Checking and validating hundreds of incoming leads every day is a massive headache for sales teams. With leads coming from multiple sources—such as contact forms, inbound emails, and third-party integrations—your Dynamics 365 system can quickly become cluttered with fake emails, test submissions, and outright spam. Reps end up wasting precious hours sifting through garbage data instead of engaging with genuine prospects. What if you could automatically validate every incoming lead, assess its authenticity, and boost your lead score in real time using native Power Platform tools? Here is a step-by-step guide on how to build an automated AI-Based Lead Scanner for Dynamics 365 Sales and Marketing using Power Automate and AI Builder Prompts. Solution Architecture Overview The solution relies entirely on native, low-code Power Platform features: Trigger: A new Lead record is created in Dataverse/Dynamics 365 (via Web, Email, or API integration). AI Analysis: Power Automate calls a custom AI Builder Prompt, passing four key attributes: Email, Phone Number, Address, and Description. Structured Validation: AI analyzes the lead data for syntax, disposable domains, and logical consistency (e.g., matching area code formats to physical address locations). Actionable Output: AI returns a structured JSON payload with individual check results and a confidence score. Automated Lead Scoring: Dynamics 365 processes the output to auto-update custom lead fields, increment lead scores, or archive spam automatically. Step 1: Create the AI Builder Custom Prompt In the Power Apps portal, navigate to AI Hub > Prompts and create a new custom prompt. Get started with prompt library - Microsoft Copilot Studio | Microsoft Learn Inputs Define four parameters: EmailAddress PhoneNumber Address Description Prompt Definition & System Instructions Copy and paste the following prompt configuration into AI Builder: You are an expert sales lead auditor and data validation assistant. Analyze the provided lead information to determine if the lead is genuine or spam. Lead Details: Email: {EmailAddress} Phone: {PhoneNumber} Address: {Address} Description: {Description} Analysis Guidelines: Check if the email address syntax is valid and whether it looks like a temporary/disposable domain or spam pattern (e.g., test12345@asdf.com). Check if the phone number is valid and if its country/area code logically aligns with the provided address location. Verify if the street address appears to be a real, plausible address structure. Evaluate the description for coherent buyer intent versus generic spam, gibberish, or promotional links. Output Requirement: Respond strictly in valid JSON format using the exact schema below. Do not...