Jesper Bagh’s Post

You can’t build a "validated" AI model on a "shaky" foundation. This audit provides the "Qualified foundations" required for the next wave of agentic AI in Pharma, R&D and manufacturing. #microsoft #gxp #ai #regulatorycompliance.

It is interesting and encouraging to see major players like Microsoft taking formal steps to engage with regulated industry requirements like GxP. For many companies in the Life Science space, Microsoft Azure is a foundation technology in their stack, so compliance is a non-negotiable. Naturally, the question now turns to AI. How will this same level of rigor extend to GitHub Copilot, Microsoft Copilot, and broader AI‑based tools that are rapidly becoming embedded in development, operations, and scientific workflows? #clinicaltrials #clinicalresearch #pharma #biotech #FDA #MHRA

🛡️Digital sovereignty is no longer a “future trend” in EMEA – it is now a hard requirement in many of the countries and opportunities our partners operate With today’s expansion announcement from Satya Nadella - Microsoft Sovereign Cloud offeries bring single core kd new capabilities that address sovereignty across technology, legal and operational perspective. For our EMEA Software Partners, this means 🔹Build on a full sovereign stack – #AzureLocal #disconnected operations, #Microsoft365Local and #FoundryLocal – to deliver industry solutions and AI capabilities that run entirely inside national and customer‑controlled boundaries, even when completely offline. 🔹 Drive a new class of opportunities across government, defense, critical infrastructure, healthcare and financial services in EMEA, where data residency, operational autonomy and “air‑gapped” deployments are non‑negotiable. 👉 For Software Partners, the ask is clear how will you redesign your roadmap, architecture and go‑to‑market to become the sovereign, AI‑powered platform of choice in your regulated EMEA markets? Read more about what this announcement means for the future of sovereign AI: https://lnkd.in/d6brinjn #Microsoft #SovereignAI #DigitalSovereignty #TrustedCloud #AI #Trust #ISV

Here is the real shift. AI is no longer something you have to send your data to. AI can now come to where your data already lives. With new local and disconnected capabilities, organizations can run AI models inside their own environments while keeping full control over access, compliance, and operations. This is a big deal for government, healthcare, defense, and financial services. But it also matters to any business that cannot afford downtime or data risk. Control is becoming a feature. Not a constraint. Where would this change your AI roadmap? #EnterpriseAI #DataSovereignty #AIInfrastructure #CloudStrategy #Azure #Microsoft

Microsoft just set the baseline for AI adoption velocity. Security budgets didn't. In FY26 Q2, Microsoft reported: - $37.5B in capital spend in Q2 (up 66% YoY) — largely to expand AI/cloud capacity - $81.3B revenue - $51.5B Microsoft Cloud revenue (up 26% YoY) - Azure grew 39% (and still got labeled "slowing") Now translate that into risk. Microsoft said Microsoft 365 Copilot "seat adds" rose over 160% year-over-year, reaching 15 million paid seats. GitHub Copilot subscribers hit 4.7M (up 75% YoY). That's millions of new "AI operators" in the enterprise — and an explosion of workloads, identities, data paths, plugins, connectors, and agents that need governance. Meanwhile, security budgets cooled toward ~4% growth in many organizations during the 2025 cycle. If your cloud footprint is compounding anywhere near the pace of your platform providers, but your security capability is scaling like a cost center, you're creating systematic risk that compounds every quarter. At this adoption speed, three capabilities become non-negotiable: - Identity-first security (Entra ID) for agent and privilege governance - Data classification and policy (Purview) before AI touches sensitive content - Integrated detection (Defender and Sentinel) across workloads and user/agent activity Most CFOs track Microsoft spend closely. They saw the earnings print. Bring the same discipline to this question: Did our security capability scale with our adoption? #MicrosoftSecurity #CISO #Purview #EntraID

Microsoft has announced AI-powered assistants are now integrated into SSMS, VS Code, and Microsoft Fabric. These tools will further lower barriers to entry for data professionals, streamlining routine tasks and accelerating custom solution development. In the short term, we may see productivity bumps and faster onboarding for new team members. Still, there’s also a challenge: over-reliance on AI may risk overlooking fundamental best practices. For the Azure platform, widespread AI adoption could drive demand for cloud workloads, supporting a more agile and efficient data ecosystem. Yet, the industry should remain thoughtful about governance and code quality, as automated helpers become core team members. Curious to hear what this community thinks—Will these assistants ultimately improve or complicate your workflow, and how can leaders best guide responsible adoption? #MicrosoftFabric #Azure #PowerBI #DataAutomation #ArtificialIntelligence Read more here: https://lnkd.in/gKe_7Zin

𝗢𝗽𝗲𝗻-𝗦𝗼𝘂𝗿𝗰𝗲 𝘃𝘀 𝗖𝗹𝗼𝘀𝗲𝗱 𝗟𝗟𝗠𝘀: 𝗪𝗵𝗮𝘁’𝘀 𝗕𝗲𝘀𝘁 𝗳𝗼𝗿 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗔𝗜? 🤔 Enterprises today are racing to build AI-powered apps — chatbots, summarization tools, knowledge management, document processing, and more. But there’s a critical first decision: Should you go open-source or closed/proprietary? Microsoft highlights that both approaches have unique benefits and trade-offs. 𝗢𝗽𝗲𝗻-𝗦𝗼𝘂𝗿𝗰𝗲 𝗟𝗟𝗠𝘀 🛠️   • 𝗙𝘂𝗹𝗹 𝘁𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝗰𝘆: Access to model architecture, weights, and training code.   • 𝗖𝘂𝘀𝘁𝗼𝗺𝗶𝘇𝗮𝗯𝗹𝗲: Fine-tune for your industry or domain.   • 𝗙𝗹𝗲𝘅𝗶𝗯𝗹𝗲 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁: Cloud, on-premises, or hybrid.   • 𝗗𝗮𝘁𝗮 𝗼𝘄𝗻𝗲𝗿𝘀𝗵𝗶𝗽: Total control over governance and security.   • 𝗧𝗿𝗮𝗱𝗲-𝗼𝗳𝗳: Experts note that open-source requires enterprises to manage deployment, monitoring, and lifecycle themselves. 𝗖𝗹𝗼𝘀𝗲𝗱/𝗣𝗿𝗼𝗽𝗿𝗶𝗲𝘁𝗮𝗿𝘆 𝗟𝗟𝗠𝘀 🔒   • 𝗠𝗮𝗻𝗮𝗴𝗲𝗱 𝘀𝗲𝗿𝘃𝗶𝗰𝗲: Vendor handles hosting, scaling, and updates.   • 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 & compliance: Built-in privacy features and SLAs.   • 𝗤𝘂𝗶𝗰𝗸 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻: Ready-to-use for production workloads.   • 𝗟𝗶𝗺𝗶𝘁𝗮𝘁𝗶𝗼𝗻𝘀: Microsoft points out that model internals aren’t accessible, and customization is mostly prompt-based. 𝗞𝗲𝘆 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗖𝗼𝗻𝘀𝗶𝗱𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 ⚖️ 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 & 𝗖𝘂𝘀𝘁𝗼𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻   • 𝗢𝗽𝗲𝗻-𝗦𝗼𝘂𝗿𝗰𝗲 → Deep control, tailored to your needs   • 𝗖𝗹𝗼𝘀𝗲𝗱 → Easier to deploy, limited tuning 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 & 𝗖𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲   • 𝗢𝗽𝗲𝗻-𝗦𝗼𝘂𝗿𝗰𝗲 → You control data, ideal for regulated industries   • 𝗖𝗹𝗼𝘀𝗲𝗱 → Vendor-managed privacy reduces operational overhead 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗢𝘃𝗲𝗿𝗵𝗲𝗮𝗱   • 𝗢𝗽𝗲𝗻-𝗦𝗼𝘂𝗿𝗰𝗲 → Requires skilled teams for infrastructure & monitoring   • 𝗖𝗹𝗼𝘀𝗲𝗱 → Vendor-managed, faster to deploy 𝗖𝗼𝘀𝘁   • 𝗢𝗽𝗲𝗻-𝗦𝗼𝘂𝗿𝗰𝗲 → No licensing fees, but higher infra/engineering costs   • 𝗖𝗹𝗼𝘀𝗲𝗱 → Subscription/token-based, predictable costs 𝗛𝘆𝗯𝗿𝗶𝗱 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵 💡 Microsoft recommends that many enterprises combine the best of both worlds:   • 𝗖𝗹𝗼𝘀𝗲𝗱 𝗟𝗟𝗠𝘀 for rapid deployment and general tasks   • 𝗢𝗽𝗲𝗻-𝗦𝗼𝘂𝗿𝗰𝗲 𝗟𝗟𝗠𝘀 for sensitive data, compliance, or deep customization ✅ 𝗕𝗼𝘁𝘁𝗼𝗺 𝗹𝗶𝗻𝗲: Experts emphasize that the right choice depends on 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗻𝗲𝗲𝗱𝘀, 𝗰𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲 𝗿𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁𝘀, 𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗺𝗮𝘁𝘂𝗿𝗶𝘁𝘆, 𝗮𝗻𝗱 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗴𝗼𝗮𝗹𝘀. Balancing flexibility, control, and operational efficiency ensures AI solutions are 𝘀𝗰𝗮𝗹𝗮𝗯𝗹𝗲, 𝘀𝗲𝗰𝘂𝗿𝗲, 𝗮𝗻𝗱 𝗶𝗺𝗽𝗮𝗰𝘁𝗳𝘂𝗹. #AI #EnterpriseAI #LLM #OpenSource #ClosedSource #Microsoft #AIGovernance #HybridAI #DigitalTransformation #ResponsibleAI #TechStrategy #EnterpriseArchitecture #Azure #CloudComputing #MicrosoftAzure #AzureAI #TechOpportunities #AzureSolutions

Microsoft Approves Everfox’s Trusted Thin Client for Azure Clouds https://ow.ly/t0xC50YkgoR #TechnologyNews #AI #TechNews #CIOCommunity #CIOLeadership #CIOInfluence #TechLeadership #ITStrategy #FutureOfIT #TechTrends

New in Microsoft Marketplace: February 12, 2026. Learn about 252 new offers that went live in Microsoft Marketplace, a single destination to find, try, and buy cloud solutions, AI apps, and agents to meet your business needs. Get it now in our marketplace AI-Powered Supply Chain Solutions: Enmovil's Supply Chain solution uses AI for precise forecasting, inventory optimization, and synchronized planning across demand, stock, and logistics. It enhances delivery reliability, cuts costs, speeds planning, and improves adaptability, enabling enterprises to operate efficiently and resiliently amid disruptions.AutoSec Security Scanning: AutoSec offers AI-powered website security scanning that detects critical vulnerabilities in minutes, replacing costly, slow manual penetration testing. It provides actionable reports, reduces false positives, and integrates via API. Ideal for IT, DevOps, and SMBs, it ensures continuous, affordable... #techcommunity #azure #microsoft https://lnkd.in/e8UAkNF4

From Microsoft Community Hub, Public Preview: Automatic zone balance for Virtual Machine Scale Sets, by HilaryWang "We're excited to announce the public preview of automatic zone balance for Azure Virtual Machine Scale Sets. This new capability helps..." https://lnkd.in/eqJXk4fu