopper behavior.

Primary value to OpenAI:

  • High-frequency purchase data: Recurring basket-level signals ideal for agent habit formation.
  • Localized real-time inventory: Enables agents to optimize decisions across substitution, delivery speed, and pricing.
  • Integrated retail media monetization: Advertising revenue directly tied to purchase behavior.

The case for Etsy

Own the marketplace

Etsy operates a global marketplace focused on handmade, vintage, and specialty goods, with 100+ million active listings, 8+ million sellers, and approximately 96 million active buyers. In 2024, Etsy generated more than $12.6 billion in gross merchandise sales.

Its experience is driven by discovery rather than price, emphasizing personalization, gifting, and niche communities.

Primary value to OpenAI:

  • High-signal preference data: Deep insights into taste, gifting, and niche category behavior.
  • 2nd tier marketplace: Large enough to matter, less complex than dominant incumbents.
  • Discovery-optimized commerce: AI agents could materially improve search and recommendation quality.

The case for BigCommerce (Feedonomics)

Own the product data pipes

BigCommerce powers over 130,000 merchants across 150+ countries, generating roughly $350 million in ARR. Feedonomics provides structured product data feeds to major marketplaces (Amazon, Google, TikTok) and ad channels.

It is particularly strong in B2B commerce, where early agentic commerce value is emerging.

Primary value to OpenAI:

  • Structured product feed layer: Clean SKU, pricing, and catalog normalization critical for AI accuracy.
  • B2B commerce exposure: Early advantage in high-margin procurement automation.
  • Ecosystem leverage: Influence over product data standards feeding major marketplaces.

The case of Cart.com

Fulfillment and commerce infrastructure

Cart.com provides end-to-end commerce services, including storefronts, analytics, warehousing, and fulfillment. It has raised over $380 million and expanded through acquisitions to build a distributed logistics network.

Its platform captures operational data such as inventory velocity, shipping performance, and fulfillment timelines—data typically unavailable to discovery-layer platforms.

Primary value to OpenAI:

  • Operational telemetry: Real-world delivery and inventory data to inform agent optimization.
  • Discovery to delivery: Enables AI to reason about fulfillment constraints.
  • Multi-channel insight: Visibility across marketplaces and merchant storefronts.

OpenAI would have to buy several of these companies, top three Klaviyo (customer graph), BigCommerce (data pipes), and Instacart (fast cycle replenishment). Cart.com adds operational telemetry but is most valuable after OpenAI has control of demand and identity. Without the customer graph and habit loop, fulfillment intelligence is secondary. Etsy is a large secondary global marketplace, but Instacart delivers a marketplace and faster cycle replenishment buying activity.

Acquisitions would radically change the monetization potential of OpenAI’s commercial business. New revenue streams from AI SaaS (Klaviyo), transactions and retail media (Instacart), merchant services (BigCommerce), in addition to their enterprise contracting and consumer subscriptions. These acquisitions would make a powerful strategic statement, legitimize OpenAI’s vision of being the default interface to commerce (or at least being competitive as such), and radically rebrand the company as the AI OS for commerce.

Who owns the personal shopper?

Assuming the industry resolves the operational challenges of agentic commerce, the key question becomes: who owns the consumer interface? Consumers will likely default to a single personal shopper agent that interacts across brands and marketplaces.

OpenAI is a strong interface but has structural vulnerabilities. At best, it is a third-party app unless it secures exclusive distribution with a major device manufacturer. Even then, marketplace operators can control and meter third-party agent access—pushing OpenAI back into a margin squeeze.

More critically, platform-native competitors are emerging. A Gemini-powered Siri deployed across billions of Apple devices could be extremely difficult to displace. If OpenAI cannot effectively monetize commerce or advertising, it will depend on enterprise and consumer subscriptions—yet consumers will gravitate toward the lowest-friction interface.

Gerry Murray - Research Director, Marketing and Sales Technology - IDC

Gerry Murray is a Research Director with IDC's Marketing and Sales Technology service where he covers marketing technology and related solutions. He produces competitive assessments, market forecasts, innovator reports, maturity models, case studies, and thought leadership research. Prior to his role at IDC, Gerry spent six years in marketing at Softrax Corp. an enterprise financial solutions provider. There, he managed marketing programs that produced 4 million emails a year, multiple websites, interactive tools and product tours, an online game, collateral, and PR. Concurrently, he was Managing Editor at RevenueRecognition.com, a thought leadership site featuring partnerships with IDC and the Financial Accounting Standards Boards (FASB) which was quoted and referenced in leading industry publications such as CFO magazine, BusinessFinance, and others. Gerry spent the first half of his career at IDC advising executives from some of the world's largest software and services providers on market strategy, competitive positioning, and channel management. He was the Director of Knowledge Management Technology and conducted research on a worldwide scale including: market sizing and forecasting, ROI models, case studies, multi-client studies, focus groups, and custom consulting projects.

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