In this blog, we’ll explore Microsoft AI Builder’s capabilities, discuss practical business use cases, and find out how to start using prebuilt AI models right away.

In brief:

• AI Builder democratizes artificial intelligence by providing low-code tools within Microsoft Power Platform that enable business users to build, train, and deploy AI models without advanced coding skills.
• Prebuilt models handle common business tasks, including invoice processing, sentiment analysis, form recognition, and entity extraction—allowing teams to add intelligence to apps and workflows immediately.
• Custom models adapt to unique business needs by training on your own data for specialized use cases like customer application processing, contact extraction, and product identification.
• AI Hub now includes Prompt Builder, giving users access to GPT-4 and GPT-3.5 for conversational AI capabilities alongside traditional AI Builder models, offering greater flexibility in how you deploy AI solutions.
• Cross-industry applications span healthcare to finance, automating patient data extraction, manufacturing defect detection, fraud detection, and invoice processing to reduce errors and improve decision-making.

Microsoft’s mission is to help people and businesses improve operations, drive efficiency, and unlock the power of data. While Azure’s advanced AI tools support developers, Microsoft AI Builder makes artificial intelligence accessible to a broader audience, offering a simplified way to build, train, and deploy models within the Microsoft Power Platform.

What Is Microsoft’s AI Builder?

Microsoft’s AI Builder is a low-code AI tool available within the Microsoft Power Platform, accessible through both Power Apps and Power Automate. It allows business users to apply machine learning and natural language capabilities to their workflows with no advanced coding skills required.

By integrating AI Builder with low-code or no-code tools, you can build intelligent applications, automate tasks, and streamline operations across your organization.

Power Apps empowers citizen developers to build business applications efficiently, while Power Automate automates repetitive and time-consuming workflows. AI Builder enhances these tools by providing access to core AI capabilities like:

• Machine learning
• Cognitive services
• Natural language processing (NLP)
• Computer vision

Together, these technologies power AI Builder models that help improve data accuracy, automate manual processes, and deliver actionable insights.

Microsoft AI Builder and Prompt Builder: What’s the Difference?

Microsoft recently evolved AI Builder into a broader solution called AI Hub, which now includes Prompt Builder, a tool currently in preview.

While we’ll continue to refer to it as AI Builder for clarity, the newly integrated platform empowers users to either use prebuilt AI models or create custom prompts using large language models (LLMs) like GPT-4 and GPT-3.5.

Prompt Builder provides a conversational interface that enables users to design and deploy AI prompts directly within Power Apps and Power Automate. These GPT-based prompts offer more flexibility, allowing users to generate responses, summarize content, classify data, and perform additional tasks.

It’s important to note that while both AI Builder and Prompt Builder help you use AI to drive action, their deployment workflows differ significantly. Here’s how:

How AI Builder Works

• Choose a prebuilt model or create a custom AI model
• Select a model type (e.g., Document Processing).
• Follow a step-by-step wizard to:
  • Connect your target data to the process
  • Provide sample data inputs
  • Tagging that data to train the model for accuracy
• Deploy it in Power Automate or Power Apps

How Prompt Builder Works

• Choose from existing GPT prompts or create a new one
• Use a conversational design interface
• Input prompt instructions (with optional input parameters from Power Apps or Power Automate)
• Select a GPT model (3.5 or 4)
• Use model output to trigger downstream actions in your flows or apps

Since the back-end models differ, results may vary. We recommend testing both tools to determine which best supports your unique business needs.

Prebuilt or Custom AI Models? The Choice Is Yours

AI Builder models give users two flexible paths: leveraging prebuilt models or creating custom ones tailored to specific business challenges. These models are trained to detect patterns in data and help automate decisions, allowing you to improve efficiency with less development overhead.

Prebuilt Models

Prebuilt AI Builder models let you add intelligence to apps and flows without the need to collect and label training data. For example:

• In Power Automate, you can use a prebuilt sentiment analysis model to evaluate customer feedback.
• In Power Apps, you can insert a component to scan business cards and automatically extract contact information.

The following models can be built within AI Builder and incorporated into a Power Apps or Power Automate flow:

• Business card reader
• Form processing (invoices, receipts, ID documents)
• Sentiment analysis
• Key phrase and entity extraction
• Image description (preview)
• Language detection
• Text recognition
• Text translation (only available in Power Automate)
• Text generation (deprecated)
• Text generation (preview) (deprecated)

Each of these is trained to recognize specific fields or content types. For example, the invoice model automatically identifies due dates, invoice totals, and invoice numbers.

Custom AI Models

When your needs go beyond what prebuilt models can handle, AI Builder enables you to train custom models with your own business data. This gives you more control over accuracy and performance.

A few real-world examples include:

• Customer Application Processing: Scan and extract handwritten or printed information from forms and populate fields automatically using form processing.
• Contact List Creation: At events, use a canvas app built in Power Apps to capture photos of business cards or sign-in sheets, extract contact details, and load them into your CRM within hours instead of days.

To see other kinds of business scenarios that Microsoft supports through its AI Builder models, check out this chart on Microsoft’s website, and take a look at these common use cases.

Next, we explore how these prebuilt models can solve common pain points.

Prebuilt Models in AI Builder: Solving Real Business Challenges

To illustrate the value of Microsoft AI Builder, let’s explore a retail business scenario and how prebuilt models can solve specific challenges.

Scenario

ABC Retail, an e-commerce clothing brand, struggles to manage information across multiple channels. These inefficiencies impact everything from customer experience to marketing performance.

Pain Point 1: Difficulty Identifying Key Customer Reviews

The team spends too much time sifting through reviews, missing critical feedback that could impact the brand.

AI Builder Solutions:

• Category classification breaks down reviews by product type
• Key phrase extraction summarizes reviews and shares the main concepts
• Sentiment analysis identifies any negative reviews for quick customer service

Pain Point 2: Missed Engagement Opportunities on Social Media

With limited visibility into relevant content, ABC Retail misses moments to engage with customers.

AI Builder Solution

Entity extraction identifies when references are made to ABC Retail rather than another similarly named entity. For example, “The purse I got from ABC was so cute” is a match, but “My child loves to sing the ABC song with their friends” is not, so AI Builder identifies it as not relevant.

Pain Point 3: Disorganized Data Across Formats

The company stores information in various formats, making it tedious to process and resulting in poor reporting.

AI Builder Solution

Form processing using the invoice model accelerates supplier invoice processing and extracts data from important fields. That means less time spent on humdrum tasks and more time available for building the business.

Pain Point 4: Missed User-Generated Content for Marketing

The company squanders opportunities to drive customers to their website because they are not taking advantage of community posts showing people wearing ABC products.

AI Builder Solution

Object detection, in conjunction with entity extraction, identifies products from posted images or when creating marketing content after a photoshoot.

AI Builder’s Versatile Use Cases

Microsoft AI Builder supports a wide range of industry applications, helping organizations automate processes, reduce errors, and improve decision-making with minimal development effort.

• Healthcare: AI Builder can automate patient data extraction from medical forms, improving both the speed and accuracy of data entry. It can also enhance diagnosis accuracy and analyze medical imaging data.
• Manufacturing: Manufacturers use AI Builder to analyze sensor data and visual inputs to detect defects early, improving product quality and reducing waste from production errors.
• Finance: In the financial sector, AI Builder supports fraud detection, streamlines risk assessments, and accelerates invoice processing by automating data extraction from financial documents.

Despite its powerful capabilities, AI Builder is designed to be user-friendly, making it easier for teams to get started without extensive technical expertise. Below are the steps to get started with the tool.

Getting Started With Creating a Custom Model in AI Builder (AI Hub)

Microsoft AI Builder allows you to create custom models trained on your own business data to perform a wide range of tasks. These models can be integrated into Power Apps and Power Automate, similar to prompts built with GPT technology.

You can also use Prompt Builder to generate reusable components that apply AI to tasks such as summarization, classification, sentiment analysis, and response generation. Whether you’re building from scratch or leveraging Microsoft’s existing language models, getting started is simple.

It’s easy to put AI Builder in motion. Just access it from Power Apps or Power Automate and follow these steps:

1. Select the AI model type. Choose a model that fits your specific business needs.
2. Connect your data. The in-app wizard guides you through the setup and outlines the data required.
3. Train your AI model. Upload your training data and define what the model should analyze (for example, the text fields it should extract from a document). After training, you can test and publish the model.
4. Create solutions across the Power Platform with your new AI Model. Use it to generate insights, create new records, or integrate into existing tables for analysis and workflow automation.

You can read more about this tool and review a comprehensive breakdown of the steps above in Microsoft’s AI Builder documentation.

Microsoft is continually evolving AI Builder to enhance efficiency and functionality, enabling it to handle a business process climate that is never stagnant and always dynamic. Next, we’ll look at where Microsoft plans to take this tool in the future.

Future Developments for Microsoft AI Builder

Microsoft continues to enhance the AI Builder solution with updates that improve performance, accuracy, and user experience. You can always visit Power Platform’s release plans to keep up, but below are some of the major releases that are in preview or intended for 2026:

The only item I found slated for 2026 is the following:

• Test and validate AI prompt actions for better outcomes. This feature allows you to use a prompt as instructions to a Copilot or Power Automate. With this capability, you can do batch testing on various scenarios to ensure the effectiveness of your prompt.
• Monitor Usage of AI Builder Models, Including GPT Outputs. Preconfigured reports are available to display which models or prompts are being used, the data being processed, and the credits being consumed.
• Validation Station. This feature lets you send feedback to makers based on the AI-generated content to modify and enhance models to generate more accurate results.
• Document Processing Agent. Copilot Studio Agents can be extended with document processing capabilities from AI Builder to automate and streamline document workflows.
• Ground With Connectors in Prompt Builder. This lets you use connector data in prompts that are currently limited to data only in Microsoft Dataverse.

These improvements aim to help organizations confidently scale AI adoption, aligning it with business needs and compliance standards.

Maximize Business Efficiency With Microsoft AI Builder

Microsoft built the AI Builder for today’s challenges and to evolve with your business and support long-term growth. With its extensive capabilities and integration across the Microsoft Power Platform, AI Builder empowers organizations to automate processes, uncover insights, and adapt to changing business demands.

As new features continue to roll out, this low-code AI solution will help more businesses scale smarter, streamline operations, and stay ahead of evolving market needs. Whether you’re looking to improve decision-making or modernize workflows, AI Builder is built to support enterprise-wide transformation.

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