Agentic AI security: Prompt injection and manipulation attacks
As AI apps and autonomous agents gain more reasoning and independence, they also open new pathways for adversarial attacks. Join this webinar and hear how the most critical risks are broken down—prompt injection, goal hijacking, and memory poisoning—and how they the impact real AI applications. Learn practical defenses your teams can implement today, including input validation, behavioral detection, and robust architectural patterns that keep agentic systems aligned and secure. Learn more and sign up to attend this webinar or watch the recording after. Agentic manipulation: Prompt injection, goal hijacking & memory poisoning | Microsoft Community HubLearn to maximize your productivity at the proMX Project Operations + AI Summit 2026
As organizations accelerate AI adoption across business applications, mastering how Microsoft Dynamics 365 solutions, Copilot, and agents work together is becoming a strategic priority. Fortunately, businesses no longer need to rely on speculation — they can gain practical insights with fellow industry professionals during a unique two-day event: On April 21-22, 2026, Microsoft and proMX will jointly host the fourth edition of proMX Project Operations Summit at the Microsoft office in Munich, but this time with an AI edge. The summit brings together Dynamics 365 customers and Microsoft and proMX experts to explore how AI is reshaping project delivery, resource management, and operational decision‑making across industries. On day one, participants will discover how Dynamics 365 Project Operations, Copilot, Project Online, proMX 365 PPM, and Contact Center can strategically transform business processes and drive organizational growth. On day two, they can explore the technical side of these solutions. Secure your spot! What to expect from the summit Expert-led, actionable insights Join interactive sessions led by Microsoft and proMX experts to learn practical AI and Dynamics 365 skills you can use right away. Inspiring keynotes Gain future-focused perspectives on Dynamics 365, Copilot, and AI to prepare your organization for what’s next. In between our special guests we have Microsoft's Rupa Mantravadi, Chief Product Officer, Dynamics 365 Project Operations, Rob Nehrbas, Head of AI Business Solutions, Archana Prasad, Worldwide FastTrack Leader for Project Operations, and Mathias Klaas, Partner Development Manager. Hands-on AI workshops Take part in workshops where Sebastian Sieber, Global Technology Director (proMX) and Microsoft MVP will show the newest AI features in Dynamics 365, giving you real-world experience with innovative tools. Connect with industry leaders Engage with experts through Q&A sessions, round tables, and personalized Connect Meetings for tailored guidance on your business needs. Real customer success stories Hear case studies from proMX customers who are already using Dynamics 365 solutions and learn proven strategies for successful digital transformation. Who should attend? This summit is tailored for business and IT decision-makers that are using Dynamics 365 solutions and want to drive more business impact with AI, but also for those who might be planning to move away from other project management solutions such as Project Online and need practical guidance grounded in real-life implementations. Date: Apr 21 & 22, 2026 | 2 -Days event Location: Microsoft Munich, Walter-Gropius Straße 5, Munich, Bavaria, DE, 80807 Ready to maximize your productivity? Register here.proMX Project Operations + AI Summit 2026
Ready to learn how you can turn your project challenges into business success with Dynamics 365 AI solutions? Join Microsoft and proMX on April 21st and 22nd at Microsoft Munich for the in-person proMX Project Operations + AI Summit 2026 – Turning data into productivity assets with Copilot + Agents in Dynamics 365 solutions. On DAY 1, discover how Dynamics 365 Project Operations, Copilot, Project Online, proMX 365 PPM, and Contact Center can strategically transform business processes and drive organizational growth. On DAY 2, we’ll take a deep dive into the technical side of these solutions. ✅Book a one-to-one slot with proMX, proMX customers or our Microsoft guests ✅ Explore our booths to talk to Microsoft MVPs and proMX experts ✅ Exchange ideas, project expertise, and more! Register now to secure your spot at this exclusive and free event: proMX Project Operations + AI Summit 2026 You still have questions? Feel free to contact us! Jelena Yaruchyk (Global Marketing Director) - Jelena.Yaruchyk@promx.net Kateryna Marchak (Marketing and Content Lead) - Kateryna.Marchak@promx.netBuilding an AI solution is just the first step - turning it into revenue is where real growth begins
As partners bring AI-powered apps and agents to market at record speed, many struggle with how to price, license, and operationalize their offers for long-term success. This article breaks down how to design monetization early and avoid common pitfalls when publishing on Microsoft Marketplace. Learn how the Marketplace Monetization Checklist helps SaaS and container offers establish secure licensing, effective pricing models, and scalable fulfillment. See how App Advisor translates guidance into action, and how AI Envisioning sessions help align teams on strategy before you build and publish. If you want Marketplace to become a predictable revenue engine—not just a distribution channel read the full article to learn how to monetize your AI apps and agents and drive sustainable growth. Read more: Monetize your AI apps and agents on Marketplace to realize growthLevel up your Python + AI skills with our complete series
We've just wrapped up our live series on Python + AI, a comprehensive nine-part journey diving deep into how to use generative AI models from Python. The series introduced multiple types of models, including LLMs, embedding models, and vision models. We dug into popular techniques like RAG, tool calling, and structured outputs. We assessed AI quality and safety using automated evaluations and red-teaming. Finally, we developed AI agents using popular Python agents frameworks and explored the new Model Context Protocol (MCP). To help you apply what you've learned, all of our code examples work with GitHub Models, a service that provides free models to every GitHub account holder for experimentation and education. Even if you missed the live series, you can still access all the material using the links below! If you're an instructor, feel free to use the slides and code examples in your own classes. If you're a Spanish speaker, check out the Spanish version of the series. Python + AI: Large Language Models 📺 Watch recording In this session, we explore Large Language Models (LLMs), the models that power ChatGPT and GitHub Copilot. We use Python to interact with LLMs using popular packages like the OpenAI SDK and LangChain. We experiment with prompt engineering and few-shot examples to improve outputs. We also demonstrate how to build a full-stack app powered by LLMs and explain the importance of concurrency and streaming for user-facing AI apps. Slides for this session Code repository with examples: python-openai-demos Python + AI: Vector embeddings 📺 Watch recording In our second session, we dive into a different type of model: the vector embedding model. A vector embedding is a way to encode text or images as an array of floating-point numbers. Vector embeddings enable similarity search across many types of content. In this session, we explore different vector embedding models, such as the OpenAI text-embedding-3 series, through both visualizations and Python code. We compare distance metrics, use quantization to reduce vector size, and experiment with multimodal embedding models. Slides for this session Code repository with examples: vector-embedding-demos Python + AI: Retrieval Augmented Generation 📺 Watch recording In our third session, we explore one of the most popular techniques used with LLMs: Retrieval Augmented Generation. RAG is an approach that provides context to the LLM, enabling it to deliver well-grounded answers for a particular domain. The RAG approach works with many types of data sources, including CSVs, webpages, documents, and databases. In this session, we walk through RAG flows in Python, starting with a simple flow and culminating in a full-stack RAG application based on Azure AI Search. Slides for this session Code repository with examples: python-openai-demos Python + AI: Vision models 📺 Watch recording Our fourth session is all about vision models! Vision models are LLMs that can accept both text and images, such as GPT-4o and GPT-4o mini. You can use these models for image captioning, data extraction, question answering, classification, and more! We use Python to send images to vision models, build a basic chat-with-images app, and create a multimodal search engine. Slides for this session Code repository with examples: openai-chat-vision-quickstart Python + AI: Structured outputs 📺 Watch recording In our fifth session, we discover how to get LLMs to output structured responses that adhere to a schema. In Python, all you need to do is define a Pydantic BaseModel to get validated output that perfectly meets your needs. We focus on the structured outputs mode available in OpenAI models, but you can use similar techniques with other model providers. Our examples demonstrate the many ways you can use structured responses, such as entity extraction, classification, and agentic workflows. Slides for this session Code repository with examples: python-openai-demos Python + AI: Quality and safety 📺 Watch recording This session covers a crucial topic: how to use AI safely and how to evaluate the quality of AI outputs. There are multiple mitigation layers when working with LLMs: the model itself, a safety system on top, the prompting and context, and the application user experience. We focus on Azure tools that make it easier to deploy safe AI systems into production. We demonstrate how to configure the Azure AI Content Safety system when working with Azure AI models and how to handle errors in Python code. Then we use the Azure AI Evaluation SDK to evaluate the safety and quality of output from your LLM. Slides for this session Code repository with examples: ai-quality-safety-demos Python + AI: Tool calling 📺 Watch recording In the final part of the series, we focus on the technologies needed to build AI agents, starting with the foundation: tool calling (also known as function calling). We define tool call specifications using both JSON schema and Python function definitions, then send these definitions to the LLM. We demonstrate how to properly handle tool call responses from LLMs, enable parallel tool calling, and iterate over multiple tool calls. Understanding tool calling is absolutely essential before diving into agents, so don't skip over this foundational session. Slides for this session Code repository with examples: python-openai-demos Python + AI: Agents 📺 Watch recording In the penultimate session, we build AI agents! We use Python AI agent frameworks such as the new agent-framework from Microsoft and the popular LangGraph framework. Our agents start simple and then increase in complexity, demonstrating different architectures such as multiple tools, supervisor patterns, graphs, and human-in-the-loop workflows. Slides for this session Code repository with examples: python-ai-agent-frameworks-demos Python + AI: Model Context Protocol 📺 Watch recording In the final session, we dive into the hottest technology of 2025: MCP (Model Context Protocol). This open protocol makes it easy to extend AI agents and chatbots with custom functionality, making them more powerful and flexible. We demonstrate how to use the Python FastMCP SDK to build an MCP server running locally and consume that server from chatbots like GitHub Copilot. Then we build our own MCP client to consume the server. Finally, we discover how easy it is to connect AI agent frameworks like LangGraph and Microsoft agent-framework to MCP servers. With great power comes great responsibility, so we briefly discuss the security risks that come with MCP, both as a user and as a developer. Slides for this session Code repository with examples: python-mcp-demoBringing AI fluency to every corner of the organization (even yours!)
Ashley Masters Hall joined Microsoft more than five years ago, just a month after earning her undergraduate degree. She’s currently a learning manager at Microsoft, focused on AI skilling for business pros. In this first blog post in a series of three, she shares her insightful and relatable perspective on AI fluency and skills for everyone in the organization. I was driving to an appointment recently, and I was reminded of the days when we used to print out directions at home and then try to follow them while driving. That was until GPS and later map apps came along. Suddenly, we had real-time guidance and rerouting from our phones. At first, we might have been reluctant to give up our familiar (though inefficient and unsafe) habit of wrangling printed directions behind the wheel. But once we experienced the speed and simplicity of GPS, there was no going back. AI is having its GPS moment. Two years ago, AI was this mysterious thing, a shiny object we weren’t sure we needed. Now, it’s the default way to navigate (and even orchestrate) work. Just like GPS didn’t replace driving, AI doesn’t replace thinking. It removes friction, gives us faster paths, and lets us focus on better outcomes. So the question isn’t, “Will AI change work?” It already has. The real question is, “Are you fluent enough to lead with it?” Regardless of your role or team, AI is likely already part of your world. In this blog post, the first in a series of three, I share practical tips, including six easy steps, that turn AI from a buzzword into your work GPS. What I mean by AI fluency (no jargon, I promise) Let me first define AI fluency. AI fluency is the degree of understanding and ability to interact effectively with generative AI. It’s recognizing when AI will add value and inspiration, plus having the skills to incorporate it into your workflows and tasks. AI skills are now foundational for everyone in every department. These skills not only help set you apart but also help keep you in the mix as work and roles evolve. We’ve seen a shift in the job market toward skills efficiency rather than work experience. In fact, according to the January 2025 LinkedIn Economic Graph Work Change Report: AI Is Coming to Work, “By 2030, 70% of the skills used in most jobs will change, with AI emerging as a catalyst.” Five years ago, when I was interviewing for jobs, my differentiators were my work experience and the Microsoft Certifications I had earned, which verified my expertise and abilities with Microsoft Office apps. But in interviews last year, most of the questions I got were about how I use AI today and how I’d apply it in the role. That’s the reality: AI fluency isn’t a future skill, it’s a “now skill.” It’s the differentiator that hiring managers seek. They want to know the real-world ways that you’re putting AI to work. Why this matters for your role (for every role, actually) If you’re wondering what AI looks like in your day-to-day work, you’re not alone. Let’s explore its practical applications for different teams and tasks. Marketing. If you’ve ever stared at a blank page trying to translate “We need a campaign” into an actual brief, AI can get you to a starting point fast. Maybe not the final answer, but a decent first draft that you can shape in your voice, for your audience and your goals. Sales and other customer-facing roles. AI is fantastic for meeting prep and follow-ups, like summarizing account notes, pulling themes from call transcripts (if they’re available), and drafting a clean recap email for you to personalize. The magic isn’t the email itself; it’s being able to more quickly and more clearly join in the conversation. Finance. Sometimes the hard part isn’t the analysis but the explanation. AI can help you draft the narrative: what moved, why, what questions a leader might ask, and what you should verify before you hit Send. Human resources (HR). AI can help turn good intentions into clear language, like job descriptions that match the role, onboarding plans that don’t overwhelm people, and summaries of themes you’re hearing so you can act on them before they get lost in the noise. Operations and program management. If your job involves herding context across multiple stakeholders, AI can help you turn chaos into structure, with action trackers, risk lists, crisp status updates, and decision logs you don’t have to rewrite every time. Legal/compliance (with the right guardrails). AI can help you triage, summarize, and spot inconsistencies. And then (pay close attention to this part) people do the actual review. Fluency includes knowing when to stop and bring a human into the loop. If you’re looking for a practical first step, regardless of your role, start with something familiar: email. Watch How to Prompt: Drafting Emails, and learn how Microsoft 365 Copilot can help you get to a first draft in seconds. One thing we shouldn’t gloss over here: AI can speed you up, but it doesn’t take responsibility for you. If you send it to a customer, put it in a deck, or use it to make a decision, you own it, so don’t forget the human layer. That’s the job. It doesn’t need to be scary, but it shouldn’t be overlooked. Get started with AI this week (an easy six-step plan that fits in your real life) If you do one thing after reading this post, don’t make it “Learn AI.” Make it “Pick one task you already do, and run it through a better workflow.” Choose one repeatable workflow. Think of something you do weekly, like meeting prep, a status update, a customer recap, a brief, or a summary. Decide what “better” means to you. Faster? Clearer? Fewer back-and-forth edits? More consistent output? Start with low-risk inputs. Use public info or your own notes while you get more comfortable with the tools. Give Microsoft 365 Copilot a task. Tell it the goal, context, source, and expectations, including the format you need, like bullets, a table, an email, or a memo. Check the work. Verify the facts, including names, numbers, and anything sensitive. Ask Copilot what might be missing. Save the good prompt. Keep it for future reference and reuse. No need to reinvent the wheel every time. Start strong with AI Skills Navigator When people ask me where to start, I have a simple answer: AI Skills Navigator, an agentic learning space that helps you build AI skills (even without a technical background) by bringing together AI-powered skilling experiences, credentials, and training. It makes learning feel approachable. Flexible formats, like short videos, AI‑generated podcasts, quick summaries, and guided skilling sessions, fit naturally into your day in the ways you learn best. This mix of formats helps you get started without feeling overwhelmed, stay engaged as priorities change, and keep up your momentum. AI doesn’t have to feel big. Make it small. Pick one task. Do it once with help. Keep what worked. Repeat it next week. And if you want an easy way to stay on track, start with (and keep coming back to) AI Skills Navigator. It’s like a learning “home base.” Assess where you are, choose a pathway by role or function, and build a habit of learning with small, steady steps. You may be surprised by how far a little AI fluency can take you.Monetize your AI apps and agents on Marketplace to realize growth
Ready to stop guessing how to monetize your offer? Skip right to App Advisor Software development companies are building faster than ever. But when it comes to sales, the key to monetization happens early. Monetization, packaging, and operational execution helps determine whether your AI solution becomes a growth engine on Microsoft Marketplace. New data reinforces the opportunity. According to Omdia research highlighted in Microsoft’s blog on the partner revenue opportunity: 88% of partners selling through Marketplace report revenue growth, 75% close deals faster, 69% secure larger deals, 60% agree Marketplace improved their deal structure. The Omdia study found that among partners that sell through Marketplace (compared to direct go-to-market and sales motions), they saw incredible gains with Marketplace. The opportunity is clear. The question is how to capture it consistently. How the AI app and agent monetization checklist helps The time to think about sales is when you’re building, not just when you hit “publish” on an offer. That’s why the Microsoft Marketplace Monetization Checklist for SaaS and Container Offers was created as part of the AI envisioning sessions. It gives your team a structured, practical framework to move from idea to revenue with confidence. A solution can offer immense value, but because monetization decisions are made too late, it can perform worse than expected. Pricing models, packaging tiers, metering accuracy, and subscription flows are often bolted on after architecture is finalized. The checklist changes that. It organizes monetization strategy around the five pillars of the Well-Architected Framework so that revenue design and technical design stay aligned. This checklist is also featured in App Advisor Build and Publish stage, so that you don’t miss a single step along the way. This ensures your offer is: Secure and enterprise-ready, Reliable across subscription lifecycle events, Cost-optimized for margin protection, Performance-aligned to your pricing model, Operationally structured for scale. Instead of guessing, you follow a clear path. Monetizing your offer the right way While designed for Saas and Azure Container offers, this checklist can be helpful for any offer. It guides you through key decisions that directly impact growth: Define your revenue model early during design, not after deployment, Model cost of goods sold against pricing tiers to protect margin, Package plans intentionally (Starter, Pro, Enterprise) to drive upsell, Implement secure licensing and Marketplace API validation to prevent revenue leakage, Optimize trial-to-paid conversion with structured upgrade paths. The checklist also reinforces operational execution with best practices for both SaaS and Azure Container offers. The result: an offer built for revenue, not just deployment. From build to publish to monetization on Microsoft Marketplace Building a great app or agent for your customers is the goal, but scaling your sales helps you grow. You’re not just publishing an offer, you’re building: A pricing strategy aligned to architecture, A subscription model aligned to customer value, An operational model aligned to Marketplace growth. This is how your company can turn Marketplace from a just listing platform into a revenue multiplier. Ready to monetize apps and agents on Microsoft Marketplace? You don’t have to guess how to grow. Use these resources to monetize your app or agent and get world-class Microsoft best practices, curated for you: Download the Marketplace Monetization Checklist, See the opportunity for your revenue growth in App Advisor, Watch sessions with experts by signing up for the AI Envisioning sessions.
Getting Started with AI and MS Copilot — French (FRANÇAIS)
Souhaitez-vous découvrir l’intelligence artificielle (IA) et Microsoft Copilot de manière pratique et ludique ? Nous vous invitons à participer à la séance intitulée « Introduction à l’IA et Microsoft Copilot », spécialement conçue pour les membres du corps enseignant qui débutent avec Microsoft Copilot. Cette séance vous permettra d’acquérir les notions fondamentales de l’IA générative, de comprendre comment formuler des requêtes efficaces (invites, ou « prompts ») et d’explorer comment appliquer ces outils en classe. Vous aurez accès à des supports pédagogiques que vous pourrez utiliser en classe et vous aurez l’occasion de mettre vos connaissances en pratique à travers 10 exercices. Rejoignez la réunion iciPartner Blog | Introducing Partner Marketing Center Pro
Across the ecosystem, partners are moving quickly to support customers on their frontier transformation journey. You’re building AI solutions, strengthening security, and modernizing data estates—and you need messaging that can keep pace with your delivery. To support your go-to-market efforts and make campaign execution more efficient and impactful, we are introducing a new partner marketing experience: Partner Marketing Center Pro. Partner Marketing Center Pro is an AI-driven hub that brings key marketing tools into one convenient, intuitive platform. Now, you can run end-to-end marketing campaigns powered by AI, with key features including asset customization, intelligent translation, comprehensive campaign reporting, and an AI assistant that supports you through each step. Partner Marketing Center Pro is developed with modern, AI-powered marketing capabilities designed for you to generate targeted demand, personalize outreach at scale, and move faster from launch to measurable results. Over the coming months, we will continue adding new features that strengthen targeting, streamline execution, and improve performance insights across your campaigns. Continue reading hereNew Microsoft Certified: AI Business Professional Certification
Do you use generative AI tools, like Researcher and Analyst in Microsoft 365 Copilot, to enhance your daily work, boost productivity, guide decisions, and drive business outcomes—without writing code or developing AI applications? Are you comfortable with AI fundamentals, prompt creation, and applying AI to real-world tasks? Do you produce professional content, summarize meetings, and collaborate across teams using Microsoft 365 apps? If this is your skill set, we have a new Microsoft Certification for you. The Microsoft Certified: AI Business Professional Certification validates your expertise in these skills. To earn this Certification, you need to pass Exam AB-730: AI Business Professional, currently in beta. This new Certification shows employers that you’re an AI-ready professional who can drive better outcomes in any business role, that you’re fluent in using AI in your day-to-day projects, including how to be more productive and creative as you work across Microsoft 365 apps, and that you understand how to use Copilot and agents to analyze data and automate tasks. Is this the right Certification for you? This Certification is designed for business professionals who want to apply AI tools to real business challenges. Whether you're in marketing, operations, project management, human resources, customer service, or another field, this Certification proves that you can unlock new levels of productivity and insight. As a candidate for the Certification, you should have a basic understanding of Microsoft 365 and should be comfortable navigating core apps, such as Outlook, Word, Microsoft Teams, PowerPoint, and Excel. You also need to be familiar with common business processes, including creating presentations, generating images, and managing documents. If you use generative AI tools, such as Microsoft Copilot, to draft emails, summarize documents, create presentations, or generate creative content, like images and text, this Certification could be a great fit for you. Ready to prove your skills? Take advantage of the discounted beta exam offer. The first 300 people who take Exam AB-730 (beta), on or before December 11, 2025, can get 80% off market price. To receive the discount, when you register for the exam and are prompted for payment, use code AB730Smore25. This is not a private access code. The seats are offered on a first-come, first-served basis. As noted, you must take the exam on or before December 11, 2025. Please note that this beta exam is not available in Turkey, Pakistan, India, or China. Get ready to take Exam AB-730 (beta): Review the Exam AB-730 (beta) exam page for details. The Exam AB-730 study guide explores key topics covered in the exam. Want even more in-depth, instructor-led training? Connect with Microsoft Training Services Partners in your area for in-person offerings. Need other preparation ideas? Check out Just How Does One Prepare for Beta Exams? Did you know that you can take any Microsoft Certification exam online? Taking your exam from home or the office can be more convenient and less stressful than traveling to a test center—especially when you know what to expect. To find out more, read Online proctored exams: What to expect and how to prepare. The rescore process starts on the day an exam goes live, and final scores for beta exams are released approximately 10 days after that. For details on the timing of beta exam rescoring and results, check out Creating high-quality exams: The path from beta to live. Ready to get started? Remember, the number of spots is limited to the first 300 candidates taking Exam AB-730 (beta) on or before December 11, 2025. Stay tuned for general availability of this Certification in February 2026. Learn more about Microsoft Credentials. Related announcements We recently migrated our subject matter expert (SME) database to LinkedIn. To be notified of beta exam availability or opportunities to help with the development of exam, assessment, or learning content, sign up today for the Microsoft Worldwide Learning SME Group for Credentials.
