How AI agents are going to re-shape ecommerce, operations and customer support

Table of contents

• The rise of AI agents and why they matter
• AI in commerce: smarter buying and selling
• AI in operations: increasing efficiency and data-driven outcomes
• Helping both decision-makers and frontline teams
• AI in customer care: building trust and loyalty through a deeper, personalized customer journey
• What the future holds for AI agents
• Why businesses & operators should take the leap  

Artificial Intelligence (AI) has made significant inroads into various aspects of businesses, fundamentally reshaping how organizations operate, execute and interact with customers. 

Among the numerous AI advancements, AI agents are emerging as the next frontier of process efficiencies.  

By leveraging AI agents, businesses streamline complex processes, improve decision-making across tiered data insights via multiple systems and enhance customer experiences with rapid, personalized solutions.  

But what sets these AI agents apart and how are they empowering businesses to evolve toward a smarter, more efficient future?  

This blog explores the revolutionary role of AI agents in three core areas of enterprise functionality and illustrates how they’re transforming industries across the globe. 

The rise of AI agents and why they matter 

AI agents are intelligent systems designed to perform tasks autonomously or support decision-making processes.  

Equipped with advanced algorithms, these agents analyze vast amounts of data, learn repetitive patterns and either execute specific instructions or recommend optimal actions. 

What distinguishes AI agents from traditional tools is their ability to seamlessly integrate into ecosystems using layers like MCP (model context protocol). The protocol offers multi-layered functionality to agents that allows them to cross pollinate across various systems to find an answer or solution.

Why AI agents are a must-have for modern operators 

• Efficiency gains: automating repetitive tasks reduces human error and allows teams to focus on high-impact activities.  
• Data-driven decisions: pre–filled agents with historical context can offer up actionable insights without being asked. 
• Customer-centric interactions
• Scalability: AI agents offer solutions that can grow with you, from automating workflows to orchestrating multi-dimensional fulfillment

AI in commerce: smarter buying and selling 

Chatbots in retail and ecommerce have always been present on landing pages and home pages.  

We are now starting to see the evolution of AI agents embedded into these chatbots to drive deeper personalization. 

Personalizing the shopping experience 

A deeper understanding of consumers drives better loyalty, higher retention and improved cart conversion.  

The ability for AI agents to increase AOV (average order value) of carts is possible at scale by analyzing purchase history through detailed order repository histories.

• Example: Platforms like Amazon use AI-driven algorithms like Rufus to recommend complementary products and create dynamic conversion strategies for real-time back-end optimization. 

Optimizing inventory and product listings 

The ability to use foresight has long been a needed requirement in supply chain execution. The nuances of upstream inventory components are essential to optimizing inventory downstream.

Retailers, brands and businesses using AI enabled order decisioning like Infios Order Management to achieve 33% faster restocking and prevent loss through predictive inventory adjustments and agentic workflows.

AI in operations: increasing efficiency and data-driven outcomes 

Operations are the backbone of any business and integrating AI agents into these workflows ensures smoother, data-rich processes across supply chains order fulfillment and resource optimization. 

Streamlining supply chain management 

Machine learning has long been the only way that supply chains navigated disruptions.  

Looking at historical data, algorithms would give you statistical relevance of events and how to navigate them accordingly. That changes significantly with the power of AI agents.

Did you know? A recent study by PWC found that 70% of Operations Executives 3 or greater operating profit benefits by leveraging AI Agents. 

Helping both decision-makers and frontline teams

 AI agents can gather data from across systems, using tools like MCP (model context protocol) and turn it into clear, actionable dashboards.  

That way, leaders get strategic insights and operators get real-time information they can actually use.  

These insights help leaders make faster and smarter decisions; whether that’s adjusting growth plans, managing costs or coordinating with vendors in real time.

• Example: With tools like Tableau and Power BI - now powered by AI, C-suite leaders can quickly see where supply is lagging behind demand and make real-time decisions based on the data.

AI in customer care: building trust and loyalty through a deeper, personalized customer journey

A customized touch goes a long way. This is evident in live shopping experiences where curators offer a much deeper and improved experience to consumers.  

Building loyalty and trust with consumers requires a deeper understanding of their needs – thus leveraging AI to identify these unmet needs and deliver a personalized experience. 

Delighting at the first touch 

Ever been bugged by a chatbot and liked it? The answer is probably no.  

Although chatbots have been around for over a decade, intelligent AI agents are able to be much more conducive to cart conversion improvements or offering personalized service based on order history information. 

• Example: Intelligent AI bots like Solvvy (acquired by Zoom) reduce first-response times by 60% while freeing human agents to focus on complex issues. 

Supporting multi-channel communications 

Consumers interact with brands in whatever way they choose – albeit with email, social media or text/phone calls. This kind of complexity forces humans to jump between systems, chasing down information manually.

AI agents, especially those using MCP (model context protocol), can cut through the layers, surfacing the right details at the right time and guiding each customer interaction in a consistent, structured way.

• Example: Zendesk’s AI tools do this by giving agents instant access to past conversations, making it easier to deliver seamless, personalized service without starting from scratch every time.

What the future holds for AI agents  

AI agents should be our companions - not replacements.  

This is essential to understand and call out. The world will see a shift in roles and responsibilities, but AI is not a direct replacement for humans.  

While significant progress has been made, the potential of AI agents is just beginning to unwrap.  

The future holds even greater possibilities, including advanced contextual understanding, predictive customer support, autonomous financial operations and industry-specific AI use cases.  

We’re also seeing the rise of modular AI systems - tools that let businesses plug AI into the areas where it matters most.  

Whether it’s connecting to an ERP, streamlining order management or surfacing real-time business insights, these systems are built for flexibility. They give companies the ability to adapt as they grow, without locking into one-size-fits-all solutions. 

Why businesses & operators should take the leap  

 AI Agents will provide significant efficiencies for businesses that take calculated leaps into the space.  

Companies that succeed in adopting AI agents often achieve long-lasting advantages, such as lower operational costs, higher fulfillment accuracy and sustained customer trust.  

Whether you’re navigating omnichannel commerce, leveling up operational capabilities or reshaping customer support, AI agents fit seamlessly into your systems to deliver immediate results. With AI agents on your side and humans in the loop, the future is much more malleable.