Leveraging Azure AI Services for Nonprofits
Nonprofits can harness the power of AI through Microsoft Azure's affordable and accessible AI services. Azure Cognitive Services, Azure Machine Learning, and Azure Bot Services offer a wide range of capabilities that can be utilized by nonprofits to streamline operations enhance decision-making and create innovative solutions. By leveraging these services, nonprofits can achieve greater efficiency, effectiveness, and impact without compromising financial constraints.Build, Deploy, & Manage AI with Azure AI Foundry
Microsoft's Unified AI Development Platform Imagine an Enterprise organization with multiple departments which need to create new AI solutions to streamline operations while boosting customer experience. Each has different objectives and goals they are trying to achieve with AI. Marketing wants to analyze customer engagement on social media, Finance aims to spot fraud, and Operations plans to predict when machines need repairs. Teams have different subscriptions, resource groups, storage, etc. per department. Resource management can be tedious to say the least while sharing data safely, with the added complexity of provisioning things accurately. That is where Azure AI Foundry comes in. Azure AI Foundry is a unified platform allowing organizations to have a centralized hub where they can manage their AI development with the tools and features they need. Nonprofits can now step into the world of AI and build their own solutions for their organization and the communities they serve. Azure AI Foundry is accessible to developers and beginners alike, making AI implementation cost-effective for organizations of any size. In this blog we will cover How you can get started with Azure AI Foundry. Before we begin, there are some prerequisites that need to be made before you start your journey. Prerequisites & Azure Role Based Access Control (RBAC) Acquiring an Azure Account Azure AI Foundry is integrated into Microsoft’s Azure cloud infrastructure. To use the platform, you will need an Azure Account. You need to be assigned the role of Owner or have your administrator assign you the appropriate role. You can learn more about Azure AI Foundry roles in the Role Comparison Between Foundry Projects and Hub Based Projects. Nonprofits can take advantage of Microsoft’s Nonprofit $2000 Azure Sponsorship Credit Subscription. You will need to be an approved participant of Microsoft’s Nonprofit Offers Program. To learn more about how you can get started please see the following blogs: Getting Signed Up with Microsoft Nonprofits Program | Microsoft Community Hub Claiming Azure Credits | Microsoft Community Hub Azure Role Based Access Control (RBAC) Access Control and identity management are crucial steps in safeguarding your sensitive data. Organizations that deal with global privacy compliance standards understand the necessity of securing and hardening their environment. Microsoft aims to empower clients with security tools and measures built in Azure to help secure access to their resources. One of these tools is Microsoft Entra ID (formerly known as Azure Active Directory) which applies built-in roles with limited access and permissions to resources based on their job function, known as Role Based Access Control (RBAC). This follows a security principle called The Principle of Least Privilege. For example, a Business Analyst may need access to Customer Relationship Management software (CRM) to record interactions with stakeholders, allocate budgets, and manage financial records. The Business Analyst would need administrative access related to worked performed. However, they would not need access to creating resources such as virtual machines since that is out of the scope of their role. This ensures security best practices to prevent access to highly sensitive data. Azure AI Foundry has roles designed for developers, managers, and users. By assigning specific roles, such as reader or manager, organizations can ensure that only authorized individuals can view or modify critical AI tools and data. Keep this in mind when granting access to users. Below is a comparison of the features and capabilities of the two project types within Azure AI Foundry: Foundry Project and Hub Based Project. Disclaimer: Some roles may limit functionality in the Azure AI Foundry portal. For example, if a user cannot create a compute instance, that option will not appear in the studio. This prevents access denied errors. Types of Projects Foundry Project Hub-based Project Built on Azure AI Foundry resource Agents Azure AI Foundry Models Azure AI Foundry API Agents Project files (upload and start experimenting) Project-level isolation of files and outputs Evaluations Playground Hosted on Azure AI Foundry Hub Agents (preview) Create if features are not available in Foundry project Azure AI Foundry Models (Connections) Azure AI Foundry API Agents (Connections) Project-level isolation of files and outputs Evaluations Playground Prompt flow Managed compute Azure Storage account & Azure Key Vault Role Comparison Between Foundry Project & Hub Based Project Foundry Project Azure AI User: Azure AI User This role grants reader access to AI projects, reader access to AI accounts, and data actions for an AI project. This role is automatically assigned to the user if they can assign roles. If not, this role must be granted by your subscription Owner or user with role assignment privileges. Azure AI Project Manager: Azure AI Project Manager This role lets you perform management actions on Azure AI Foundry projects, build and develop projects, and grants conditional assignment of the Azure AI User role to other user principles. Azure AI Account Owner: Azure AI Account Owner This role grants full access to managing AI projects, accounts, and grants conditional assignment of the Azure AI User role to other user principles. Hub-Based Project Owner: Full access to the hub, including the ability to manage and create new hubs and assign permissions. This role is automatically assigned to the hub creator Contributor: Users have full access to the hub, including the ability to create new hubs, but cannot manage hub permissions on the existing resource. Azure AI Administrator (preview): This role is automatically assigned to the system-assigned managed identity for the hub. The Azure AI Administrator role has the minimum permissions needed for the managed identity to perform its tasks. For more information, see Azure AI Administrator role (preview). Azure AI Developer: Perform all actions except create new hubs and manage the hub permissions. For example, users can create projects, compute, and connections. Users can assign permissions within their project. Users can interact with existing Azure AI resources such as Azure OpenAI, Azure AI Search, and Azure AI services. Azure AI Inference Deployment Operator: Perform all actions required to create a resource deployment within a resource group. Reader: Read only access to the hub. This role is automatically assigned to all project members within the hub. Playgrounds, Agents, & Models Oh My! Model Catalog Investing in AI can be expensive, from overhead to capital expenditure. Adoption and development can be costly for many organizations with tight budgets. Nonprofits that want to venture in AI development are met with the challenge of balancing budget with performance and navigating the ever-evolving AI landscape. Nonprofits need the ability to evaluate and test drive models before making the major investment to develop AI projects. Azure AI Foundry now makes it easy to compare models and benchmarks for the latest AI models. Choose from a comprehensive collection of models from Open AI, Meta, Mistral, Grok, Cohere, and more. Track your model's quota usage to stay within limits. Fine-tuned AI Models Create tailored experiences with fine-tuned AI models by utilizing base models from Azure AI Foundry and adapting your own data to create an experience to cater to your audience. For nonprofits and businesses alike, fine-tuned models offer a practical path to maximize impact without the need for intensive computational resources or expertise. Whether optimizing for customer support, document summarization, healthcare analysis, or content generation, fine-tuning ensures AI solutions are more effective and aligned to user needs. Playgrounds Playgrounds are a workspace where you can work on GPTs, Assistants, Real-time audio, Images, and Completions. Playgrounds are a great way to test and compare models before making a full commitment to adopting them. Built-in tools let you quickly benchmark and evaluate what works best with your needs. You can choose from a variety of the latest models from OpenAI and third-party vendors. Setup is made simple with just a few clicks by picking your model. Chat: A chat playground lets users work with AI chat models in real time. Assistants: The Assistants’ playground is designed for experimenting with AI-driven assistants tailored to a wide range of tasks. Real-time audio: The Real-time Audio playground provides an interactive space to experiment with advanced audio-based AI models. Images: The Images playground offers an intuitive environment for working with state-of-the-art image generation and analysis models. Completions: The Completions playground allows users to test text generation models by providing prompts and adjusting settings for tasks such as content creation, summarization, or code generation. As you can see, you have many options to choose from. Create agentic bots for customer interactions or develop a chatbot for end users using specific organizational knowledge such as FAQs and documents with citations. The sky is the limit, with Azure adding new features and capabilities to improve user experience. Developers can also get started with templates and use IDEs like Visual Studio and Visual Studio Code. Now, let us talk about how you can integrate your data to refine and improve your workflows. In the next section we will discuss how you can connect your data to your customized solutions. Connecting Data Sources Connecting your data storage to Azure AI Foundry’s playground assistants, fine-tuned models, batch pipelines, and evaluation workflows is direct and straightforward. You can link storage accounts, databases, Azure blob storage, uploaded files, and Azure AI Search to supply datasets for training, testing, or real-time use. Built-in connectors and APIs make integration simple, while role-based permissions control access. Data lineage and versioning help track and manage information, ensuring your assistants and models use accurate, reliable inputs before applying additional security and governance tools. Compatible Storage Types Azure Blob Storage Azure AI Search Azure Cosmo DB for Mongo DB Uploaded Files URL/ Web Address JSON Governance & Security Azure AI Foundry provides tools to ensure the security of projects. One such tool is Role Based Access Control (RBAC), which we spoke about early. However, Azure AI Foundry integrates a security framework designed to protect sensitive data and comply with industry standards. It employs a combination of tools, governance controls, and continuous monitoring to assist organizations in developing AI solutions securely. Users can set up controls like content filters and block lists. Security recommendations are available through Windows Defender XDR integration, offering protection against data leakage, data poisoning, jailbreaks, and credential theft. Additionally, compliance policies from Microsoft Purview help maintain security measures. Security & Governance Features Compliance Security Framework Private Endpoints & Network Isolation Role Based Access Control Guard rails & Controls Data Encryption Microsoft Purview Defender XDR Integration Taken together, robust governance and security features offer organizations peace of mind, ensuring that their AI projects are not only innovative but also responsibly managed and protected against emerging threats. As organizations scale their AI initiatives, understanding and managing resource usage becomes equally important. This is where quotas come into play, helping teams allocate resources efficiently and maintain optimal performance as they build and deploy AI solutions. Managing Token Quotas Azure AI Foundry provides comprehensive tools that empower teams to monitor and manage token quotas across a diverse range of model consumption patterns. Whether your workloads are categorized as Global standard, Global provisioned, Global batch, Data zone standard, Data zone provisioned, Data zone batch, standard, or Regional, the platform allows for granular visibility into resource allocation and consumption. This centralized tracking ensures that organizations can proactively identify usage bottlenecks, optimize deployment strategies, and stay within defined limits, all while supporting efficient scaling and sustaining high performance for their AI solutions. How to Get Started Get started by visiting Azure AI foundry at https://ai.azure.com. Begin leveraging Azure AI Foundry, organizations should first explore the platform’s intuitive interface and robust documentation, which offer step-by-step guidance for onboarding teams of any size. Users can discover a suite of developer SDKs, prebuilt templates, and ready-to-deploy chatbot solutions that expedite the setup process. Engaging with these resources enables teams to rapidly prototype, customize, and scale AI solutions according to their unique requirements. Additionally, organizations are encouraged to take advantage of the extensive educational content and support channels provided, ensuring a smooth transition from initial exploration to full-scale AI deployment. With these tools and resources at their fingertips, teams can confidently embark on their AI journey, transforming innovative ideas into impactful outcomes. Hyperlinks Introducing Azure AI Foundry - Everything you need for AI development Build your own copilot with Azure AI Studio (Part 1) | Microsoft Learn Role-based access control in Azure AI Foundry portal - Azure AI Foundry | Microsoft Learn QuickStart: Get started with Azure AI Foundry - Azure AI Foundry | Microsoft Learn How to configure a private link for an Azure AI Foundry hub - Azure AI Foundry | Microsoft Learn Azure OpenAI Service - Pricing | Microsoft AzureAzure Document Intelligence - How to Extract Data from PDFs and Scanned Files
Imagine this: your nonprofit receives dozens—maybe hundreds—of forms every month. Volunteer sign-ups, program applications, donation forms, surveys. Now imagine you could automatically extract the data from those documents, no matter the layout, and drop it neatly into a spreadsheet or database—with zero manual entry. That’s not a dream. It’s Azure Document Intelligence in action. Whether you're processing handwritten forms, structured PDFs, or invoices from partner organizations, Document Intelligence can turn them into actionable data in minutes. Let’s walk through what it is and exactly how to get started—no coding required. In 2025, Microsoft now offers two ways to work with this tool: the new Azure AI Studio (also known as Foundry) or the original Document Intelligence Studio. Both are currently available, but AI Studio is the direction Microsoft is heading. 📄 What Is Azure Document Intelligence? Azure Document Intelligence is a service that uses AI-powered optical character recognition (OCR) to: Analyze and extract text, tables, and key-value pairs from documents Understand form structure (even if layout varies) Turn scanned documents or PDFs into structured data You can use prebuilt models (like invoice or receipt recognition),or train a custom model to understand your own document types. 🛠️ How to Use Azure Document Intelligence to Read Forms ⚡ Option 1: Use the New Azure AI Studio (Recommended) Azure AI Studio (formerly Azure AI Foundry) is Microsoft’s unified interface for working with AI-powered services like Document Intelligence. This is the platform that will eventually replace Document Intelligence Studio. 🔹 Step 1: Go to Azure AI Studio Sign in with your Azure account. 👉 https://ai.azure.com Choose Build a solution → Document Intelligence. If it’s your first time, you’ll be prompted to create a new project. 🔹 Step 2: Set Up the Document Intelligence Resource Select your Azure subscription, region, and resource group. Name your project (e.g., volunteer-forms). You’ll be issued: An Endpoint URL An API key Note: Keep these for later—they’re required for API calls or Power Automate connections. 🔹 Step 3: Upload and Train Your Model Upload sample forms (PDFs or images). Label fields like name, email, and date. Train a custom model using at least 5 of more example situations. Test and view your results in structured format within the testing pane. 🔹 Step 4: Use the Data Export to Excel or JSON. Connect to Power Automate, Power Apps, or your CRM via API. Check out this blog to see more on the Azure AI Foundry and a video walkthrough of the platform Build, Deploy, & Manage AI with Azure AI Foundry | Microsoft Community Hub 🧭 Option 2: Use Document Intelligence Studio (Legacy Interface) Step 1: Set Up the Document Intelligence Resource in Azure Go to the Azure Portal. Click Create a resource. Search for Document Intelligence (formerly Form Recognizer) and select it. Click Create and fill out the basics: Subscription: Choose your nonprofit subscription. Resource group: Use an existing one or create a new one. Region: Choose the region closest to you. Name: Something like doc-intel-demo. Pricing tier: Choose Free F0 if you're testing (limited pages/month), or Standard if using your credits. Click Review + Create > Create. Step 2: Use the Document Intelligence Studio This is the visual, no-code interface for trying out Document Intelligence. Visit Document Intelligence Studio. Log in with your Azure account. Click Get started. On the left, click Models > Custom model > Build a model. Paste in your Endpoint and Key from the Azure portal. Choose Create project and fill in: Project name (e.g., VolunteerFormsModel) Storage container: You’ll need a Blob Storage account with your forms uploaded (see next step). Source: Select the folder with your form samples. Step 3: Upload Your Forms to Blob Storage In Azure, create a Storage Account if you don’t have one already. Go to Containers and create a new container (e.g., forms-training). Upload 5–10 sample forms of the same type. These can be PDFs, scans, or images. Make sure the forms are consistent in layout (for best results). In Document Intelligence Studio, link this container to your project. Step 4: Label the Forms Once your forms are uploaded, start labeling fields (like Name, Date, Email). The AI will try to guess some fields—confirm or correct them. Do this for 5+ documents to train the model. Click Train model once labeling is complete. Step 5: Test the Model After training, go to Test model. Upload a new, unlabeled form and run the model. Watch as it extracts structured data like: Name: Jane Doe Email: jane@example.org Program Interest: Youth Mentoring Review the output in JSON or table format. Step 6: Export or Use the Results You can: Export the data to Excel Connect via API to feed into a database or CRM Use Power Automate to automate workflows (like adding entries to SharePoint or sending confirmation emails) check out the blog below to see up the workflow ➡️Automate the Busywork: How Nonprofits Can Use Power Automate to Extract and Process Form Data | Microsoft Community Hub Real-World Nonprofit Use Cases Here’s how nonprofits are using Document Intelligence right now: Digitizing intake forms for case management Automatically processing volunteer applications Scanning paper surveys into Excel Extracting info from grant agreements or invoices Final Thoughts Azure Document Intelligence makes what used to be tedious—scanning and retyping forms—quick, intelligent, and scalable. Once set up, it can save your nonprofit hours of manual entry each week and reduce human error. ➡️Automate the Busywork: How Nonprofits Can Use Power Automate to Extract and Process Form Data | Microsoft Community Hub
Empowering Nonprofits with Copilot Actions in Microsoft 365 Copilot
Empowering Nonprofits with Copilot Actions in Microsoft 365 Copilot Nonprofits often face unique challenges, from managing limited resources to coordinating volunteers and engaging with donors. Microsoft 365 Copilot offers a powerful solution to streamline these processes through Copilot Actions. These AI-driven tools can automate repetitive tasks, enhance productivity, and allow nonprofit teams to focus on their mission. Here's how you can make the most of Copilot Actions in your nonprofit organization. Automate Routine Tasks One of the key benefits of Copilot Actions is the ability to automate everyday tasks. For example, you can set up actions to automatically summarize your most important action items at the end of each workday. This ensures that your team stays on top of their responsibilities without spending extra time on manual updates. Enhance Meeting Preparation Preparing for meetings can be time-consuming, especially when coordinating with multiple stakeholders. Copilot Actions can automate the preparation process by generating meeting agendas, summarizing previous discussions, and even suggesting relevant documents. This allows your team to focus on the content of the meeting rather than the logistics. Streamline Volunteer Coordination Managing volunteers is a critical aspect of nonprofit operations. Copilot Actions can help by automating volunteer scheduling, sending reminders, and tracking volunteer hours. This ensures that your volunteers are well-informed and engaged, leading to a more efficient and motivated team. Improve Donor Engagement Engaging with donors is essential for the sustainability of any nonprofit. Copilot Actions can automate donor communications, such as sending personalized thank-you notes, updating donor records, and generating reports on donation trends. This helps build stronger relationships with your donors and ensures that they feel valued and appreciated. Optimize Fundraising Campaigns Fundraising campaigns require careful planning and execution. Copilot Actions can assist by automating campaign tracking, generating performance reports, and suggesting improvements based on data analysis. This allows your team to focus on creative strategies and outreach efforts, rather than administrative tasks. Enhance Data Management Nonprofits often deal with large amounts of data, from donor information to program outcomes. Copilot Actions can automate data entry, update records, and generate insights from your data. This ensures that your data is accurate, up-to-date, and easily accessible for decision-making. Getting Started with Copilot Actions To start using Copilot Actions in Microsoft 365 Copilot, follow these steps: Identify Key Tasks: Determine which tasks in your organization can be automated to save time and improve efficiency. Set Up Actions: Use the Copilot Studio to create and configure actions based on your identified tasks. You can describe the actions in natural language or manually configure them. Monitor and Adjust: Regularly review the performance of your Copilot Actions and make adjustments as needed to ensure they continue to meet your organization's needs. Creating a New Action in Copilot Studio Here are the detailed steps to create a new action in Copilot Studio: Access Copilot Studio: Open Copilot Studio from the Microsoft 365 admin center. Select Agents: On the side navigation pane, select "Agents". Add New Action: Select the "Actions" tab and click on "+ Add action". Choose Action Type: A menu of available action types will appear. Select "New action" and choose the type of action you want to create (e.g., Conversational, Flow, Connector, Topic). Configure Action: A configuration window will appear. Set the basic configurations for the action, such as name, primary language, solution, and schema name. Create Action: Click "Create" to proceed. Your new action will be created and ready for further customization. Customizing and Testing the Action After creating the action, you can customize it further: Define Capabilities: Author the basic capabilities of the action, such as the operations it will perform and the responses it will generate. Test the Action: Use the test pane in Copilot Studio to validate the action and ensure it works as expected. Refine the Action: Make any necessary adjustments based on the test results to improve the action's performance and reliability. Publishing and Deploying Action Once the action is ready, you can publish and deploy it: Publish the Action: Publish the action to the Microsoft 365 admin center. Admin Approval: The tenant admin needs to approve the action for it to be available to users. Deploy the Action: Deploy the action securely using central administration, built-in security roles, and simple management across environments to maintain compliance and governance. By following these detailed steps, you can successfully create and deploy Copilot Actions in Microsoft 365 Copilot, enhancing your organization's productivity and efficiency. References: Extend Microsoft 365 Copilot or Copilot agents with flow actions (preview) - Microsoft Copilot Studio | Microsoft LearnExtract data from documents in Azure AI Foundry portal
In today's digital age, nonprofits are constantly seeking ways to streamline their operations, reduce costs, and maximize their impact. One powerful tool that can help achieve these goals is the Azure AI Foundry Portal, which offers advanced capabilities for extracting data from documents. This blog explores how nonprofits can leverage this technology to enhance their efficiency and effectiveness. Understanding Azure AI Foundry Portal Azure AI Foundry Portal is a comprehensive platform that provides a suite of AI-powered tools designed to automate and simplify data extraction from various types of documents. Whether it's invoices, receipts, forms, or reports, the portal uses machine learning and natural language processing (NLP) to accurately extract and organize information. Key Features of Azure AI Foundry Portal Automated Data Extraction: The portal can automatically identify and extract relevant data from documents, reducing the need for manual data entry and minimizing errors. Customizable Models: Users can train custom models to recognize specific document types and formats, ensuring high accuracy and relevance. Integration with Other Azure Services: The extracted data can be seamlessly integrated with other Azure services, such as Azure Cognitive Search and Azure Data Factory, for further processing and analysis. Scalability: The portal is designed to handle large volumes of documents, making it suitable for nonprofits of all sizes. Benefits for Nonprofits Nonprofits often deal with a significant amount of paperwork, from donor records and grant applications to financial reports and volunteer forms. By leveraging the Azure AI Foundry Portal, nonprofits can: Save Time and Resources: Automating data extraction frees up staff time, allowing them to focus on more strategic tasks. This is particularly valuable for nonprofits with limited resources. Improve Data Accuracy: Manual data entry is prone to errors, which can lead to costly mistakes. The AI-powered portal ensures that data is extracted accurately and consistently. Enhance Reporting and Compliance: Accurate data extraction facilitates better reporting and compliance with regulatory requirements. Nonprofits can easily generate reports and track key metrics. Boost Donor Engagement: By efficiently managing donor information, nonprofits can personalize their communication and engagement strategies, leading to stronger relationships and increased donations. Streamline Operations: The portal's integration capabilities allow nonprofits to create a seamless workflow, from data extraction to analysis and decision-making. Real-World Applications Consider a nonprofit organization that provides educational resources to underserved communities. By using the Azure AI Foundry Portal, the organization can automate the extraction of data from grant applications, donor records, and volunteer forms. This not only saves time but also ensures that the data is accurate and readily available for analysis. The organization can then use this data to identify trends, measure impact, and make informed decisions about resource allocation. Getting Started If you're a nonprofit looking to streamline your operations and maximize your impact, consider exploring the Azure AI Foundry Portal today. The future of efficient and effective data management is just a click away! Please claim your Azure credits first by following this article: Claiming Azure Credits | Microsoft Community Hub. Once the Azure credits have been approved, follow this step-by-step guide that allows you to explore Azure AI Foundry Portal today mslearn-ai-fundamentals. Conclusion The Azure AI Foundry Portal is a powerful tool that can transform the way nonprofits manage their data. By automating data extraction and integrating with other Azure services, nonprofits can save time, improve accuracy, and enhance their overall operations. As a result, they can focus more on their mission and make a greater impact in their communities.An Interactive Exercise: How AI Can Enhance Your Day-to-Day Tasks – A Mini Guide
With artificial intelligence transforming the way we work, integrating it into daily tasks can feel overwhelming. Many professionals struggle with time-consuming, repetitive activities that don’t require deep thinking—whether it’s summarizing meetings, generating reports, or managing emails. What if AI could help reclaim those hours so you can focus on more strategic, creative, or high-value work? This interactive exercise will guide you through identifying tasks that could benefit from AI, matching them to the right tools, and estimating the potential time savings. By the end, you’ll have a personalized AI productivity plan tailored to your workflow. Whether you’re new to AI or already exploring its capabilities, this process will help you take actionable steps toward working smarter, not harder. Let’s dive in! Step 1: Identify Repetitive or Time-Consuming Tasks Think about your daily and weekly responsibilities. What tasks take up too much of your time but don’t necessarily require deep thinking or creativity? 📝 Write down 3-5 tasks that: ✅ Are repetitive and routine (e.g., summarizing meetings, scheduling, data entry). ✅ Take significant time to complete. ✅ Could benefit from automation or AI assistance. 💡 Example: “I spend 30 minutes every morning summarizing industry news for my team.” Step 2: Find the Right AI Tools for Your Needs Now, let’s match those tasks to AI capabilities! Review your list and think about how AI could assist or automate each task. 🤖 AI-powered solutions to consider: 🔹 Copilot for Microsoft 365 → Drafts emails, generates reports, summarizes meetings. 🔹 Microsoft Designer → Creates visual content for presentations or marketing. 🔹 Power BI Smart Narratives → Generates instant data insights. 🔹 Microsoft Syntex → Automates document processing. 🔹 Azure AI Content Safety → Monitors workplace communication for compliance. 📌 Match your tasks to at least one AI tool that could help. 💡 Example: “Instead of manually summarizing news, I could use AI in Copilot or ChatGPT to generate a concise industry update in minutes.” Step 3: Calculate Your Time Savings If AI took over some of these tasks, how much time would you gain each week? ⏳ For each AI-assisted task, estimate: 🔹 Time currently spent per week 🔹 Time AI could save 🔹 What you could do with that extra time 💡 Example: “If AI summarizes news in 5 minutes instead of 30, that’s 2+ hours saved per week that I could use for strategy meetings.” Step 4: Test & Implement AI into Your Workflow Now, pick one task and commit to using AI to assist with it this week. 🎯 Your Action Plan: 1️⃣ Choose one AI-powered tool to explore. 2️⃣ Apply it to one of your repetitive tasks. 3️⃣ Track your results—did AI help? Was the output useful? 4️⃣ Reflect: What worked well? What adjustments do you need? 💡 Example: “This week, I’ll use Copilot to summarize meeting notes and see if it saves me time.” Step 5: Share & Reflect Your Findings Let’s take 2 minutes to discuss: 🗣 What’s one task you think AI could enhance in your role? 🔄 What AI tool do you want to try first? 📊 What’s one way you’ll track your AI-driven productivity improvements? 🔹 Bonus Challenge: Keep a log of your AI-powered enhancements over the next month and review the results! Outcome: A Personalized AI Productivity Plan By the end of this exercise, you’ll have: ✅ Identified tasks AI can assist with. ✅ Matched them to the right AI tools. ✅ Estimated your time savings. ✅ Committed to testing AI in your workflow. 💡 Final Thought: AI isn’t just about efficiency—it’s about reclaiming time for higher-value work. Start small, track your progress, and unlock AI’s full potential in your role! 🚀Harnessing the Power of Speech AI with Azure AI Foundry
In the ever-evolving world of artificial intelligence, speech technology stands out as a transformative tool that bridges the gap between humans and machines. Microsoft’s Azure AI Foundry portal offers a comprehensive suite of AI services, including powerful speech capabilities. Let's dive into how you can explore and leverage these features to enhance your projects. What is Azure AI Foundry? Azure AI Foundry is a platform designed to help developers and businesses create intelligent applications using a variety of AI services. It provides a centralized hub where you can access, manage, and deploy AI models, including those for speech recognition and synthesis. Key Features of Azure AI Speech Speech-to-Text: Azure AI Speech can transcribe spoken language into written text with high accuracy. This feature is invaluable for applications like meeting transcription, voice commands, and automated customer service. Text-to-Speech: Convert written text into natural-sounding speech. This capability is perfect for creating voice-enabled applications, audiobooks, and accessibility tools. Real-Time Transcription: The Speech Playground in Azure AI Foundry allows you to test live transcription capabilities on your own audio files without writing any code. This feature is ideal for quickly evaluating the performance of speech-to-text models. Expressive Voices: Browse a variety of humanlike voices to find the perfect match for your project. These voices can add a personal touch to your applications, making interactions more engaging and relatable. How to Get Started with Azure AI Speech Navigate to Azure AI Foundry: Open a browser tab and go to the Azure AI Foundry portal. Sign In: Use your account credentials to sign in. Create a Project: On the home page, select "Create a project." Projects in Azure AI Foundry help organize your work. Configure Project and Hub: You will see a generated project name. Depending on your previous hub creations, you will either see new Azure resources to be created or a drop-down list of existing hubs. Select "Create new hub," name your hub, and proceed. Resources Created Take note of the resources that are created: Azure AI services Azure AI hub Azure AI project Storage account Key vault Resource group After the resources are created, you will be brought to your project’s Overview page. Using AI Services Access AI Services: On your project's Overview page, select "AI Services" from the left-hand menu. 2. Select Speech: On the AI Services page, choose the speech tile to explore the Speech capabilities. 3. Test out the real-time transcription feature: Upload your audio files and see how Azure AI Speech transcribes them into text. This hands-on experience helps you understand the capabilities and performance of the service. 4. Transcription: Upload or record your audio files to see how Azure AI Speech transcribes them into text. 5. Deploy and Integrate: Once you’re satisfied with the performance, deploy your speech models to production. Integrate them into your applications to start leveraging the power of Azure AI Speech in real-world scenarios. Benefits of Using Azure AI Speech High Accuracy: Azure AI Speech offers state-of-the-art accuracy in speech recognition and synthesis, ensuring reliable performance for your applications. Scalability: Easily scale your speech applications to handle varying workloads, from small projects to enterprise-level deployments. Customization: Fine-tune models to meet the specific needs of your business, improving the relevance and effectiveness of speech interactions. Ease of Use: The intuitive interface and comprehensive documentation make it easy to get started, even for those new to AI and speech technologies. Conclusion Exploring speech capabilities in the Azure AI Foundry portal opens up a world of possibilities for creating intelligent, voice-enabled applications. Whether you’re looking to transcribe meetings, develop voice assistants, or enhance accessibility, Azure AI Speech provides the tools you need to succeed. Start your journey today and see how speech technology can transform your projects. To learn more about Azure AI Speech, please visit: Fundamentals of Azure AI Speech - Training | Microsoft Learn.Building Secure Software from the Ground Up: Why It Matters for Nonprofits
What Is the Secure Software Development Lifecycle (SSDLC)? The Secure Software Development Lifecycle (SSDLC) integrates security into every phase of the traditional Software Development Lifecycle (SDLC). Instead of treating security as a final step before software deployment, SSDLC ensures that security measures are embedded from day one. This approach reduces vulnerabilities and strengthens nonprofit organizations against cyber threats. Key Phases of SSDLC and Why They Matter Planning & Requirements Identify security risks before development begins: This involves understanding potential threats and vulnerabilities that could affect the software. Define compliance needs: Ensure that the software meets regulatory requirements such as GDPR, HIPAA, and donor data protection. Design Use secure architecture principles to mitigate risks: Design the software with security in mind, incorporating principles that reduce potential risks. Implement encryption, authentication, and access control measures: Ensure that data is protected through encryption, and that only authorized users can access the system. Development Follow secure coding best practices: Prevent vulnerabilities like SQL injection, cross-site scripting (XSS), and unauthorized access by adhering to secure coding standards. Use automated security scanning tools: Detect issues early in the development process by employing tools that automatically scan for security vulnerabilities. Testing Conduct penetration testing, security audits, and code reviews: Uncover weaknesses by thoroughly testing the software's security. Simulate cyberattacks to test software resilience: Ensure the software can withstand real-world attacks by simulating various cyber threats. Deployment & Maintenance Monitor for security threats and apply regular updates: Continuously watch for potential security issues and keep the software up-to-date with the latest patches. Conduct incident response drills: Prepare for potential breaches by regularly practicing how to respond to security incidents. How Nonprofits Can Implement SSDLC with the Right Tools Understanding SSDLC is one thing—putting it into practice effectively is another. Many nonprofits lack dedicated cybersecurity teams or technical expertise, making it difficult to integrate security throughout the development process. This is where Microsoft’s Security Development Lifecycle (SDL) comes in. Leveraging Microsoft’s Security Development Lifecycle (SDL) Practices Microsoft’s Security Development Lifecycle (SDL) is a structured approach that aligns with SSDLC principles, providing security best practices and tools to help organizations—including nonprofits—develop secure applications. Some of the key SDL practices that nonprofits should incorporate include: 🔹 Perform Security Design Review and Threat Modeling – Nonprofits often handle sensitive data, such as donor information and beneficiary details. Conducting thorough security design reviews and identifying potential security risks early in the development cycle through threat modeling helps protect this sensitive information and ensures compliance with regulations. 🔹 Require Use of Proven Security Features, Languages, and Frameworks – Nonprofits may have limited resources, so it's crucial to use reliable security features, programming languages, and frameworks that are known to minimize vulnerabilities. This ensures that the software is built on a secure foundation without requiring extensive custom security solutions. 🔹 Perform Security Testing – Regularly run comprehensive security tests, including penetration tests and vulnerability assessments, to identify and address security flaws. This practice is essential for nonprofits to maintain the trust of their donors and beneficiaries by ensuring that their data is secure. 🔹 Implement Security Monitoring and Response – Continuously monitor for security threats and have a robust incident response plan in place to address potential breaches. Nonprofits need to be prepared to quickly detect and effectively manage any security incidents to minimize the impact on their operations and stakeholders. 🔹 Provide Security Training – Educate and train staff on security best practices and the importance of maintaining a secure development lifecycle. Nonprofits often rely on volunteers and staff who may not have extensive technical backgrounds, so ongoing security training is crucial to prevent security breaches and ensure everyone understands their role in maintaining security. This list showcases some of the essential SDL practices that can greatly benefit nonprofits. For a comprehensive overview, please view the following resources: Microsoft Security Development Lifecycle Practices. Learn how Microsoft supports secure software development as part of a cybersecurity solution - Training | Microsoft Learn Microsoft Tools That Support Secure Development To help nonprofits implement SSDLC and SDL, Microsoft offers several security-focused tools that integrate directly into the software development process. ✔ Microsoft Defender for DevOps – Protects code repositories and CI/CD pipelines from security threats, ensuring security is embedded throughout the development lifecycle. ✔ Azure DevOps Security Tools – Integrates security checks into DevOps workflows with automated scanning for vulnerabilities in code, dependencies, and containerized applications. ✔ Microsoft Defender for Cloud – Provides real-time security monitoring, threat detection, and compliance management for cloud-based applications. This helps nonprofits maintain continuous security visibility across Azure and hybrid environments. ✔ Azure Key Vault – Secures application secrets, encryption keys, and certificates, preventing unauthorized access to sensitive credentials used in nonprofit applications. ✔ Azure Web Application Firewall (WAF) – Helps protect nonprofit web applications from common threats like SQL injection, cross-site scripting (XSS), and bot attacks by filtering and monitoring traffic. ✔ Azure Policy – Automates security compliance checks within Azure environments, ensuring nonprofit applications and services follow best security practices throughout their lifecycle. Bringing It All Together For nonprofits, cybersecurity isn’t just an IT issue—it’s a mission-critical priority. A data breach can compromise donor trust, expose sensitive beneficiary information, and disrupt critical operations. By integrating Microsoft’s SDL practices and security tools into the Secure Software Development Lifecycle (SSDLC), nonprofits can: ✅ Proactively reduce cybersecurity risks before they become major threats. ✅ Protect donor and beneficiary data from unauthorized access. ✅ Ensure compliance with data privacy regulations. ✅ Strengthen trust with stakeholders who rely on them. By leveraging Microsoft’s security tools, nonprofits can build safer, more resilient applications—even without large security teams. This blog discusses building applications and incorporating security from the very beginning phases of development. If you are a nonprofit with applications that you may not have the budget to rebuild from the ground up, you can learn about modernizing and upgrading the security for your legacy applications here: Modernizing Legacy Applications in your Nonprofit | Microsoft Community HubUnderstanding the Fundamentals of AI Concepts for Nonprofits
Artificial Intelligence (AI) has become a cornerstone of modern technology, driving innovation across various sectors. Nonprofits, too, can harness the power of AI to enhance their operations and amplify their impact. In this blog, we'll explore fundamental AI concepts, common AI workloads, Microsoft's Responsible AI policies, and the tools and services available through Azure AI, all tailored for the nonprofit sector. Understanding AI Workloads AI workloads refer to the different types of tasks that AI systems can perform. Here are some common AI workloads relevant to nonprofits: Machine Learning: This involves training a computer model to make predictions and draw conclusions from data. Nonprofits can use machine learning to predict donor behavior, optimize fundraising strategies, and analyze program outcomes. Computer Vision: This capability allows software to interpret the world visually through cameras, video, and images. Applications include identifying and tracking wildlife for conservation efforts or analyzing images to assess disaster damage. Natural Language Processing (NLP): NLP enables computers to understand and respond to human language. Nonprofits can use NLP for sentiment analysis of social media posts, language translation for multilingual communities, and developing conversational AI like chatbots for donor engagement. Anomaly Detection: This involves automatically detecting errors or unusual activity. It is useful for fraud detection in financial transactions, monitoring network security, and ensuring data integrity. Conversational AI: This refers to the capability of a software agent to engage in conversations with humans. Examples include chatbots and virtual assistants that can answer questions, provide recommendations, and perform tasks, enhancing donor and beneficiary interactions. Responsible AI Practices As AI technology continues to evolve, it is crucial to ensure it is developed and used responsibly. Microsoft's Responsible AI policies emphasize the importance of fairness, reliability, safety, privacy, security, inclusiveness, transparency, and accountability in AI systems. These principles guide the development and deployment of AI solutions to ensure they benefit everyone and do not cause harm. To learn more about Microsoft Responsible AI Practices click here: Empowering responsible AI practices | Microsoft AI Azure AI Services for Nonprofits Microsoft Azure offers a suite of AI services that enable nonprofits to build intelligent applications. Some key services include: Azure Machine Learning: A comprehensive platform for building, training, and deploying machine learning models. It supports a wide range of machine learning frameworks and tools, helping nonprofits analyze data and make informed decisions. To learn more or get started with Azure Machine Learning click here: Azure Machine Learning - ML as a Service | Microsoft Azure Azure AI Bot Service: A service for building conversational AI applications. It provides tools for creating, testing, and deploying chatbots that can interact with users through various channels, improving donor engagement and support services. To learn more or get started with Azure AI Bot Service click here: Azure AI Bot Service | Microsoft Azure Azure Cognitive Services: A collection of APIs that enable developers to add AI capabilities to their applications. These services include vision, speech, language, and decision-making APIs, which can be used for tasks like image recognition, language translation, and sentiment analysis. To learn more about the various Cognitive Service please click here: Azure AI Services – Using AI for Intelligent Apps | Microsoft Azure Conclusion AI has the potential to transform the nonprofit sector by enhancing efficiency, driving innovation, and providing valuable insights. By understanding AI workloads, adhering to responsible AI practices, and leveraging Azure AI services, nonprofits can unlock the full potential of AI to better serve their communities and achieve their missions. Embrace the power of AI to take your nonprofit organization to new heights and make a greater impact. For a deeper dive into the fundamental concepts of AI, please visit the module Fundamental AI Concepts. This resource will provide you with essential insights and a solid foundation to enhance your knowledge in the ever-evolving field of artificial intelligence.Scaling AI: Strategies for Transforming Your Nonprofit
Scaling AI in a nonprofit context involves integrating AI technologies across various functions to maximize benefits such as improved decision-making, increased productivity, and enhanced service delivery. This can help nonprofits better serve their communities and achieve their missions more effectively. Key Strategies for Scaling AI in Nonprofits 1. Develop a Clear AI Strategy: Align the AI strategy with the nonprofit's mission and goals. Identify specific AI use cases that can drive value, such as automating administrative tasks, improving donor management, or enhancing service delivery. Create a roadmap for implementation, detailing resources, timelines, and milestones. Microsoft Tools that can help: Azure AI: Helps in developing and implementing AI strategies aligned with organizational goals. Power BI: Assists in identifying and visualizing AI use cases and creating implementation roadmaps. 2. Invest in AI Infrastructure: Utilize scalable cloud platforms like Azure to support data processing, storage, and analysis. Leverage tools like Azure Machine Learning to develop and deploy AI models efficiently. Microsoft Tools that can help: Azure: Provides scalable cloud infrastructure for data processing and storage. Azure Machine Learning: Facilitates the development and deployment of AI models. 3. Foster a Data-Driven Culture: Promote data literacy within the organization and encourage staff to use data in decision-making processes. Provide training and resources on AI and data analytics to build a data-driven culture. Microsoft Tools that can help: Microsoft Learn: Offers training resources on AI and data analytics. Power BI: Enhances data literacy by providing tools for data visualization and analysis. 4. Leverage Pre-Built AI Solutions: Use pre-built AI solutions and services to accelerate the scaling process. For example, Azure Cognitive Services offers APIs for vision, speech, language, and decision-making that can be integrated into nonprofit applications without building models from scratch. Microsoft Tool that can help: Azure AI Services: Provides pre-built AI solutions for vision, speech, language, and decision-making. 5. Implement Governance and Ethical Guidelines: Establish governance and ethical guidelines to ensure responsible and transparent use of AI. Address concerns related to bias, privacy, and accountability by following frameworks like Microsoft's Responsible AI principles. Microsoft Tool that can help: Microsoft Responsible AI: Offers frameworks and guidelines for ethical AI use. Real-World Examples of Scaling AI in Nonprofits: Disaster Response: AI can improve efficiency in disaster response by automating data collection and analysis, enabling faster and more accurate decision-making. Education: Nonprofits focused on education can use AI to provide personalized support to students, such as automating responses to common inquiries and offering tailored learning resources. Fundraising: AI can enhance fundraising efforts by analyzing donor data to identify potential major donors and optimize fundraising campaigns. Conclusion Scaling AI in a nonprofit organization requires a strategic approach, robust infrastructure, and a data-driven culture. By developing a clear AI strategy, investing in the right tools and technologies, and fostering an environment that embraces data and AI, nonprofits can unlock the full potential of AI and drive significant impact. Embrace the power of AI to take your nonprofit organization to new heights and better serve your community. For more detailed information and a comprehensive guide on scaling AI in your organization, you can explore the Scale AI in your organization module on Microsoft Learn.
