Title: Microsoft Copilot’s New Agents: Insider Tips How to Make Them Work for You
Resource URL: https://podcasts.apple.com/us/podcast/ep-492-microsoft-copilots-new-agents-insider-tips-how/id1683401861?i=1000701235426
Publication Date: 2025-03-28
Format Type: Podcast
Reading Time: 30 minutes
Contributors: Ray Smith;Jordan Wilson;
Source: Everyday AI Podcast (Apple Podcast)
Keywords: [Artificial Intelligence, Business Automation, Microsoft Copilot Studio, Deep Reasoning Agents, Agent Flows]
Job Profiles: Academic/Researcher;Machine Learning Engineer;Artificial Intelligence Engineer;Data Analyst;Chief Technology Officer (CTO);
Synopsis: In this episode of the Everyday AI podcast, host Jordan Wilson speaks with Google DeepMind's Ray Smith about Microsoft Copilot Studio’s new AI agents, including deep reasoning models and Agent Flows, and how businesses can leverage them today.
Takeaways: [Microsoft's new "Deep Reasoning" agents combine reinforcement learning with self-verification to automate complex tasks like report generation and business analysis., Agent Flows in Copilot Studio allow businesses to define deterministic workflows, ensuring reliable, repeatable outcomes alongside flexible AI reasoning., Natural language is becoming the primary "programming language" for building AI agents, lowering the barrier for non-technical users., Deep Reasoning agents can connect securely to enterprise data in Microsoft 365, enabling customized, dynamic outputs tailored to organizational knowledge., To succeed with AI agents, business leaders must prioritize hands-on experimentation with real business processes, not theoretical planning.]
Summary: Microsoft's Copilot Studio now offers powerful new tools for businesses to build AI agents more easily and securely. The introduction of Deep Reasoning agents leverages reinforcement learning models capable of self-analysis, enabling more sophisticated tasks such as financial reporting, lead research, and RFP generation. These agents integrate securely with Microsoft 365 enterprise data, allowing organizations to maintain strict access controls while enhancing their workflow automation.

Agent Flows, launching broadly at the end of March 2025, provide a new layer of deterministic automation within Copilot Studio. Businesses can combine flexible AI reasoning with guaranteed, repeatable process steps—helping balance innovation with operational reliability. Users can describe their desired automation in natural language, which the platform translates into actionable flows, making the technology accessible to non-technical professionals.

Microsoft envisions an "agentic transformation," where AI agents handle most routine work and humans oversee exception management, driving efficiency and freeing employees for more strategic tasks. Organizations are encouraged to dive directly into using the tools, starting small with practical use cases to build understanding and scale AI integration systematically.
Content: ## Introduction

In a week marked by rapid advancements in artificial intelligence, Microsoft unveiled significant updates to its Copilot Studio platform, introducing new AI agents designed to simplify complex workflows for business users. These enhancements promise to reduce technical barriers and enable organizations to harness AI more effectively across various functions.

## Microsoft Copilot Studio: An Overview

Copilot Studio is a low-code application framework that empowers users to build AI-driven agents without extensive programming knowledge. Accessible via copilotstudio.com, the platform offers a trial period and integrates with existing Microsoft 365 and Azure subscriptions. Organizations can also adopt a pay-as-you-go model through prepaid usage packs.

Key features of Copilot Studio include:

• Model selection and orchestration.  
• Integration with enterprise data sources and connectors.  
• Governance, security, and observability controls suitable for large organizations.

By abstracting underlying complexities, Copilot Studio enables business leaders and domain experts to describe desired outcomes in natural language and iteratively refine AI solutions.

## Major Announcements

### 1. Deep Reasoning Agent

Microsoft introduced a new class of AI models optimized for analytical tasks. These “deep reasoning” models employ reinforcement learning techniques that allow them to self-evaluate and refine their outputs. They excel in scenarios requiring verified results—such as code generation, research, and report creation—because their outputs can be programmatically validated.

Organizations can deploy deep reasoning agents to automate workflows previously reliant on multiple human checkpoints. For example:

• **Sales Development**: Automatically research and qualify leads by aggregating web data, internal documents, and customer profiles.  
• **Request for Proposals (RFPs)**: Ingest customer requirements from emails, generate complex project plans, and draft proposals with minimal human intervention.  
• **Financial Analysis**: Execute on-the-fly code scripts to perform inventory optimization, generate reports, and trigger downstream actions.

These agents become reusable building blocks for multi-step processes, facilitating more efficient decision-making and freeing human experts to focus on high-value tasks.

### 2. Agent Flows

Scheduled to roll out at the end of March, Agent Flows integrate deterministic robotic process automation (RPA) capabilities with Copilot Studio’s existing AI orchestration. By embedding Microsoft Power Automate components directly into the agent workflow, users gain fine-grained control over critical process steps that require predictable, repeatable execution.

Agent Flows support a hybrid approach:

• **Deterministic Steps**: Predefined automations and connectors that guarantee consistent behavior.  
• **Non-Deterministic Reasoning**: AI-driven decision points where the agent selects tools or paths dynamically.

Users simply describe desired outcomes in natural language; Copilot Studio then generates and assembles the necessary automations and prompts. This approach further lowers the barrier to entry, allowing business professionals to design sophisticated workflows without writing code.

## Business Use Cases and ROI

Enterprise customers have already deployed Copilot Studio across diverse functions:

• **Customer Engagement**: Accelerating lead qualification and proposal generation in sales.  
• **Finance Operations**: Automating invoice processing, risk analysis, and M&A due diligence.  
• **Research and Development**: Generating technical reports, market analyses, and product documentation.

Within three months, more than 400,000 agents were created by over 160,000 organizations, reflecting growing demand for AI-driven process automation. Companies report increased efficiency, faster response times, and enhanced capacity to scale operations.

## Implications for Human Roles

Rather than displacing employees, AI agents are poised to augment human expertise. Common patterns include:

1. **Delegation of Routine Tasks**  
   Agents handle repetitive, data-intensive work—such as data extraction and preliminary analysis—allowing staff to focus on strategy and exception management.  
2. **Human-in-the-Loop Oversight**  
   For high-risk or compliance-sensitive processes, humans review agent outputs before finalizing decisions.  
3. **Shift to Agent Management**  
   Teams evolve from executing tasks to orchestrating and supervising fleets of AI agents, ensuring governance, security, and performance.

## Getting Started: Practical Advice for Business Leaders

1. **Adopt an Experiential Approach**  
   Select a high-value use case and build a proof-of-concept agent. Experimentation accelerates organizational learning and uncovers hidden opportunities.  
2. **Break Processes into Modules**  
   Decompose end-to-end workflows into discrete steps—some suited for deep reasoning, others for RPA. Chain these agents together for comprehensive automation.  
3. **Leverage Natural Language**  
   Frame requirements and iteratively refine agents using plain English descriptions. Over time, the platform’s abstractions will handle model selection, code generation, and connector integration.  
4. **Ensure Governance**  
   Establish guidelines for data access, security labels, and exception handling. Monitor agent performance and maintain human oversight in critical areas.

## Conclusion

Microsoft’s latest Copilot Studio enhancements—Deep Reasoning Agents and Agent Flows—usher in a new era of accessible, enterprise-grade AI. By combining natural language interfaces with robust automation frameworks, organizations can streamline complex workflows, drive revenue growth, and reallocate human talent to higher-value activities. The key to success lies in hands-on experimentation, iterative refinement, and disciplined governance.

For more information and step-by-step guides, visit copilotstudio.com or consult Microsoft’s Azure AI documentation.