In my previous blog, I talked about how we collaborate with great partners such as Sight Machine, Litmus, Mesh Systems, Siemens, Rockwell, Schneider Electric, and others to deliver end to end value for the practical application of AI in manufacturing environments. These partners, along with forward-thinking customers like Chevron, Husqvarna and Ecopetrol continue to drive our innovation roadmap and push the boundaries of how to use Agentic AI for operational efficiency improvements, visual inspection, and safety enhancements.
How Ecopetrol is modernizing its data platform to take advantage of AI
As an integrated energy conglomerate, Ecopetrol operates across the entire hydrocarbon chain encompassing exploration, production, transportation, refining, and commercialization, as well as linear infrastructure, including energy transmission and road concessions. The company is dedicated to leading the energy sector into a more sustainable future by adopting technology that enables intelligent operations.
Ecopetrol has partnered with Microsoft to build a flexible and secure edge to cloud platform, based on Azure IoT Operations and Fabric Real-Time Intelligence, that can standardize data across diverse sources to enable data contextualization and eventually, AI integration. This improved ability to harness data can help Ecopetrol meet key objectives such as improved operational performance, cost savings, lowered energy consumption, and reduced carbon emissions.
New innovations introduced at Hannover Messe 2026:
Microsoft’s Industrial AI platform has been purpose-built to support edge and physical AI scenarios. It offers a comprehensive foundation to build, scale, and govern Industrial AI initiatives with a unified intelligence layer powering AI (Fabric IQ, Foundry IQ, Work IQ) and a consistent framework to managing apps, data and infrastructure with the adaptive cloud approach.
Looking more closely at how these components come together to enable business outcomes: Azure IoT Operations and Azure IoT Hub collect real-time data from operational assets and devices and send semantically-ready modelled data to Fabric IQ so that it can be contextualized with other enterprise data sources for downstream analytics. Microsoft Foundry has been extended to the edge with Foundry Local so that organizations can use the same tooling that they use to deploy and manage AI models in the cloud for edge use cases as well. Azure IoT Operations, Azure IoT Hub, and Foundry Local integrate into Azure Resource Manager, which brings OT devices, assets, and edge AI models into the same management and security paradigm as all other Azure managed resources. For organizations with sovereignty requirements, Microsoft enables Sovereign Private Cloud with Azure Local, which can run in connected or disconnected mode, depending on customer requirements.
At HMI 2026, we are announcing our next set of innovations in this space to help manufacturers and partners initiate and scale industrial AI initiatives on a trusted foundation.
Unlocking value from operational data
Azure IoT Operations, enabled by Azure Arc, is a set of scalable edge services, built on industry standards to easily capture device and equipment data, process and normalize it at the edge, seamlessly send and receive operational insights to and from the cloud, and contextualize that data so it can be used directly by Physical AI workloads running at the edge. Through Arc and Kubernetes, Azure IoT Operations empowers our customers with a unified technology architecture and data plane that supports repeatable solution deployment, automated updates to apps, cost-effective high availability, and redundancy at the edge.
At HMI 2026, we are announcing the next major release of Azure IoT Operations, 2603. This release enables manufacturers to build, manage, and operate industrial data flows across the full edge-cloud lifecycle without custom code. Key new capabilities include edge-to-cloud industrial data management with no-code visual data pipelines, cloud-to-edge device and asset command and control, unified health status and observability, as well as new connector integrations for third-party MQTT brokers and Litmus Edge industrial gateways. Furthering our commitment to open standards, we also recently announced support for WC3 Web of Things (WoT) in Azure IoT Operations, which simplifies the process of integrating industrial assets into intelligent applications.
Agentic operations at the edge
Foundry Local enabled by Azure Arc extends cloud grade AI inference to on-premises and edge environments. It allows organizations to deploy, run, and manage generative and predictive AI models directly on customer-controlled infrastructure, such as factory floors, remote industrial sites, and disconnected environments, where low latency, data locality, and operational autonomy are critical. The solution builds on Azure Arc-enabled Kubernetes as a unified control plane, enabling AI workloads to be deployed and operated locally using the same paradigms as in the cloud.
Today, we are excited to announce Foundry model catalog in Azure Local, which supports both curated open-source models from a managed catalog and customer proprietary bring-your-own-model (BYOM) deployments. Models can run concurrently across available on-premises hardware, on CPU-only systems or with GPU acceleration, so customers can match performance and cost requirements across diverse edge environments. AI models are delivered as containerized services, exposing standard REST endpoints, including OpenAI compatible APIs for generative models and dedicated APIs for predictive workloads. This allows applications to consume local AI inference in the same way they consume cloud AI services, with minimal changes.
New capabilities for secure policy and identity management
While properly contextualized data and AI hold the key to optimizing business outcomes, organizations cannot risk rolling out these initiatives without the proper management and security foundation in place. Taking an adaptive cloud approach for these capabilities is also crucial, to ensure organizations have the right level of visibility, control, and protection across their entire digital and physical domain.
Azure IoT Hub is Microsoft’s key offering to connect and manage IoT devices and assets with direct connections to the cloud. In November, we announced the public preview of Azure IoT Hub integration with Azure Device Registry which brought IoT devices under the purview of the Azure management plane (ARM, Azure resource manager) and allowed them to be secured with best-in-class Microsoft-backed X.509 certificate management capabilities.
Today, we are expanding upon that preview with strengthened device identity, security, and fleet‑scale management. This refresh delivers a more complete, end‑to‑end certificate management experience, covering certificate issuance, renewal, and revocation, with support for hybrid trust models, including customer‑managed root CAs from non‑Microsoft PKIs. It also introduces a more cohesive Azure Portal experience for service configuration and device operations, allowing operators to manage devices consistently as ADR resources using standard Azure tooling and workflows.
Firmware analysis capabilities
Another critical security consideration for customers is the security profile of the device itself. With firmware analysis, enabled by Azure Arc, our goal is to provide deeper visibility into IoT/OT and network devices by analyzing the foundational software (firmware) they run. At HMI, we are releasing a preview of integration of firmware analysis with Azure Device Registry, delivering fleet-level visibility into where firmware vulnerabilities exist across deployed IoT and OT environments.
This new integration correlates analyzed firmware images with devices and assets registered in Azure Device Registry, allowing customers with both Azure IoT Operations and IoT Hub to quickly see how many devices are running a given firmware image and which specific assets may be exposed to known security risks, bridging the gap between firmware insights and real-world operational impact. This release also offers new capabilities to help customers prioritize vulnerabilities, work with larger firmware images, and share security analysis results with supply chain partners.
Sovereign options for mission-critical workloads
While security continues to be a strategic priority for most large, global organizations, digital sovereignty is an increasingly critical requirement for many manufacturers as well. For these scenarios, Microsoft offers capabilities that support customers across connected, intermittently connected and fully disconnected modes. With Azure Local disconnected, organizations can now run mission-critical infrastructure with Azure governance and policy control, with no cloud connectivity, optimizing continuity for sovereign, classified, or isolated environments.
With Azure Local disconnected operations, management, policy, and workload execution stay within the customer-operated environments, so services continue running securely even when environments must be isolated or connectivity is not available. Using familiar Azure experiences and consistent policies, organizations can deploy and govern workloads locally without depending on continuous connection to public cloud services. Azure Local is designed to scale with mission-critical needs from smaller deployments to larger footprints that support data-intensive and AI-driven workloads.
Conclusion
As a leading forum for industrial innovation, Hannover Messe provides manufacturers with an opportunity to explore the latest technologies transforming modern operations. This year’s theme, “Think Tech Forward,” aligns with the industry’s growing emphasis on applying proactive, AI‑driven intelligence across business processes and ecosystems. Join Microsoft in Hall 17, Booth G06 to discover practical approaches for implementing AI to improve operational outcomes.
Learn more about Microsoft’s overall presence at the show here. For a deeper dive into how Microsoft is driving industrial outcomes with partners, please refer to the first blog in this series: Making Physical AI Practical for Real-World Industrial Operations: Part 1
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Microsoft