The scenario is rapidly approaching reality: you tell your phone, "Find me a pair of trail running shoes under $150, deliverable by Friday, preferably not all black." In the blink of an eye, an AI filters suitable products. You say "yes," payment is processed, and an order confirmation SMS arrives on your phone—all without clicking an "add to cart" button. Following the integration of Qwen App with Taobao's flash sales last year, which enabled food ordering via simple commands, ByteDance's Doubao has also entered the e-commerce fray, recently starting an internal AI shopping test where users can directly say "buy this" to place an order, skipping page redirects entirely.

This shift in user experience offers a glimpse into the embryonic form of Agentic Commerce. Internet giants are strategically positioning themselves, unanimously betting on the same future: AI will be the one filling your shopping cart. The term "Agentic Commerce," while complex, is fundamentally reshaping our entire understanding of "shopping."

Behind this instantaneous process lies a massive industrial chain in motion. A simple request like "find trail running shoes" requires the AI to rapidly execute a multi-step workflow: deconstructing the need, performing cross-platform filtering and brand recommendations, evaluating merchants and logistics, and finally completing the payment. In that blink, five layers—models, protocols, payment systems, platforms, and tools—activate simultaneously, involving a vast industrial network. The bet is on an irreversible trend: consumers can now spend money directly through AI interfaces.

This hypothesis is supported by China Securities' latest analysis, which identifies 2026 as a critical window for Agentic Commerce to evolve from concept to protocolization and standardization. McKinsey further predicts this model could redirect $3 to $5 trillion in global retail spending by 2030. AI-driven visitors are no longer synonymous with low-quality traffic. Adobe data indicates that by mid-2025, AI-generated traffic to retail websites grew 4700% year-over-year, while Shopify reported a 15-fold annual increase in orders originating from AI searches. Clearly, this is not merely an iteration of traditional shelf-based or content e-commerce, but a new frontier for the consumer internet. The logic is simple: when shopping can be accomplished through natural conversation, bypassing the need to open apps or browse websites, it unleashes significant consumer potential previously constrained by traditional processes, creating a genuine, tangible trillion-dollar incremental market.

In the race for this trillion-dollar opportunity, global tech giants, payment providers, and e-commerce platforms have been actively participating over the past six months, each leveraging their core strengths to assemble the essential pieces of the Agentic Commerce puzzle. The competition is fierce, with the battle for the entry point layer, exemplified by the close contest between OpenAI and Google, being particularly prominent. In September 2025, OpenAI partnered with Stripe to launch the ACP protocol, enabling direct shopping within ChatGPT. By January 2026, Google collaborated with 20 retail giants to release the UCP protocol, aiming to connect the entire e-commerce world to its conversational AI. This clash of protocols is essentially a struggle to define the "universal language" between AI Agents and merchant systems, targeting the power to define the primary entry point for AI-powered shopping.

A deeper logic lies in the shifting dynamics of the broader advertising market. According to Dentsu forecasts, global ad spend is expected to surpass the $1 trillion mark for the first time in 2026, growing 5.1% year-over-year, significantly outpacing the projected 3.1% global GDP growth. The scale of a trillion dollars underscores that AI is entering a massive, essential, existing market. Even OpenAI has acknowledged the power of advertising, trialing ad services earlier this year and reportedly generating $100 million in revenue within just six weeks, stunning observers with the aggressive potential of AI monetization. The company has even suggested it aims for its ad business to reach $102 billion by 2030. Advertisers spend trillions annually on traffic, creativity, and placement, but is this spending efficient? Can AI precisely capture and amplify its impact? These are the core challenges that AI Marketing Technology (MarTech) aims to address.

At its essence, AI MarTech serves as a super-entry point linking e-commerce, advertising, and AI applications. Consumers require precise targeting, and brands need intelligent recommendation. This involves real-time integration of traffic sources, cleaning and labeling structured data across platforms, deep analysis of consumer intent by specialized models, and instantaneous optimization of advertising strategies by marketing Agents. Further illustrating the scale of MarTech, Frost & Sullivan's latest statistics peg the global AI MarTech market at $34.2 billion in 2025—a solid hundred-billion-dollar market and the industrial logic behind MarTech's springtime. The transition from massive ad budgets to精细化 AI-driven decision-making demands an efficiency revolution, and AI MarTech is poised to be the precise instrument for that change.

The landscape is crowded with players. Companies like Salesforce, Shopify, AppLovin, and T-Impact are pushing the boundaries of AI MarTech from their respective domains. Legacy SaaS leader Salesforce was quick to expand its Agentforce platform, offering一站式 Agent assistance for customer service, sales, and internal processes. It has reportedly become Salesforce's fastest-growing star product, generating over $500 million in revenue shortly after launch and maintaining a stable market capitalization within the trillion-dollar club. E-commerce services giant Shopify, valued in the hundreds of billions, is betting on volume to win the AI entry point race with its Agentic Storefronts, allowing millions of merchants to connect to all AI entry points at zero cost. By January 2026, it had already processed 350,000 AI-driven orders, with its market cap recently reaching $170 billion. AppLovin, renowned in mobile game advertising, has forcefully entered the e-commerce track with its AXON 2.0 engine, seeing nearly 20% quarter-over-quarter growth in e-commerce clients in Q4 and surpassing a $150 billion market cap.

Chinese AI MarTech firm T-Impact has adopted a dual-track technological approach, focusing on both specialized marketing models and multi-agent systems for marketing. Leveraging a decade of experience in cross-border e-commerce, it has pioneered the AI-driven transformation of the entire marketing workflow—from market insight and creative production to placement optimization—compressing processes that once took months down to hours. It also deeply integrates with global traffic data sources and major overseas e-commerce service platforms, serving over 100,000 advertisers by 2025. Every link in the industrial chain is vigorously stirring this trillion-dollar commercial restructuring. Entry tickets to the massive opportunity are available across the board, but the ranking contest within the MarTech sector has only just begun.

As sensitive observers of industrial trends, major investment banks have also weighed in on the ecosystem derived from Agentic Commerce. China Securities included toolchain service providers in a recommended list, noting that players offering merchants data integration, Agent toolchains, and generative marketing optimization are well-positioned to capture a new wave of digital budget migration. Goldman Sachs recently highlighted the e-commerce industry as a key recommendation. As early as January, it identified advertising and marketing as one of the most noteworthy AI themes, citing advertisers' shift from pure SEO to a combined "SEO + GEO + AEO" strategy to ensure content visibility in AI-driven scenarios. Reports indicate that T-Impact has correspondingly launched a GEO solution, leveraging what it claims is the world's leading specialized marketing large language model to strike a balance between AI technical depth and understanding of marketing scenarios, helping brands secure "recommendation rights" in the GEO era.

An even more imaginative growth area lies in A2A (Agent-to-Agent) advertising. Some analysts believe A2A ads could capture 40% of the total advertising market, representing a new commercial space worth approximately $400 to $500 billion. In fact, participation in the A2A ecosystem is becoming a benchmark for determining a company's viability in the Agentic Commerce era. Following the joint release of the A2A open standard by Google and the Linux Foundation in April last year, rapid adoption by AWS, Microsoft, and Salesforce signaled a push to establish a "common language" for AI agents. This implies that a company lacking its own Agent and A2A integration capability risks being permanently muted in the era of Agent dialogue.

T-Impact recognized this early, developing one of the world's first marketing multi-agent systems, Navos, in 2025. Positioned as a "digital avatar" for the era of agent communication, Navos has achieved commercialization, built upon the company's accumulated best practices in B2B marketing services, including training on data, case studies, and client analysis, as well as corpus and knowledge materials for building RAG (Retrieval-Augmented Generation) systems. This foundation is crucial not only for creating functional Agents but also for preparing to participate meaningfully in the A2A era. Notably, these advancements are progressing in tandem with the development of underlying Agent communication protocols.

The focus of competition among marketing service providers is undergoing a fundamental shift towards Agentic Commerce. Success will no longer hinge solely on who has the most traffic or the most aggressive ad spend, but rather on who possesses the most accurate structured data (industry know-how), the most effective experiential paradigms (Skills), stronger machine-readable capabilities (A2A), and higher efficiency in interface compatibility (MCP) and task coordination (AI Orchestration).

Looking back at industrial shifts in e-commerce and advertising, every paradigm change has created new wealth legends. Amazon emerged from the shelf e-commerce era, Meta was propelled by the content e-commerce wave, Shopify achieved a hundred-billion-dollar valuation through e-commerce services, and AppLovin became a behemoth in mobile game advertising. Players that combine AI capability, marketing insight, and deep e-commerce expertise undoubtedly stand at the forefront of this current transformation. The key is not necessarily predicting which entity will become the next titan, but rather discerning the direction of the tide and recognizing the contenders positioned for the long haul.