If you’ve been working with Microsoft’s AI tools for a while, you probably remember Cognitive Services and the Bot Framework - handy APIs for adding speech recognition, computer vision, or chat bots without diving deep into machine learning.

Fast forward to 2025, and Microsoft’s AI lineup has expanded (and rebranded) dramatically. Today, you’ll see names like Azure OpenAI, Microsoft Copilot, Azure AI Studio, Azure AI Services, and Azure AI Foundry.

It’s exciting… but also a bit confusing.

If you’re wondering:

• Which service should I use now?

• What happened to the older tools?

You’re in the right place. Let’s break it down, tool by tool, so you know exactly what’s what in Microsoft’s AI ecosystem this year.

Azure AI Services (Previously Cognitive Services)

Think of Azure AI Services as Microsoft’s original “ready-to-use” AI toolbox. Previously called Cognitive Services, it was rebranded in 2023 to unify Microsoft’s prebuilt AI features under one name.

These services are perfect if you want to quickly add AI capabilities—vision, speech, language, decision-making—without building your own model. You just call an API, and the heavy lifting happens behind the scenes.

Pro tip: While Azure AI Services is still the go-to for prebuilt APIs, many of its capabilities (like vision and language understanding) are now also available through Azure AI Studio workflows or Azure AI Foundry pipelines.

Azure OpenAI Service

Launched in 2021, Azure OpenAI Service brings OpenAI’s powerful models—like GPT-4 and GPT-4o—into the secure, enterprise-grade Azure environment.

A few key points:

•     Focuses only on OpenAI models (GPT family).
•     Integrated into other Microsoft products like Azure AI Studio and Microsoft Copilot.
•     Ideal for GPT-powered solutions such as customer service automation, content creation, code generation, and enterprise search.

If you need other foundation models (like Meta’s LLaMA, Mistral, or Google’s Gemini), that’s where Azure AI Foundry comes in.

Azure AI Studio (Formerly Azure OpenAI Studio)

In 2024, Microsoft evolved Azure OpenAI Studio into Azure AI Studio, expanding its scope beyond just OpenAI models.

This is your no-code/low-code playground for building AI-powered applications. With it, you can:

•     Visually design AI workflows
•     Combine OpenAI models with enterprise data
•     Create custom copilots and agents
•     Manage prompt engineering, orchestration, and deployment—all in one place

While Azure AI Studio is focused on building and orchestrating AI apps, it often works hand-in-hand with Azure AI Foundry for model management and governance.

Azure Machine Learning (Azure ML)

Azure Machine Learning is Microsoft’s powerhouse for custom model training—especially for structured/tabular data.

Unlike the prebuilt services, Azure ML is for teams who want to:

•     Build, train, and fine-tune their own models
•     Run large-scale experiments
•     Deploy models in controlled environments

It now integrates with Azure AI Foundry for better lifecycle management, compliance, and deployment across multiple teams.

Azure AI Foundry

Brand new in 2025, Azure AI Foundry is Microsoft’s answer to enterprise AI lifecycle and governance.

Here’s what makes it different:

•     Works with multiple model providers (OpenAI, Meta, Mistral, Google, and more)
•     Centralizes governance, compliance, and deployment pipelines
•     Integrates with Azure ML (training), Azure AI Studio (app building), and GitHub (CI/CD)
•     Ideal for organizations scaling AI across multiple teams and projects

If Azure OpenAI Service is your single-model, GPT-only toolbox, then Azure AI Foundry is your multi-model command center.
Final Thoughts – How These Services Work Together

You don’t have to pick just one. In fact, in many enterprise projects, they work best together:

•     Train your model in Azure ML
•     Manage & govern it in Azure AI Foundry
•     Build the workflow in Azure AI Studio
•     Integrate it into apps using Azure OpenAI or Azure AI Services

Microsoft’s AI ecosystem in 2025 is more powerful (and interconnected) than ever—once you know which tool does what, the possibilities are huge.