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AI Agents Revolutionize Global Commerce: The Dawn Of Agentic Commerce

Emergence Of Agentic Commerce

Major payment and technology companies are pioneering the next evolution in global commerce—agentic commerce, a system where artificial intelligence agents perform searches, compare prices, and execute purchases on behalf of consumers. This transformation builds on the growing consumer reliance on chatbots for everyday transactions and represents a significant shift from traditional e-commerce models.

From Digital To Intelligent

Industry leaders such as Visa and Mastercard are at the forefront, designing infrastructure that integrates AI into the payment process. Sandeep Malhotra, Executive Vice President for Core Payments in Asia Pacific at Mastercard, highlighted that we have transitioned from cash to digital, and now from digital to intelligent commerce. This progression promises a transformative impact potentially greater than the advent of platforms like Amazon.

How Agentic Commerce Works

The concept of agentic commerce involves AI systems that autonomously handle product discovery, price comparisons, and secure payments without requiring users to switch between multiple interfaces. For example, a user may instruct an AI to find and book the cheapest red-eye flight from Singapore to Tokyo under $500. The AI agent would then process the search, present the best options, finalize the payment using stored credentials, and complete the booking—all within a single conversational interface.

Piloting The Future

Both Visa and Mastercard have initiated early pilot programs to refine and secure this technology. With promising tests in regions such as Asia Pacific, experts predict the technology will fully materialize around early 2026. The rapid adoption of AI-enhanced shopping experiences, as evidenced by a significant rise in AI-driven retail site traffic reported by Adobe, underscores the market’s readiness for this innovation.

Addressing Structural And Security Challenges

While the efficiency gains and convenience of agentic commerce are evident, there are significant challenges to overcome. Payment companies are developing robust security measures, including ‘agentic tokens’ and the recently launched Trusted Agent Protocol by Visa, to authenticate AI agents and distinguish them from malicious bots. Additionally, liability concerns must be addressed as AI systems introduce a new fifth party into the traditional four-party payment transaction framework.

Implications For Merchants And Consumers

Proponents argue that agentic commerce will streamline shopping by reducing search costs and personalizing consumer experiences. However, this shift will also require merchants to innovate rapidly—adapting their loyalty programs, pricing strategies, and customer engagement models to remain competitive in an AI-driven market. As consumer behavior evolves, traditional e-commerce practices will inevitably give way to this emerging paradigm.

The Unavoidable Shift

Despite potential hiccups during the formative phase, industry experts agree that the evolution towards agentic commerce is inevitable. With investments from major players and collaborations with AI innovators such as OpenAI, the transition from digital to intelligent commerce will redefine consumer transactions. In the near future, companies across the payment and tech sectors are poised to benefit from a more efficient, secure, and personalized shopping experience.

Mirendil Signs $100 Million Google Cloud Deal To Advance Self-Improving AI

AI startup Mirendil has signed a multi-year agreement worth more than $100 million with Google Cloud to secure computing infrastructure for its self-improving AI research.

The partnership reflects growing competition among AI companies to lock in access to high-performance computing, while cloud providers race to attract promising startups developing next-generation AI models.

Backing The Next Stage Of AI Research

Mirendil plans to use Google’s Tensor Processing Units (TPUs), Nvidia GPUs and managed training infrastructure to develop AI systems capable of improving their own performance over time.

Known as recursive self-improvement, the concept focuses on building AI that can refine its knowledge and capabilities with minimal human intervention. The technology is attracting growing interest across the industry, with several startups and leading AI labs exploring similar approaches.

According to co-founder and Chief Executive Behnam Neyshabur, the long-term goal is to develop AI that can automate scientific research and accelerate discoveries in fields such as medicine, biology and materials science.

Compute Capacity Becomes A Strategic Asset

Training increasingly advanced AI models requires enormous computing resources, making long-term infrastructure agreements a critical competitive advantage.

Mirendil said Google’s combination of TPUs and GPUs allows workloads to be matched with the most suitable hardware, improving efficiency while reducing costs for customers.

For Google Cloud, the agreement strengthens its position in the race to provide infrastructure for frontier AI developers, while giving the company exposure to one of the industry’s emerging approaches to next-generation artificial intelligence.

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