Syksyn 2026 Tekniset ja myynnin Kumppanitunnit
Microsoftin tekniset ja myynnille suunnatut Kumppanitunnit järjestetään nykyään Microsoftin globaalilla Skilling Hub -sivustolla, josta ne ovat kätevästi saatavilla myöhemmin tallenteina materiaaleineen. Rekisteröidy Skilling Hub -portaaliin, josta löydät kaikki Microsoftin kumppanikoulutukset yhdessä paikassa eri kielillä tai tekstitettyinä. Rekisteröityessäsi voi valita ne kielet, kuten suomi, jollaista sisältöä haluat ensisijaisesti nähdä englannin kielisen koulutussisällön lisäksi. Kumppanitunti on joka toinen perjantai klo 10–11 järjestettävä Microsoftin kumppaniwebinaari, joka on tarkoitettu kaikille Microsoftin kumppaneille. Tekniset ja kaupalliset aiheet vuorottelevat ja olet tervetullut molempiin webinaareihin. Webinaareissa keskitymme Microsoftin ratkaisualueiden teknologioiden mielenkiintoisiin uutuuksiin, MAICPP-kumppaniohjelmaan, kumppanietuihin ja ratkaisumyyntiin. Microsoftin suomalaiset arkkitehdit, tuotepäälliköt, ratkaisumyyjät ja kumppanivastaavat ovat poimineet kiinnostavia ja hyödyllisiä aiheita, joita he vuorollaan esittelevät. Syksyn 2026 ohjelma Alla ovat suunnitellut päivät ja teemat Syksylle 2026, joiden tarkka aihe päivitetään aina lähempänä esityspäivää tälle sivulle. 18.9. Kaupallinen Kumppanitunti: Partner START FY27 - webinaari Rekisteröidy mukaan tästä: Partner START FY27 Kickoff - webinaari | Microsoft Partner Skilling Hub Etkö päässyt mukaan START FY27 Kickoff -tapahtumaan? Webinaarissa saat kattavan katsauksen tapahtumassa käsiteltyihin FY27: n liiketoimintamahdollisuuksiin, strategisiin painopisteisiin sekä Microsoftin kumppaneille suunnattuihin ohjelmiin ja resursseihin. Puhujat: Kalle Saarikannas, Liiketoimintajohtaja, AI Business Solutions Vibha Deshpande & Teemu Lainiola, Liiketoimintajohtajat, Cloud & AI Platforms Mikael Winqvist, Liiketoimintajohtaja, Security Mereta Laukkanen, Sr Partner Development Manager Jonna Kaarlenkaski, Partner Development Manager Intern Jonna Fred-Jokela, Sr Solution Engineer Manager 25.9. Kaupallinen Kumppanitunti: Onko julkisen pilven suvereniteetti riittävä huomioiden sen kaikki hyödyt? Rekisteröitymislinkki päivittyy tähän Euroopan unioni valmistelee uusia pilvi- ja tekoälyinfrastruktuuria koskevia linjauksia. Samanaikaisesti organisaatiot pohtivat, miten digitaalinen suvereniteetti, tekoälyn käyttöönotto, kyberturvallisuus ja sääntelyvaatimukset voidaan sovittaa yhteen käytännössä. Tervetuloa ajankohtaiseen webinaariin, jossa tarkastelemme Euroopan muuttuvaa pilviympäristöä ja mitä digitaalinen suvereniteetti tarkoittaa suomalaisille organisaatioille käytännössä. Lisäksi kerromme viimeisimmät tilannetiedot pilvipalveluiden kvanttiturvallisuuden ja Suomen datakeskushankkeiden osalta. Puhujat: Juha Karppinen, National Technology Officer, Microsoft Timo Salminen, Partner Solution Architect, Microsoft Niko Hiltunen, IAMCP 2.10. Tekninen Kumppanitunti: Copilot Cowork: Copilot Credits ja kustannusten hallinta Rekisteröitymislinkki päivittyy tähän Tässä teknisessä kumppanitunnissa käymme läpi Copilot Coworkin toimintamallin, kulutuksen seurannan sekä kustannusten hallinnan. Lisäksi tarkastelemme, millaisia mahdollisuuksia kulutuspohjainen AI luo kumppaneiden palveluliiketoiminnalle. Puhujat: Henri Nevalainen, Microsoft 16.10. Kaupallinen Kumppanitunti: Rekisteröitymislinkki päivittyy tähän Puhujat: 30.10. Tekninen Kumppanitunti: Rekisteröitymislinkki päivittyy tähän Puhujat: 6.11. Tekninen Kumppanitunti: Rekisteröitymislinkki päivittyy tähän Puhujat: 20.11. Kaupallinen Kumppanitunti: Rekisteröitymislinkki päivittyy tähän Puhujat: 4.12. Kaupallinen Kumppanitunti: Rekisteröitymislinkki päivittyy tähän Puhujat: 18.12. Tekninen Kumppanitunti: Agentit Azuressa Rekisteröitymislinkki päivittyy tähän Azure Copilot pitää sisällään uusia palveluiden elinkaarenhallintaan liittyviä agentteja. Tule kuulemaan, miten voit hyödyntää näitä omissa palveluissasi! Puhujat: Timo Salminen, Partner Solution Architect, MicrosoftPartner Blog | FY27 is the year to execute on AI: A starting point for Azure partners
FY27 is the year to execute on AI. For Azure partners, that means moving more customer AI initiatives into production, modernizing the cloud, data, application, security, and governance foundations they depend on, and connecting those investments to outcomes customers can measure. Across the partner ecosystem, you are starting from different places. Some partners are already scaling AI solutions in production. Others are modernizing legacy environments, unifying data, or strengthening security and governance so customers are ready for what comes next. The opportunity is to understand where each customer is today and create a practical path forward. Microsoft has aligned FY27 customer conversations, go-to-market guidance, incentives, skilling, and partner resources around that goal. The focus is less on starting with a product and more on starting with what the customer is trying to achieve. In July, MCAPS Start for Partners and the Microsoft Partner FY27 GTM Kickoff laid out that direction. If you missed the events or want to revisit a specific topic, the content is available on demand: Watch MCAPS Start for Partners on demand Explore the Microsoft Partner FY27 GTM Kickoff The more important question now is what you do with that guidance. Turn customer priorities into Core and Frontier conversations Customers rarely begin by asking for a portfolio of technologies. They begin with a challenge, an ambition, or an outcome: modernize an aging application, make fragmented data useful, strengthen security, improve employee productivity, automate a process, or create a new customer experience. That is the starting point for FY27. Core conversations establish the foundation customers need to become AI-ready. Depending on the customer, that can mean modernizing infrastructure and applications, bringing data together on a governed platform, improving security, or establishing the controls required to operate AI with confidence. Continue reading hereBeyond Tokens: Rethinking AI Economics with Microsoft Foundry
Beyond Tokens: Rethinking AI Economics with Microsoft Foundry From the cost of intelligence to the value of outcomes Enterprise AI has an accounting problem. Executives expect agentic AI to return roughly 171% on investment, according to one widely cited survey. Yet McKinsey finds only about 39% of organizations can attribute any earnings impact to AI at all. Both numbers can be true at once — because the gap between them is not a technology gap. It is a measurement gap. For the first few years of generative AI, one number dominated the economics conversation: tokens. How many tokens did a model consume? What was the cost per million tokens? Could a smaller model perform the same task? Those questions mattered when enterprises were experimenting with AI. They are no longer enough as AI moves into production. An enterprise agent doesn't simply consume tokens. It reasons, retrieves context, invokes tools, calls APIs, verifies its work, retries unsuccessful actions and sometimes escalates exceptions to humans. The model call might cost pennies. The business outcome could cost considerably more. Which leads to an increasingly important question: What is the right economic unit for intelligence? From AI experimentation to economic accountability The first wave of enterprise AI was about possibility: Can AI do this? The next wave is about production, as AI becomes embedded in software engineering, customer service, finance, healthcare and supply chains. And production changes the question: Should AI do this and at what cost? Microsoft has moved decisively onto this ground. In August 2026, the Microsoft Foundry team launched its Economics of Agent Optimization series, arguing that "tokens have become the new unit of technology spend" and that AI should be run as a managed investment system. On the latest earnings call, Satya Nadella described Microsoft's objective as "advancing the frontier on the cost-to-outcome curve, ensuring every customer can turn tokens into business results." The discipline is going mainstream too: 98% of FinOps teams now manage AI spend, up from 31% two years ago. Microsoft's series is largely about the numerator of that curve - making every request, agent and dollar more efficient. This article is about the denominator: what an outcome is, what it truly costs, and what it is worth. The evolution of Microsoft Foundry reflects the same shift. At Build 2026, Microsoft expanded the conversation beyond building agents toward tracing behavior, evaluating quality, monitoring production performance, optimizing agents and connecting their operation to ROI. Think of the progression as: Trace → Evaluate → Monitor → Optimize → ROI This is more than a technology roadmap. It represents a shift from observing AI as technology to managing AI as an economic asset. Tokens became the unit of spend. They were never the unit of value. Consider two AI agents handling the same customer-service workflow. Agent A costs $0.08 per interaction. Agent B costs $0.20. Agent A appears cheaper. But suppose Agent A successfully resolves only 55% of cases, while Agent B resolves 90%. The remainder require retries, additional reasoning or human intervention. Which agent is actually cheaper? The inexpensive interaction may produce the expensive resolution. This illustrates a fundamental problem: We often measure AI where it is consumed rather than where value is created. Tokens are a unit of consumption. Businesses operate in outcomes. A customer-service leader cares about issues resolved. An engineering leader cares about high-quality software reaching production. A finance leader cares about reconciliations completed accurately. The economic denominator needs to move closer to the business. The AI Economic Ladder I think of this evolution as an AI Economic Ladder: Tokens → Interactions → Tasks → Outcomes → Value Each step moves measurement closer to what the enterprise actually cares about. At the token level: What intelligence did we consume? At the interaction level: What did each AI run cost? At the task level: What did it cost to complete the work? At the outcome level: What did a successful result cost? At the value level: Was the outcome worth creating? An AI system can become more efficient at every technical metric while creating little economic value. Conversely, an expensive AI workflow could be extraordinarily valuable if it prevents revenue leakage, reduces operational risk or accelerates a critical business process. The objective isn't cheaper AI. It is better economics. Not every completed task is a successful outcome There is another complication. If an agent completes a workflow, should we count it as a successful outcome? Not necessarily. A meaningful outcome needs three characteristics: Completed. Quality-gated. Attributable. It must reach its intended end state, meet an explicit standard for quality, accuracy, safety or business acceptability, and be attributable to the agent or workflow that produced it. That gives us a more meaningful measure: Cost per Successful Outcome = Fully Loaded AI Workflow Cost / Completed, Quality-Gated, Attributable Outcomes The denominator becomes real only when named in business language: cost per prior authorization resolved in healthcare, per pull request triaged and tested in engineering, per disputed invoice reconciled in finance operations. If you cannot name the outcome in a sentence the process owner recognizes, you are not ready to measure it. The quality gate matters. With AI, "the system ran successfully" and "the system produced a good outcome" are not the same thing. Microsoft Foundry's tracing and evaluation capabilities become economically important for precisely this reason. Evaluation isn't merely quality control. It helps determine what gets counted as value. What does an AI outcome really cost? The true economic footprint goes far beyond inference: Model + Reasoning + Grounding + Tools + Orchestration + Infrastructure + Retries + Evaluation + Governance + Human Intervention Human intervention is particularly easy to overlook. Every time someone must review, correct, approve or recover an AI-generated outcome, the economics change. The same applies to verification. An agent reaching an acceptable result in three steps has different economics from one requiring fifteen steps and multiple retries. And verification is not a rounding error — it is the bulk of the bill. McKinsey's 2026 analysis of production agentic workflows found roughly 60% of an agentic task's cost is tied to refining answers — checking, repairing, re-verifying — not generating the initial response. Most of what you pay for is not intelligence. It is assurance. This means quality and economics are connected. The quality bar you set influences the cost you pay. The challenge isn't simply minimizing consumption. It is finding the right balance between quality, cost, speed and risk. Cost per outcome is only half the equation Now imagine two agents. Both cost $5 per successful outcome. One saves an employee ten minutes of administrative work. The other prevents $500 in revenue leakage. Their cost efficiency is identical. Their economics clearly aren't. So we need to move another step up the ladder: from Cost per Outcome to Value per Outcome. The question isn't only how cheaply AI can complete the work. It is: How much economic value does this outcome create relative to the intelligence required to produce it? Now the CIO, CFO, CAIO and business leader have a common conversation. Give every outcome an Intelligence Budget Not every problem deserves the smartest model available. Classifying an email may require relatively little intelligence. Resolving a complicated customer complaint may justify more context and reasoning. Assessing the risks in a multimillion-dollar contract may justify sophisticated reasoning, multiple validations and human review. Every business outcome therefore has an economically rational amount of intelligence worth spending on it. Call it an Intelligence Budget. This changes the architecture question from which model should we standardize on, to: What combination of model, reasoning, context, tools and human judgment does this outcome deserve? This is where Microsoft Foundry's model router becomes interesting. Individual requests can be dynamically routed so simpler work doesn't consume the same model resources as complex reasoning. If the Intelligence Budget is the economic principle, intelligent routing is one way of operationalizing it. The future enterprise AI architecture won't be about one model doing everything. It will route intelligence according to the economics, quality and risk of the outcome. Making AI economics observable None of this works without visibility. An AI system can be technically healthy and economically unhealthy — responsive and error-free while repeatedly choosing inefficient reasoning paths, invoking unnecessary tools or producing outputs requiring expensive human correction. AI economics and AI observability are becoming inseparable. Microsoft Foundry increasingly connects these disciplines. Tracing shows what an agent did. Evaluation determines whether it met required criteria. Observability helps monitor production behavior. Agent optimizer can test improvements across prompts, skills and models. Microsoft's emerging ROI capabilities take the next step by connecting operating costs with measures such as task completion, time saved and cost efficiency. Attribution is the bridge to the finance conversation. Teams place Azure API Management in front of Foundry endpoints as an AI Gateway, stream token telemetry into Application Insights, and use Entra Agent ID to give every agent run a discrete identity that maps cost to its cost center. Microsoft Agent 365 extends the discipline tenant-wide — spending policies, budget caps and departmental chargeback across Microsoft and third-party agents. Together, they create something enterprises have historically lacked: A feedback loop between how intelligence is consumed and what that intelligence accomplishes. The paradox of cheaper intelligence There is another reason AI economics will become more important as models get cheaper. The Jevons paradox suggests that when technology makes a resource cheaper and more efficient, total consumption can actually increase. AI may experience the same effect. Cheaper intelligence enables more agents, more reasoning and more workflows that were previously uneconomic. So we could see cost per unit of intelligence fall while total intelligence consumed rises. Cheaper AI may therefore produce larger AI bills. That isn't necessarily bad — provided value grows faster than consumption. The objective isn't minimum AI consumption. It is maximum economic value from AI consumption. From workload economics to portfolio economics As AI scales, economics becomes a capital-allocation question. I see three levels. Workload Economics: Is this AI system running efficiently? Outcome Economics: Is it producing quality outcomes economically? Portfolio Economics: Where should we put our next AI dollar? That final question will become increasingly important. An enterprise with hundreds of AI initiatives shouldn't assume every one deserves continued investment. Some should scale. Some need optimization. Some should be redesigned or consolidated. And some should be stopped. The ability to experiment cheaply created the first explosion of enterprise AI. The discipline to allocate capital intelligently will determine what scales. Who owns AI economics? Once an agent becomes part of how work gets done, its economics cannot remain purely an IT metric. The business understands the value of the outcome. Technology understands the architecture and optimization levers. Finance brings economic discipline and comparability. That suggests a shared model: Business owns the outcome. Technology owns the optimization levers. Finance owns the economic discipline. AI economics ultimately isn't just a technology-cost conversation. It is a business-performance and capital-allocation conversation. From abundant intelligence to intelligent economics We are entering an era where intelligence is becoming an increasingly abundant, programmable and variable-cost resource. Microsoft Foundry and the broader Microsoft AI stack are making it easier to build, evaluate, observe, optimize and govern that intelligence. But abundant intelligence does not guarantee abundant value. Enterprises still need to decide where AI belongs, how much intelligence each problem deserves, what defines a successful outcome, when humans should remain involved and which AI investments deserve more capital. The winners won't necessarily use the cheapest models. They won't consume the fewest tokens. And they won't be the organizations that build the most agents. They will become exceptionally good at moving up the AI Economic Ladder: from consumption, to outcomes, to value. Because the next era of AI won't be won by organizations that buy intelligence most cheaply. It will be won by those that convert intelligence into value most efficiently. Where to start: the first 90 days Define the denominator for your top three agents — what counts as done, what quality gate applies, who signs off. Instrument attribution — Azure API Management as an AI Gateway, token telemetry to Application Insights, Entra Agent ID on every run. Wire evaluations into the cost pipeline so only quality-gated outcomes count. Set Intelligence Budgets — model router per request, agent optimizer against your evaluators, Agent 365 policies as circuit breakers. Stand up a joint monthly review — business, technology and finance on one dashboard: outcomes delivered, cost per outcome, value per outcome. Frequently asked questions What is Cost per Successful Outcome in enterprise AI? The fully loaded cost of an AI workload divided by outputs that were completed, quality-gated and attributable - for example, cost per prior authorization resolved or per pull request triaged. It turns token metrics into the unit economics of AI-performed work. What is an Intelligence Budget? The economically rational amount of intelligence - model capability, reasoning, context, tools and human review — worth spending on a given outcome, based on its value and risk. Model router in Microsoft Foundry is one way to operationalize it. Why do AI agents cost more than single model calls? One agent task can involve planning, tool calls, retries and verification - many model calls with compounding context. Research on production agentic workflows attributes roughly 60% of task cost to refining and verifying answers, not generating the first response. Will falling model prices make AI cost management unnecessary? No. By the Jevons paradox, cheaper intelligence expands consumption, so total AI spend typically rises as unit prices fall. The discipline that matters is maximizing value per unit of intelligence. Who should own AI economics? A shared model: the business owns the outcome and its value, technology owns the optimization levers, and finance owns the economic discipline and review cadence. #MicrosoftFoundry #Agent365 #AzureAI #FinOps #AgenticAI #AIAgents #Azure #MicrosoftCostManagement #AIEconomics #Tokens References Microsoft Azure Blog: "The Economics of Agent Optimization: From pilots to measurable returns" (August 12, 2026) Microsoft FY26 Q4 earnings call (Satya Nadella, July 2026) McKinsey — "Cost versus value: managing agentic AI system performance" (July 2026) FinOps Foundation — State of FinOps 2026; Microsoft Learn — Model router for Microsoft Foundry; Agent optimizer; Foundry Control Plane cost optimizationSimplify AKS observability with Azure Native New Relic Service
An Azure Native path to New Relic Intelligent Observability for AKS AKS environments are dynamic by design. Applications can span clusters, namespaces, nodes, pods, and containers, while workloads scale and change continuously. Obtaining consistent visibility often requires platform teams to deploy and maintain monitoring components separately on every cluster. Azure Native New Relic Service simplifies this process by integrating New Relic onboarding and management into Azure. Customers can already use the service to: Create a new New Relic account or link an existing account from Azure. Configure the forwarding of Azure platform metrics and logs to New Relic. View the monitoring status of Azure resources. Consolidate procurement and eligible New Relic charges through Azure Marketplace. Monitor multiple Azure subscriptions through a single New Relic resource. With AKS extension support, customers can now extend this native management experience to their Kubernetes clusters. Install the New Relic integration from the Azure portal The new experience follows the same simple model used by Azure Native integrations for other compute resources. From an Azure Native New Relic Service resource, customers can navigate to New Relic account config > Azure Kubernetes Services, select an eligible AKS cluster, and choose Install Extension. Azure then deploys the New Relic Kubernetes integration by using the AKS cluster extensions framework. After deployment completes, the portal displays the installation status for the cluster. Customers can return to the same experience to review the status or select Uninstall Extension when monitoring is no longer required. AKS cluster extensions provide an Azure Resource Manager-based approach for installing and managing services on AKS. This gives customers a consistent Azure control plane experience for deployment and lifecycle operations instead of requiring a separate, manual Helm installation for each cluster. Gain deeper visibility into Kubernetes workloads The extension deploys the New Relic Kubernetes integration to the selected AKS cluster. The integration provides visibility across Kubernetes infrastructure and workloads, including cluster, node, namespace, deployment, pod, and container health and performance. Depending on the enabled New Relic configuration, customers can also bring together Kubernetes events, logs, and Prometheus-formatted metrics with application and Azure platform telemetry in New Relic. This helps application, platform, and site reliability engineering teams investigate issues across the stack without stitching together disconnected views. Teams can use New Relic to: Understand resource consumption and health across clusters, nodes, pods, and containers. Identify unhealthy workloads, container restarts, and capacity constraints. Correlate Kubernetes infrastructure signals with application performance data. Explore Kubernetes entities and relationships through New Relic's cluster experience. Create dashboards, alerts, and operational workflows using telemetry from Azure and AKS. The result is a more direct path from detecting an issue to understanding its impact on applications and users. Reduce operational toil with unified telemetry For organizations operating multiple AKS clusters, consistency is as important as visibility. Manual installation can lead to configuration drift, missed clusters, and additional work whenever monitoring components need to be changed. The Azure Native New Relic Service experience helps address these challenges by providing: Simplified onboarding: Install the integration from the Azure portal without building a separate deployment workflow. Centralized visibility: Review AKS extension status alongside other Azure resources connected to New Relic. Azure governance alignment: Use Azure Resource Manager and Azure role-based access control as part of the management experience. Lifecycle management: Install or remove the extension through a consistent Azure workflow. Unified, full-stack observability: Connect AKS telemetry with application, infrastructure, log, and Azure platform data in New Relic. This experience is particularly useful for platform teams that want to make observability available as a standardized service while allowing development teams to use New Relic for troubleshooting and performance optimization. Get started To begin monitoring AKS with Azure Native New Relic Service: Either browse to the Marketplace offer listing or in the Azure portal, create an Azure Native New Relic Service resource. Go to New Relic account config > Azure Kubernetes Services. Select the AKS cluster that you want to monitor. Select Install Extension and then confirm the installation. After the status changes to Installed, open New Relic to explore your Kubernetes data and configure the dashboards and alerts appropriate for your environment. If you face any technical challenges do raise a support ticket and share your feedback.Partner Case Study | Siemens
The longstanding partnership between Microsoft and Siemens—a German tech conglomerate that focuses on industrial automation—helps solve a crucial challenge facing consumer packaged goods (CPG) and retail companies: fragmented processes across production. The CPG and retail industries—both essential to everyday life and major players on the global stage—experience multiple unique pain points. Consumers have rapidly shifting preferences; labeling and packaging regulations are more stringent than in past decades; and both product ingredients and waste reduction efforts must reflect sustainability goals—not to mention the complexity of global supply chains. In addition to all this, siloed teams and disconnected operations can take a serious toll, slowing down product launches, driving up compliance costs, and making it harder to keep up with market trends. Siemens' Integrated Lifecycle Management (ILM) is specifically tailored to address the complex needs of the CPG and retail industries. A single, reliable source of truth helps organizations manage industry complexity, minimize errors, and accelerate decision-making. By seamlessly connecting product development, program management, and brand management using AI and cloud innovation, Siemens' ILM helps these sectors remain agile and competitive in a fast-paced market. Cloud-powered lifecycle management tailored for CPG and retail At the core of Siemens' ILM is Siemens' Teamcenter X on Azure, a cloud-based product lifecycle management (PLM) platform. Teamcenter X securely integrates teams, processes, business systems, and critical product data. For CPG manufacturers, this accelerates innovation, shortens product development cycles, and provides the agility needed to quickly respond to changes in consumer demand and regulatory requirements. Additionally, Teamcenter X on Azure delivers powerful generative AI capabilities, including seamless integration with Microsoft Teams and its intuitive chat functionality. This significantly improves cross-team communication and collaboration, a critical advantage for any organization. Teamcenter X on Azure harnesses advanced AI to enhance productivity and innovation specifically within the demanding environment of CPG manufacturing. Powered by Microsoft Azure OpenAI Service, the application helps augment the creation, optimization, and debugging of code for factory automation software, while industrial AI makes visual quality inspection on the shop floor possible. Continue reading here Explore all case studies or submit your own Subscribe to case studies tag to follow all new case study posts. Don't forget to follow this blog to receive email notifications of new stories!December 2025
Microsoft Ignite 2025 - Marketplace highlights Microsoft Ignite was packed with announcements and insights for Marketplace partners. From new commerce capabilities to AI-driven innovations, here are some key takeaways: Global expansion of Microsoft Marketplace - Microsoft announced that the reimagined Microsoft Marketplace, which launched in the U.S. earlier this year, is now globally available. This expansion includes new APIs for distribution partners, enabling them to link their own cloud marketplace with Microsoft’s, opening significant opportunities for software companies in SMB and mid-market segments. 🎬 Watch a recorded webinar with TD SYNNEX on the power of distribution to accelerate SMB marketplace sales. Global availability of Resale Enabled Offers - This capability allows software development companies to and channel partners to resell software solutions directly through Marketplace, simplifying transactions, expanding reach, and scaling revenue. 👉 Read more about this announcement and get started Introducing App Accelerate - A unified offer that brings together incentives, benefits, and co-sell support across the Microsoft Cloud. App Accelerate provides end-to-end technical guidance, developer tools, and go-to-market resources so software development companies can innovate and scale. Previews are beginning now, with full availability planned for 2026. ✅ Sign up to receive updates Enhanced Partner Marketing Center - Discover, customize, and launch campaigns faster with intelligent search and AI-powered tools—all on one connected platform. The current Partner Marketing Center will remain available as the new and enhanced Marketing Center platform launches in early 2026 with 24 campaigns-in-a-box, aligned to FY26 solution plays. ✨ Get ready for the new era of partner marketing Frontier Partner badge – New customer-facing badges recognize top services, channel, and software development company partners that are driving AI transformation with customers and offer them an opportunity to differentiate themselves from the competition. 🛡️Differentiate your AI-first leadership Catch up on Microsoft Ignite sessions Ignite 2025 delivered powerful insights and announcements for Marketplace partners, and now you can catch up on the sessions you missed. Explore these recorded keynotes to learn about new capabilities, partner programs, and strategies to accelerate growth through Microsoft’s ecosystem. Ignite opening keynote Ignite partner keynote: Powering Frontier Partnerships Additionally, we’ve compiled recordings of relevant Marketplace partner and customer sessions so you can watch on-demand. Revisit Marketplace-focused sessions and resources. Just look for the ✨ icon below. Partner sessions: PBRK415 Grow your business with Microsoft AI Cloud Partner Program Find out how the Microsoft AI Cloud Partner Program helps you grow with new benefits, designations, and skilling opportunities. This session covers updates like the Frontier Partner Badge, Copilot specialization, and streamlined Marketplace engagement—all designed to accelerate your AI transformation journey. PBRK416 Accelerate Growth through Partner Incentives Explore how Microsoft is boosting partner growth with streamlined incentives, AI-first strategies, and new designations like Frontier Distributor. This session covers expanded investments in Azure Accelerate, Copilot solutions, and security practices—plus insights on how to capitalize on evolving programs and co-sell opportunities. PBRK417 Partner: Connect, Plan, Win – Enhancing Co-sell Engagement Discover how to enhance collaboration, optimize joint efforts, and drive success in shared initiatives. Gain insights into improving interactions with Microsoft sellers and leveraging opportunities, along with guidance on proactive co-selling to align your goals with Microsoft's for sustained growth. PBRK418 Partner: Benefits for Accelerating Software Company Success Learn about the resources and benefits available for software development companies across all stages of the build, publish and grow journey in MAICPP. Whether you’re developing a new agent solution or working toward a certified software designation, there are targeted skilling opportunities, technical resources, and GTM benefits to help. Tap into new investments for AI apps and agents and hear from your peers on how they’ve used rewards such as customer propensity scores and Azure sponsorship. PBRK419 SI & Advisory Partner Readiness: Accelerating the Journey to Frontier Understand how Microsoft is empowering our SI and advisory partners to accelerate frontier firm readiness for our Enterprise customers by driving AI transformation with agentic solutions and services. ✨PBRK420 Executing on the channel-led marketplace opportunity for partners See how Microsoft’s unified Marketplace drives partner growth with resale-enabled offers, creating scalable channel sales and co-sell opportunities. This session shares practical steps to build a sustainable Marketplace practice and leverage the partner ecosystem for greater reach and profitability. PBRK421 Enabling a thriving partner ecosystem: New CSP Authorization Criteria Dive into what’s new for Cloud Solution Providers, including updated authorization requirements and designations that help you stand out. This session covers steps to choose the right tier, build trust as a customer advisor, and prepare for growth with AI-driven solutions and Copilot offerings. PBRK422 The Future of Partner Support: Customer + Partner + Microsoft Discover ‘Unified for Partners,’ Microsoft’s new support model designed for CSP partners to deliver customer success at scale. This session introduces the Support Services designation, offering faster response times, financial incentives, and integrated tools to strengthen your support capabilities. PBRK423 Partner Execution at Scale with SME&C Explore growth opportunities in the high-potential SME&C segment. This session highlights investments in co-selling, AI-first strategies, and what it means to become ‘customer zero,’ with examples of frontier firms driving innovation at scale. ✨PBRK424 Marketplace Success for Partners—from SMB to Enterprise Learn how to build, publish, and monetize AI-powered solutions through Microsoft Marketplace. This session shares a proven approach to align your Marketplace strategy with your sales motion and unlock new revenue opportunities. PBRK272 Accelerate Secure AI: Microsoft’s Security Advantage for Partners Explore Microsoft’s integrated security solutions and learn how to help customers strengthen their defenses in the AI era. This session highlights partner opportunities, resources to grow your security practice, and what it takes to lead as a next-generation security partner. Customer Sessions: ✨Microsoft Marketplace: Your trusted source for cloud solutions, AI apps, and agents | STUDIO47 Hear from Cyril Belikoff, VP of Commercial Cloud & AI Marketing, sharing the reimagined Microsoft Marketplace—the gateway to thousands of AI-powered apps, agents and cloud solutions—all built to accelerate innovation and drive business outcomes. Discover how customers benefit from faster deployment, seamless integration with Microsoft tools, and trusted solutions, and how partners can scale their reach, accelerate sales, and tap into Microsoft’s global ecosystem. Azure Accelerate in action: Confidently migrate, modernize, and build faster Join Cyril Belikoff for a rapid Q&A that spotlights real-world customer success and the transformative impact of Azure Accelerate. Hear how customers like Thomson Reuters achieved breakthrough results with our powerful offering that provides access to Microsoft experts and investments throughout your Azure and AI journey. ✨BRK213 Microsoft Marketplace: Your trusted source for cloud and AI solutions Discover how the reimagined Microsoft Marketplace is reshaping the future of cloud and AI innovation. In this session, we’ll explore how Microsoft Marketplace—unifying Azure Marketplace and Microsoft AppSource—empowers organizations to become Frontier Firms by streamlining the discovery, purchase, and deployment of tens of thousands of cloud solutions, AI apps, and agents. ✨BRK215 Boost cloud and AI ROI using Microsoft Marketplace As organizations embrace an AI-first future, cloud adoption is accelerating to drive innovation and efficiency. This session explores practical strategies to optimize cloud investments—balancing performance, scalability, and cost control. Learn how Microsoft Marketplace enables rapid solution deployment while maintaining governance, compliance, and budget discipline. Build a resilient, cost-effective cloud foundation that supports AI and beyond. Community Recap Partner of the Year Award Winners Congratulations to the winners and finalists of the 2025 Microsoft Partner of the Year Awards in the Marketplace category! 🏆 Explore all winners and finalists Fivetran earned the top honor as Marketplace Partner of the Year for its innovation in automating data movement on Microsoft Azure, enabling enterprises to accelerate AI and analytics initiatives. Varonis Systems Inc. and Bytes Software Services were recognized as finalists for delivering exceptional solutions and driving customer success through Marketplace. What’s Coming Up AI-powered acceleration: Scale faster in Microsoft Marketplace 📆 Thursday, December 04, 2025, at 9:00 AM PST Microsoft Marketplace is no longer just a procurement convenience; it’s a strategic revenue engine. Dive into operational readiness, CRM-native automation, seller engagement, trust signals, and AI-enabled acceleration. Whether you're just getting started or looking to optimize your Marketplace motion, this session will provide you with information that will turn your first sale into a repeatable growth engine. Scale smarter: Discover how resale enabled offers drive growth 📆 Friday, December 05, 2025, from 11:00 - 12:00 PM GTM+1 Discover how resale enabled offers help software development companies to scale through the Microsoft Marketplace by simplifying transactions, expanding reach and accelerating co-sell opportunities. Chart your AI app and agent strategy with Microsoft Marketplace 📆 Thursday, December 11, 2025, from 8:30 - 9:30 AM PST Organizations exploring AI apps and agents face a critical choice: build, buy, or blend. There’s no one-size-fits-all—each approach offers unique benefits and trade-offs. Tune in for insights into the pros and cons of each approach and explore how the Microsoft Marketplace simplifies adoption by providing a single source for trusted AI apps, agents, and models. Office hours for partners: Marketplace resale-enabled offers 📆 Thursday, December 18, 2025, at 8:30 AM PST Tune in to explore resale enabled offers through Microsoft Marketplace. This recently announced capability enables software companies to expand into new markets globally, at scale, and without additional operational overhead. Dive deep into the workflow and requirements for these deals. Learn about reporting and best practices from those that are already selling globally with resale enabled offers. Microsoft Ignite will return to San Francisco next year 📆 November 17-20, 2026 Sign up now to join the Microsoft Ignite early-access list and be eligible to receive limited‑edition swag at the event. 💬 Share Your Feedback! We truly appreciate your feedback and want to ensure these Partner Digests deliver the information you need to succeed in the marketplace. If you have any feedback or suggestions on how we can continue to improve the content to best support you, we’d love to hear from you in the comments below!
