Data Science Foundations

Data Science: Foundations for Strategic Decision-Making

Data Science for Business

Data Science Models & Their Business Applications

Storytelling with Data

Data Visualization and Storytelling: Making Data Speak

Cybersecurity

Cybersecurity: Securing the Modern Enterprise

Digital Transformation

Digital Leadership: Leading in a Digital World

Emerging Technologies

Emerging Technologies: Shaping the Future of Business

Creative Problem Solving

Design Thinking: Creative Approaches for Modern Challenges

Entrepreneurship

Entrepreneurship: Launching and Scaling New Ventures

Growth Strategy

Growth Strategy: Expanding Business 

Innovation Management

Innovation Management: Driving Creativity and Change

Budgeting & Planning

Budgeting and Planning: Financial Success for Business

Finance Foundations

Finance Fundamentals: Building a Strong Financial Foundation

Investment Analysis

Investment Analysis: Making Data-Driven Investment Choices

Complex Decision Making

Decision-Making: Navigating Complex Business Challenges

Leadership

Leadership Essentials: Developing Personal Leadership Skills

Negotiation & Influence

Negotiation: Achieving Win-Win Outcomes

Storytelling in Business

Business Storytelling: Persuading and Inspiring Audiences

Strategic Leadership

Strategic Leadership: Visionary Leadership for Growth

Strategic Planning

Strategic Planning: Creating Long-Term Success

Team Leadership

Team Leadership: Leading High-Performance Teams

Brand Marketing

Brand Management: Building and Sustaining Market Leadership

Growth Marketing

Marketing Analytics: Data-Driven Marketing for Results

Marketing Foundations

Marketing Fundamentals: Building and Implementing Strategies

Sales Leadership

Sales Leadership: Leading Teams to Achieve Excellence

Strategic Sales

Sales Strategy: Driving Growth Through Strategic Sales

Influence & Power

Influence and Power: Strategies for Professional Impact

Product Design

Product Design: Crafting Solutions for Customer Needs

Product Management

Product Management: Driving Success Across Product Lifecycles

Product Marketing

Product Marketing: Aligning Product with Market Needs

Project Mgmt Leadership

Project Leadership: Managing Teams for Successful Outcomes

Project Management

Project Management: Delivering Projects on Time and Budget

Technical Program Mgmt

Technical Program Management: Leading Complex Programs

Strategic Marketing

Strategic Marketing: Aligning Goals with Market Opportunities

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AI as Your Copilot (4 min)

Prompting: Speak So AI Listens (8 min)

Step inside The Moonshot Factory to see how teams prototype new concepts in hours, pinpoint the riskiest part of any idea, and turn bold thinking into real-world breakthroughs.

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Leadership and Decision-Making Under Pressure

Breakthrough Innovation Strategy

Scaling AI Strategy

Lead With AI

Lead With AI: Adapt, Implement & Transform Your Organization

Use AI to help create real, company-wide impact – grounded in Microsoft’s decades of experience turning breakthrough tech into trusted tools for teams of every size.


Advance your career in 15-20 hours with engaging video lessons, hands-on practice, and a capstone project. Some information relates to pre-released product which may be substantially modified before it’s commercially released. Microsoft makes no warranties, express or implied, with respect to the information provided here.

Microsoft

In responsible AI, accessibility means designing AI systems so they can be used by as many people as possible. If an AI system only works well for some users, its usefulness is limited.

Governments in the U.S. and Europe publish digital accessibility standards that organizations can use as a baseline.

These standards can help organizations design AI systems that work for people with different abilities, backgrounds, languages, and physical needs. Accessible AI tools do not depend on a specific ability, dialect, or device, and they offer alternative ways to complete tasks when needed.

Accessibility

An experimental AI feature in Microsoft Excel that lets Copilot take multistep actions—like building a budget template or timeline—directly inside a spreadsheet. 

To access experimental AI features such as Agent Mode in Excel, you typically need a supported Microsoft 365 Copilot license with Frontier Features enabled. Availability may vary based on your organization’s configuration and rollout status. 

Agent Mode in Excel

An agent is an AI tool that can take actions for you while you review or guide what it does.

Unlike chat tools that only answer questions, agents can connect to your data and systems to complete multistep tasks.

Agents make AI more useful by helping automate real work.

AI agent

The Change Management Playbook includes a statement on your approach to leading change and strategies for addressing challenges with AI adoption.  

Your change management plan will include:

**Approach statement**

* A short summary of how you’ll lead AI change (mindset, tone, priorities)

**Leadership challenges**

* Clear, specific barriers you anticipate with AI adoption

**Evidence or context for each challenge**

* Examples, team feedback, risks, or patterns that show why it matters

**Strategies to address each challenge**

* Practical actions you’ll take to address it (habits, structures, communication, training)

AI Change Management Playbook

AI Fundamentals: Think, Create, and Work Smarter is a MasterClass Certificate course that can help you build fluency in generative AI.

[Learn more here.](https://www.masterclass.com/certificates/ai-fundamentals-think-create-and-work-smarter)  

AI Fundamentals

An organization’s plan for ensuring AI is used safely, securely, and in alignment with its values. 

There are four steps: 

### AI Oversight Strategy

1. **Set your guiding principles.**

   Define what responsible AI means for you.

2. **Define who’s accountable.**

   Assign ownership and decision-making.

3. **Plan how you’ll monitor.**

   Decide what you’ll monitor and why.

4. **Communicate with transparency.**

   Share how AI is used and governed.
	 
	 ![](https://www.masterclass.com/course-images/attachments/xbe6vey0evehmxm20wj8flsq2hvw)

AI Oversight Strategy

An AI pilot project is the focused project you’ll plan for in the Lead With AI Certificate. 

It targets one specific workflow or business problem. It’s also the foundation for your capstone—the AI Transformation Plan.  
The course presents the AI pilot project as a starting point for broader AI use. 

The goal: Start small. Test it with your team. Measure the results. Then scale what works.

AI pilot project

Chat-based generative AI tools use large-language models (LLMs) to create new content based your prompts.

In this course, you’ll use Microsoft 365 Copilot (including features such as the Researcher Agent, where available) or another chat‑based AI tool of your choice to help evaluate and design your AI pilot project. 

If you don’t have Copilot, you may use an alternative chat‑based AI tool (examples include ChatGPT, Perplexity, Claude, and others), following your organization’s data‑handling and privacy policies.

**Reminder about data security:**

Avoid uploading personal, confidential, or sensitive work data to generative AI tools unless the tool is approved for that type of data and you’ve reviewed its data and privacy settings. 

Why? Free tools may not offer the same data protections as enterprise subscriptions. 

AI tools

AI transformation means using AI to change how an organization works and creates value—not just adding AI tools to existing processes, but by rethinking how work gets done across teams, systems, and workflows.

AI transformation is related to :glossary[ Frontier Transformation]{slug="frontier-transformation"}—Microsoft’s term for the next level of AI transformation. It goes beyond using individual AI tools to embedding AI across an entire organization.


AI transformation

Your AI Transformation Plan is the capstone portfolio you’ll build throughout this course and finalize in the last module. Each module contributes one element of the plan:

* AI Vision Statement 

* Guiding Principles

* Opportunity Proposal 

* AI Pilot Plan

* Estimated ROI

* Data Integration Blueprint

* AI Oversight Strategy

* AI Change Management Playbook

By the end of the course, you’ll review, refine, and submit all components as a single, strategic road map to advance the adoption of AI in your organization.

AI Transformation Plan

![](https://www.masterclass.com/course-images/attachments/39o2f86wsqt3go0pe8uam76xh60f)

**Chief Marketing Officer, Commercial Cloud & AI**

Alysa leads marketing for Microsoft’s Commercial Cloud and AI business, spanning product, solutions, and experience marketing teams across the globe. She’s reimagining marketing as a growth driver by combining AI personalization, intelligent workflows, and data-driven insights to deliver impact for customers and the industry.

Alysa Taylor

Analyst Agent can apply data‑analysis techniques similar to those used by data scientists. It allows you to review its steps and reasoning to validate the approach.

You may need a supported Microsoft 365 Copilot license to access the Analyst Agent, depending on your organization’s configuration.

If you don’t have access to Analyst, you can use another chat‑based AI tool of your choice (for example, free or premium versions of ChatGPT) to explore data, following your organization’s data‑handling and privacy policies.

Analyst Agent

![](https://www.masterclass.com/course-images/attachments/fzruuo2a9fdqvfwfo20xdd3ine8a)

**President, Azure Data**

With 20-plus years at Microsoft, Arun has led key data and analytics platforms like Azure and Microsoft Fabric. A former Silicon Valley entrepreneur and an alumni of the Stanford Graduate School of Business, he focuses on helping organizations build data-first applications and cultures.

Arun Ulag

Microsoft’s cloud computing platform that provides access to computing, storage, and services over the internet. Instead of running software on your own computers, Azure lets you access computing power, storage, and services over the internet—like renting a massive, superpowered data center.

Key AI services may include:

* Azure AI Foundry (development platform for custom AI apps)  
* Azure OpenAI Service (access to OpenAI models)  
* Azure Machine Learning (ML lifecycle management)  
* Azure AI Services (pre-built AI capabilities for vision, speech, language)

Azure 

![](https://www.masterclass.com/course-images/attachments/yx6dex1l35ngfm1wbc50bi6bq58i)

**Director, Microsoft 365 Copilot**

Callie leads global product marketing and launches for Microsoft 365 Copilot. She specializes in bringing AI to life through demos and real-world use cases, showing how Copilot helps people work smarter and unlock impact across everyday workflows.

Callie August

![](https://www.masterclass.com/course-images/attachments/aoc64giue65iink6uv2osgj33rl8 )

The capstone is your final assessment.

Instead of a test, you’ll show what you’ve learned by creating real-world deliverables.

Most modules end with a capstone assignment. Each one builds a key part of your final project.

Whenever you see the capstone image, know that you’re creating an element that will be part of your AI Transformation Plan. 

At the end of the course, you’ll submit your full plan as a portfolio of strategic documents for AI-powered feedback and grading.

Capstone

![]( https://www.masterclass.com/course-images/attachments/re5ug1v6fk6aotnem16gvc8rtu7y)

**Executive Vice President, Business Applications & Agents**

Charles drives product innovation in AI-powered business applications, low-code platforms, and autonomous agents at Microsoft. He oversees product and engineering for transformative technologies like Power Platform, Dynamics 365, and Agent Builder.

Charles Lamanna

Copilot Studio and Agent Builder enable you to create agents without traditional programming. They both are designed to help you create agents, but they serve different needs. 

## **Agent Builder**

**Agent Builder is a simple tool for quickly creating personal or small-team agents inside Microsoft 365 apps.**

Use Agent Builder to quickly create an agent for yourself or a small team.

Access Agent Builder within tools like Microsoft 365 Copilot and Teams.

## **Copilot Studio**

**Copilot Studio is a more advanced platform for building scalable agents with integrations and automation.**

Use Copilot Studio to build, customize, and manage more advanced agents with broader reach, multistep workflows, or custom integrations.

Access Copilot Studio from the Copilot Studio stand-alone web portal.

Copilot Studio and Agent Builder

Analytics dashboards are visual tools built into AI platforms that show you how your system is being used over time. 

They may be help you see which features people are and aren’t using. They can also help you detect unexpected usage of the tools. 

The following are some examples of products with built-in analytics:

* Copilot Studio   
* Power Platform Admin Center   
* Copilot Analytics (formerly Viva Insights)   
* Azure Monitor Insights   
* Microsoft Purview 

Dashboards

Data is the information that powers your AI. It’s what your AI reads, learns from, and draws on every time it generates a response or makes a recommendation. 

Some examples of common business data include: 

* Customer data – purchase history, contact records, support tickets  
* Sales and financial data – revenue, deal status, quarterly results  
* Employee data – HR records, performance reviews  
* Organizational knowledge – documents and processes in tools like SharePoint  
* External data – industry trends, competitor information

AI models need :glossary[quality]{slug="data-quality"}, relevant data to work well.

Data

The videos describe the following best practices for managing and using data at your organization: 

**Step 1: Anchor to business outcomes**

* Tie your data project to a specific business process and measurable result.

**Step 2: Unify your data** 

* Know where data lives, who has access, and bring your data together.

**Step 3: Connect data to daily workflows** 

* Integrate data into the tools people already use and tie insights to regular business processes.

**Step 4: Develop data literacy**

* Help teams understand and use data confidently through training and communities.

![](https://www.masterclass.com/course-images/attachments/y9ntl3ykqmrnortyhkoe6gez77j5)

Data best practices

A centralized storage system that holds large volumes of raw data from multiple sources in its original format so teams can analyze it and use it for AI.

Data lake

AI models need quality, relevant data to work well. These are the characteristics of high-quality data:

**It’s accurate.** The data reflects reality. It's correct and trustworthy.

**It’s unbiased.** The data doesn't over- or underrepresent certain groups or outcomes.

**It’s clean.** The data is free of errors, duplicates, and inconsistencies.

**It’s consistent.** The data uses the same definitions and formats across systems.

**It’s secure.** Only the right people have access to the right slices of data.

**It’s fresh.** The data is up-to-date and refreshed on a regular schedule.

**It’s available.** The data is accessible where and when people need it.

Data quality

A specialized Microsoft AI tool designed for healthcare professionals. It helps physicians document notes from patient visits, reducing manual administrative work.

Dragon Copilot

Model drift happens when an AI system’s results change after deployment because data or conditions have changed. The system may behave differently than planned, and people may use it in unintended ways.

Ongoing monitoring helps organizations detect drift and respond when performance changes.

Drift

Microsoft’s business applications for managing sales (customer relationship management, or CRM) and operations (enterprise resource planning, or ERP). It’s commonly used by sales, finance, and customer service teams to track customers, manage orders, and run your business operations.

May integrate with:

* Power Platform  
* Microsoft Fabric  
* Microsoft 365 Copilot

Dynamics 365

Training (or fine-tuning) an AI model involves providing it with large datasets so it can get better at recognizing the patterns, language, and context that matter most for its use case. 

The more relevant the data, the better the AI can get at giving useful, accurate responses—and the less likely it is to :glossary[hallucinate]{slug="hallucinations"}.


Fine-tuning

The flow of work means AI is embedded directly into the tools people use every day. It’s not in a separate app or tab, but available in the places where work happens: email, meetings, documents, and more.

Jared Spataro described it simply: AI comes to you, inside the tools you’re already in.

Flow of work

Microsoft’s term for an organization that uses AI in everyday work while keeping safety, trust, and reliability front and center.

Frontier Firm

Frontier Transformation is what Microsoft calls the next level of AI transformation. It goes beyond traditional AI efforts. It focuses on moving from small experiments to organization‑wide impact by rethinking how work gets done.

Frontier Transformation is built on three key ideas:

1. **AI in the flow of work**  
   AI is built into the tools people already use each day. This helps teams work more creatively, make decisions faster, and be more productive.  
     
2. **Ubiquitous innovation**  
   AI is combined with people’s skills across every role. This makes it easier for anyone to create, automate, and improve how work gets done—without disrupting the business.  
     
3. **Trust and observability at the core**  
   Strong security, governance, and oversight are built into every AI experience. This helps organizations protect their data, manage risk, and use AI responsibly at scale.

Frontier Transformation

Generative AI (GenAI) is a type of AI that creates new written, visual, or audio content in response to a prompt written in plain, conversational language. 

Generative AI doesn’t pull from a single source or simply search the internet. It uses :glossary[large language models (LLMs)]{slug="large-language-model-llm"} to generate responses based on patterns learned from massive amounts of existing text and data. 

You can use chat‑based generative AI tools (for example, Copilot, Claude, or ChatGPT) to create new content using GenAI. 

Note: Always follow your organization’s data‑handling and privacy policies when using  chat‑based generative AI tools. Don’t enter confidential or sensitive information unless the tool is approved for that type of data—the free versions of these tools are usually not.

Generative AI

A GitHub Copilot feature that can complete complex coding tasks from a simple prompt. It reviews your codebase, suggests changes across files, runs tests, and checks results. Rather than just responding to requests, it actively works toward your goal while you stay in control.

GitHub Copilot’s agent mode 

You can click highlighted text for more information about the terms or ideas in this course.

Glossary definitions

AI governance is how an organization guides and oversees its use of AI. It includes the rules, roles, and processes that shape how AI tools are chosen, used, and monitored.

Governance helps make sure AI use matches the organization’s values, risk standards, and legal duties.

It often covers areas like:  
• security  
• privacy  
• fairness  
• legal compliance  
• accountability

AI governance isn’t a one-time task. It continues as AI use grows and changes.

Many organizations create an AI governance group to lead this work. This group helps review AI tools, watch system performance, protect data, and keep leaders informed about risks and results.

Governance

Rules, policies, and controls designed to help keep AI systems operating as intended. They may include access limits, monitoring alerts, policies, and safety controls that help detect misuse—such as :glossary[prompt injection]{slug="prompt-injections"} attempts or unusual data activity.

Guardrails support safer AI use without unnecessarily limiting what AI can do.

Guardrails

When AI generates false information that sounds credible. 

AI can confidently make things up when it doesn’t have the right data or training.

This is a known limitation of AI, not a flaw. It can happen when the system lacks proper :glossary[training]{slug="fine-tuning"}, context, or :glossary[data]{slug="data"}.

Examples:

* AI might invent statistics, create fake references, or provide wrong answers that sound authoritative.   
* A loan AI might fabricate reasons for denying credit.   
* A customer service bot might cite nonexistent policies.

That’s why the step of checking facts for accuracy isn’t optional.

Hallucinations

![](https://www.masterclass.com/course-images/attachments/6q7fq4oo04hhkk57b7m2eg9doki5)

**Chief Marketing Officer, AI at Work, Microsoft**

Jared leads Microsoft’s AI at Work efforts, helping organizations use AI and agents to solve real business problems and drive new value. His team shapes the future of work while delivering AI features across Copilot and Microsoft’s core platforms.

Jared Spataro

![](https://www.masterclass.com/course-images/attachments/vnwzn2vn8l4v1ibdv827i5u87jzi)

**Corporate Vice President, Azure Marketing** 

Jessica leads how Azure is brought to market, shaping how customers and developers use cloud, data, and AI to modernize and scale. She champions Microsoft’s vision to help organizations become Frontier Firms using Azure to unlock innovation and growth.

Jessica Hawk

![](https://www.masterclass.com/course-images/attachments/dlxsw38mxcaevr69mo13oyni28x2)

**Chief Strategy and Transformation Officer, Microsoft**

Kathleen leads Microsoft’s corporate strategy and workforce transformation, shaping how the company evolves and operates in the Era of AI. An alumni of Harvard University and the Stanford Graduate School of Business, she previously served as the company’s Chief Human Resources Officer, where she championed the culture shift that helped make Microsoft one of the world’s most sought-after places to work.


Kathleen Hogan

The metrics you use to measure whether your AI project is making a difference. 

Good KPIs connect to something you’re already tracking—like cost, time, or revenue—so you can compare results before and after AI is introduced.

Key performance indicators (KPIs) 

Use AI to create real, company-wide impact – grounded in Microsoft’s decades of experience turning breakthrough tech into trusted tools for teams of every size.

AI adoption. Simplified.

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