What is Agentic AI and How Does It Work? (For eCommerce Brands)

Welcome to the next frontier in artificial intelligence: Agentic AI. If you've spent any time lately doomscrolling through AI headlines or testing tools like ChatGPT, you've probably heard whispers of "AI agents". But what does it mean? And more importantly for eCommerce brands: is this just another tech fad, or is there real-world potential behind the buzz?

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In this article, we break down what Agentic AI actually is, how it works, and why it could be a game-changer for brands trying to outpace the competition. Spoiler alert: it’s not just hype.

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What is Agentic AI?

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Let’s start simple. Agentic AI refers to artificial intelligence systems that can make decisions, take actions, and adapt to results without needing constant human input. Instead of just answering questions (like a chatbot), these systems behave more like autonomous agents with specific goals, tools at their disposal, and the smarts to pursue outcomes.

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You can think of Agentic AI as the difference between:

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• ChatGPT, which answers your questions.
  
  
• An AI agent, which takes your goals and starts solving problems independently.
  
  

In short, agentic AI systems are designed to do things, not just say things.

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This shift from reactive to proactive is massive, and it’s unlocking new opportunities in everything from code generation and research to, yes, eCommerce.

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How Agentic AI Works (Without the Tech Jargon)

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Let’s break it down with as little Silicon Valley hand-waving as possible.

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Agentic AI systems typically work through a loop that mimics a smart assistant that never sleeps:

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1. Goal Setting
   
   • It starts with you. You give the agent a clear objective,  whether that's “increase profit margin,” “lower customer acquisition costs,” or “identify slow-moving inventory.”

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2. Planning and Strategy Generation
   
   • The AI doesn’t just dive in,  it creates a plan. It figures out which data sources it needs, identifies the right metrics to track, and outlines a sequence of actions. Think of it as writing its own to-do list based on your goals.

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3. Tool Use and Execution
   
   • Using integrations (APIs, dashboards, reporting tools, etc.), the AI agent pulls in data, crunches numbers, and executes tasks like updating ad budgets, tagging products, or flagging underperformers.

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4. Monitoring and Feedback Loop
   
   • After acting, the agent watches the results. Did conversions increase? Did stock improve? If not, it adjusts and tries a new approach. This learning loop is what separates agentic AI from traditional rule-based automation.

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5. Iteration and Self-Improvement
   
   • Over time, the agent refines its decision-making based on historical performance and contextual feedback. In a sense, it becomes more experienced, just like a good team member.

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This cycle allows agentic systems to manage complex, cross-functional tasks, the kind you’d normally need a team (or a ton of manual hours) to coordinate. And because they operate in real-time, they can respond to performance changes far faster than any human analyst could.

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Real-Life Examples of Agentic AI

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Agentic AI might sound futuristic, but it's already at work across industries:

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1. Software Development

Tools like AutoGPT and Devin act as autonomous coding agents. You don’t tell them how to code, you tell them what you want built. From there, they research requirements, write the code, test it, and even debug errors. It’s like hiring a junior developer who works around the clock.

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2. Market Research & Content Creation

Instead of Googling and compiling research manually, agentic systems can browse the web, summarise sources, cross-reference information, and deliver a draft blog, business report or strategy summary - all within minutes.

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3. Executive Assistants

Personal AI assistants can now schedule meetings, book travel, respond to emails, and manage to-do lists autonomously. They interpret context, handle unexpected changes, and even send reminders.

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4. Customer Service Bots

Some AI agents are empowered to resolve tickets without a script - interpreting sentiment, applying discount policies, escalating appropriately, or offering relevant products.

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In each of these scenarios, the agent isn’t simply following rules. It’s reasoning, adapting, and executing across multiple steps to fulfil a larger business goal.

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Now imagine applying that level of autonomy to your entire eCommerce operation…

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Agentic AI in eCommerce: The Opportunity

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This is where the future gets exciting and very practical. If you’re running an eCommerce brand, agentic AI can act like a multi-skilled strategist, marketer, merchandiser, and analyst all rolled into one.

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Here’s how it plays out across key areas of your business:

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🛒 Marketing

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An agentic system can:

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• Monitor your ad campaigns across Google, Meta, TikTok and Bing in real time.
• Spot underperforming creatives, high CPA campaigns, or wasted budget.
• Reallocate spend toward high-converting SKUs with strong contribution margins.
• Automatically generate and test new ad copy based on past performance.

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And it can do this continuously, without needing your marketing team to manually pull and compare reports every week.

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📦 Merchandising

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Merchandising agents can:

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• Analyze sell-through rates, stock levels, and historical demand.
• Identify products that are overpriced, overstocked or slow-moving.
• Recommend actions like bundling, price drops, or prioritised promotions.
• Flag low inventory for high performers so you never miss a reorder window.

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Instead of managing by gut feeling, these insights help teams make data-backed decisions faster and sometimes automatically.

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💰 Finance & Profitability

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What if you had an agent whose only job was to protect your margins?

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• It could track your contribution profit at the SKU, category, or channel level.
• Detect trends that hurt profitability (e.g. rising ad costs, high return rates).
• Alert you to early warning signs and propose corrective actions.
• Forecast future profitability under different pricing, stock or ad scenarios.

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Think of it as having a profitability watchdog that never sleeps.

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👥 Customer Retention & Lifecycle

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Agentic AI can:

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• Segment customers by cohort, behaviour and LTV.
• Spot customers at risk of churning and automate winback campaigns.
• Optimize email offers and A/B test incentives based on individual preferences.
• Track and improve your repeat rate over time.

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It’s like having a loyalty manager who knows every customer personally and acts accordingly.

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In essence, agentic AI doesn’t just make sense of your data. It acts on it, driving decisions, actions and outcomes, all without waiting for someone to run a report.

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And with platforms like Conjura’s AI Agent, this isn’t a vision of the future. It’s already happening.

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AI Tools for eCommerce (And the Rise of Agentic Platforms)

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There’s no shortage of AI tools promising to “revolutionise” eCommerce, from product description generators to customer support chatbots. But most still rely on manual prompts and siloed data.

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Conjura’s AI Agent is different. It's like ChatGPT,  but for your entire eCommerce analytics stack.

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It acts like an in-house AI Analyst. You can ask it to:

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• Generate instant performance reports (e.g. "How did my UK store perform vs Germany this month?")
  
  
• Surface strategic insights (e.g. "Which products are hurting my contribution profit?")
  
  
• Deliver predictive forecasting on revenue, customer lifetime value (LTV), and stock levels
  
  
• Recommend actions based on real-time performance data
  
  

This kind of agentic AI for eCommerce turns your raw performance data into a decision-making engine - no spreadsheet wrangling or data scientist required.

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As AI continues to evolve, platforms like Conjura are paving the way for eCommerce brands to make faster, smarter, and more profitable decisions, autonomously.

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Risks and Considerations of Agentic AI

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Of course, autonomy doesn’t come without risk.

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• Loss of control: Agentic systems need guardrails. If not well-managed, they could make decisions based on the wrong signals.
  
  
• Data quality: Garbage in, garbage out. If your product, customer, or marketing data isn’t clean and structured, agentic tools will struggle.
  
  

That said, these risks are manageable, especially when tools are designed with transparency and business context (like Conjura) built in.

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Why Agentic AI is the Future of AI eCommerce

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Agentic AI represents a shift from insights to action. Instead of waiting for reports or manually digging through dashboards, brands can now act at the speed of their data.

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For eCommerce brands looking to stay ahead, this isn’t just a nice-to-have. It’s the future of how high-performing businesses will operate. Having an in-house data analyst is expensive; however, now with Conjura’s AI Agent, powerful, easy-to-understand insights are available at a fraction of the cost. 

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Agentic AI exists to optimize your eCommerce business’s processes, unlocking exciting doors that weren’t possible before. 

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If you’re interested in Conjura’s AI Agent then book a demo here. 

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