Retail AI Agents Using Power Platform

When a mid-sized retail chain approached Powerfy, their challenge wasn’t lack of tools—it was lack of time.

“Our teams spend more time fixing things manually than innovating,” said their CTO.

Despite having Microsoft 365, Dynamics, and SharePoint, their order management, customer service, and inventory ops were stuck in a loop of manual workflows and email chains.

We showed them a new way forward: building Retail AI agents using Microsoft Power Platform—not just to automate, but to think, act, and respond intelligently.

Retail’s Hidden Labor: The Case for Retail AI agents using Power Platform


Imagine a frontline store associate juggling stock queries, a customer rep buried under return emails, and an e-commerce manager trying to identify trends buried across systems.

Retail and e-commerce are perfect grounds for AI agents:

  • Processes are repetitive yet customer-driven
  • Data is fragmented across ERP, CRM, and inventory systems
  • Customers expect real-time, personalized responses

What these companies need isn’t more dashboards—it’s AI coworkers.

And the Power Platform makes this possible.

Step 1: Identifying Agent-Ready Processes

In our engagement, we identified five high-friction use cases ripe for agent automation:

  1. Customer Return Agent
    • Pulls return data from e-commerce portals
    • Checks against return policy logic
    • Sends personalized responses via Outlook or Teams
  2. Inventory Checker Agent
    • Connects to Dynamics 365 and warehouse management
    • Answers real-time stock queries in Teams or via chat on the store’s intranet
  3. Price Match Agent
    • Scrapes competitor pricing from approved sources
    • Recommends discounting decisions
    • Updates Power BI dashboards dynamically
  4. Order Exception Handler
    • Flags orders delayed beyond SLA
    • Escalates automatically with root-cause summary
    • Notifies customer service via Teams
  5. Product Description Generator
    • Uses AI to write SEO-optimized product copy
    • Pulls key specs from SharePoint and supplier PDFs

All of these were built within 6 weeks.

Step 2: Building the Retail AI Agents Using Power Platform

Here’s how we helped the client build these agents with zero heavy code:

  • Copilot Studio was used to create conversation-driven agents
  • Power Automate orchestrated backend logic
  • Power Apps provided custom interfaces for internal use
  • Power BI delivered real-time visibility
  • Dataverse unified product, order, and customer data

Each Retail AI Agents Using Power Platform was designed around natural language prompts. For example:

“Check inventory for SKU #89342 across all warehouses”

The Inventory Agent fetched data, calculated buffer stock, and even alerted replenishment triggers.

No tickets. No middle steps. Just answers.

Step 3: Embedding Agents in the Flow of Work

Agents were deployed directly in:

  • Microsoft Teams (for store and ops staff)
  • Power Pages (for internal portals)
  • Dynamics 365 (for sales and customer service reps)

The key principle? Don’t change how people work. Enhance it.

Now, store managers simply chat with the Inventory Agent in Teams to get answers in seconds. Customer reps let the Return Agent triage inbound emails.

Step 4: Governance & Guardrails

We partnered with the IT team to:

  • Define data access roles and agent behavior boundaries
  • Use Microsoft Purview for compliance tagging
  • Establish a lightweight AI Governance Council to review new agents before deployment

Business units had freedom to innovate—but within safe, secure guidelines.

Outcomes: What Changed in 90 Days

  • 🛍️ Return response time reduced by 60%
  • 📦 Inventory queries dropped 80% in email volume
  • 🕐 Customer order issue resolution time cut in half
  • 💡 Store staff satisfaction jumped (measured via Viva Insights)

“These agents didn’t replace jobs—they removed friction,” said the Head of Retail Ops.

Why This Matters for CIOs & CTOs

You already have the tools—Power Platform, Microsoft 365, Azure. What’s missing is an AI agent strategy.

These agents:

  • Free up teams for strategic work
  • Improve customer experience with instant answers
  • Reduce operational lag without custom dev costs

And since they’re built in Power Platform, they’re scalable, governable, and customizable.

The Retail AI Agent Playbook

Here’s a quick-start model for tech leaders:

  1. Start with Friction Mapping: Where are people chasing info or doing repeat work?
  2. Design Conversational Logic: What questions should the agent answer?
  3. Use Existing Data: Leverage SharePoint, Dynamics, Outlook, Dataverse.
  4. Deploy in Teams or Portals: Let people engage where they already work.
  5. Track KPIs: Time saved, agent usage, satisfaction.

Final Thought

AI agents aren’t just for tech giants. They’re the new frontline of digital transformation—especially in fast-moving sectors like retail and e-commerce.

At Powerfy, we help CIOs and innovation leaders turn Power Platform into a factory of intelligent agents. Because in retail, speed and intelligence win. And now, you can have both.
At PowerFy, we are ever eager to help you in creating Retail AI Agents Using Power Platform, get in touch with us here.