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    Home»Technology»How Agentic AI Is Redefining Digital Commerce in 2025
    Technology

    How Agentic AI Is Redefining Digital Commerce in 2025

    Zayne PhamBy Zayne PhamJuly 4, 2025No Comments4 Mins Read3 Views
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    Agentic AI in Digital Commerce: The Next Frontier of Autonomy.
    Agentic AI in Digital Commerce: The Next Frontier of Autonomy.
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    Artificial Intelligence has evolved beyond passive assistance—agentic AI now independently performs tasks like shopping, order management, and customer support. This advancement is reshaping digital commerce, creating seamless, personalized experiences. Here’s how this new generation of AI agents is transforming the industry.


    What Is Agentic AI?

    Agentic AI refers to intelligent systems that perceive, decide, and act autonomously to achieve user-defined goals without constant human input. Unlike traditional AI or generative models, agentic AI operates proactively within parameters and thresholds set by users, performing tasks end-to-end—such as automated shopping, inventory management, and support services .

    Agentic AI in Everyday Commerce

    From household errands to enterprise operations, agentic AI is integrating into every layer of commerce:

    • Autonomous shopping assistants: AI agents can track preferences, find optimal deals, complete purchases, and manage returns—all on behalf of the user .

    • Retail automation: Brands deploy agentic systems to handle SEO updates, compliance checks, catalog management, and supply chain coordination, reducing reliance on manual processes.

    • Proactive home and business management: Agents monitor household supplies or business inventories, automating reorder workflows and subscription management .

    Retail and Enterprise Adoption

    Major retailers and fintech players are racing to implement agentic AI:

    • Mastercard and Visa are building tokens and payment solutions to secure agentic transactions, ensuring traceability and human authorization.

    • Walmart is testing in-app AI for reordering groceries and planning purchases, alongside support for third-party agents.

    • SharkNinja is piloting Salesforce’s Agentforce to integrate intelligent agents into e‑commerce workflows.

    • Cisco research predicts agentic AI will handle up to 68% of customer support interactions by 2028, enhancing predictive service delivery.

    • Bank of New York Mellon has onboarded AI “digital workers” for tasks like payment validation, with other financial institutions following suit.


    Benefits Driving Agentic AI

    Agentic AI offers several tangible advantages:

    1. Enhanced personalization: Agents tailor recommendations by analyzing real-time behavior and preferences, mirroring human-like assistance.

    2. Operational efficiency: Tasks like inventory adjustments, pricing, and content updates are automated, lowering costs and boosting speed.

    3. Faster decision cycles: Agents detect and respond to market shifts—like flash sales or promotions—in real time.

    4. Improved customer experience: Seamless, support-driven interactions foster trust and loyalty.

    Risk Of AI Autonomy

    While promising, agentic AI introduces novel concerns:

    • Trust & transparency: Consumers worry about AI making purchases without oversight and maintaining privacy.

    • Fraud and identity risks: Automated agents may complicate fraud detection—merchants need new systems to verify legitimate agent activity.

    • Legacy system constraints: Older e‑commerce platforms struggle with real-time task execution and scalability.

    • Ethical and governance frameworks: Safeguards are necessary to prevent misuse, require consent protocols, and ensure responsible autonomy .

    Key Technological Ecosystem

    The rise of agentic AI is supported by a robust tech stack:

    • Model Context Protocol (MCP): Enables secure, modular integration of AI agents into enterprise systems.

    • Agentic Tokens: Payment credentials that tie AI transactions to user authorizations.

    • Composable retail infrastructure: Flexible CMS/PIM systems, real-time data pipelines, and orchestration layers facilitate scalable automation.


    Practical Use Cases of Agentic AI

    Leading use cases where agentic AI shows impact:

    • Product catalog upkeep: Auto-updated listings optimized for SEO and compliance.

    • Dynamic pricing: Adaptive price strategies reacting to competitor activity and stock levels salesforce.com.

    • Autonomous support: Agents proactively handle support interactions, preempting issues and escalating as needed.

    • End-to-end shopping: AI-driven discovery, comparison, checkout, and post-purchase follow-ups—all within conversational interfaces.


    Is Agentic AI The Future of Digital Commerce?

    Agentic AI is poised to usher in an era of intelligent, autonomous digital commerce. Gartner projects that by 2028, 20% of digital storefront interactions will occur through AI agents . The future will feature:

    • Fully autonomous shopping ecosystems, where agents coordinate across platforms.

    • New advertising models, as brands target agents rather than human shoppers.

    • Governance frameworks that balance capability with control and ethical oversight.

    Agentic AI is not just a technological novelty—it represents a paradigm shift in commerce. By autonomously managing tasks, optimizing operations, and driving personalized experiences, AI agents are becoming indispensable in retail and enterprise operations. Yet success hinges on building trust, upgrading infrastructures, and establishing ethical guardrails. Brands that navigate these challenges are set to lead the next wave of truly intelligent commerce.

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    Zayne Pham

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