Welcome to the Power Platform monthly video update. Here is a quick summary of last month’s product, community, and learning news. Let’s see what’s new in Power Platform.  

Platform management 

Licensing capacity reporting 

Licensing capacity reporting is now fully available in the Power Platform Admin Center > Licensing > Power Automate Usage. Admins can now easily see which users are over capacity and which flows use the most resources. Export options and a unified licensing page are coming soon, along with more improvements.  

Moving on to Power Platform inventory, 

Power Platform Inventory is now generally available. Tenant Administrators can now see all Cloud Flows, Copilot Studio, Agent Flows, and Workflows. Agent workflows across every environment in one view. Soon, additional connectors, actions, and key usage data will make it even easier to identify active automations, enforce compliance, and avoid orphan resources.  

Next, let’s discuss the new usage page, 

The new usage page is now in public preview. It features modern dashboards that show adoption trends and analytics for Power Apps, Power Automate, and Copilot Studio. You can already see how Flow runs data to track execution patterns across your tenant.  

Agentic apps 

Bringing Microsoft 365 Co‑pilot into model-driven apps. 

Earlier, we showed how to enable Microsoft 365 Copilot in model-driven apps. Now you can use it where your business processes open in the Copilot side-play pane. You can ask Copilot to summarize table data, show active or pending items, recap area causes history, and find related content through Work IQ. This helps you move easily from asking “What’s going on?” to deciding “What should I do next?”all without leaving the app.  

With Microsoft 365 Co-Pilot, you can bring in the right agent when you need it. You can add or mention built-in agents, such as Researcher and Analyst, or use a custom agent your organization provides. Working with agents helps you turn insights into action, such as drafting documents, creating PowerPoint presentations, or scheduling meetings. Everything stays connected to your app context and chat history. To get started, follow the admin setup guide to see how end users work in the pane and learn how to customize the experience with agents.  

Building Modern apps 

New quality updates for modern controls in Canvas apps. 

We’ve released quality updates for all 9 modern controls in Power Apps: Canvas Apps, Text Number Input, Date Picker, Text Input, Tab List, Combo Box, Radio, Link, and Info Button. This major update focuses on consistency, reliability, and flexibility, driven by maker feedback. Whether building new apps or updating existing ones, these improvements make modern controls easier to use.  

The main improvements are inconsistency, performance, and developer experience. Controls now use a unified property model with standardized names and predefined value sets offering better intelligence, fewer formula errors, and less guesswork. The on-change behavior now triggers at the right times for faster, more responsive apps. Mobile optimized defaults are automatically applied to mobile layouts.  

Migration is supported at every step. When you open an app with an older modern control, you’ll see an in-product notification with a “learn more” link. An Update button will be available soon for all controls, each with its own migration guide for property renames and formula changes. You choose when and how to upgrade.  

Power Automate 

Object-centric process mining analyzes processes by following real interacting business objects 

Object-centric process mining (OCPM) is a new way to analyze processes in Power Automate Process Mining. It models processes as they happen in real business environments. In contrast to traditional case-centric process mining, which groups events under a single case (e.g., an Order ID), OCPM allows a single event to belong to multiple objects and types, such as orders, invoices, deliveries, and payments. This retains the full network of interactions and dependencies intact.  

This feature solves a key problem in case-centric mining when events involve multiple objects. Putting them into a single case can hide relationships, duplicate events, or distort metrics. OCPM keeps these connections clear, showing object life cycles, activity nodes across object types, and color-marked flows. This makes it easier to spot bottlenecks. Check compliance rules, such as “ship only after payment,” and see how different processes or flows come together.  

OCPM works best when outcomes depend on relationships between different object types, such as in order-to-cash, procure-to-pay, or supply chain processes that can involve multiple related activities. Case-centric mining remains best for focused, single-instance workflows and processes centered on a single object or case.  

The Process Intelligence Experience is the new interface for process analysis in Power Automate Process Mining. It replaces the old fixed overview with a flexible card-based dashboard that adapts to your needs. You can create multiple tabs for different views, use dynamic filters across all visualizations, and arrange or resize cards to build your own workspace.  

Major enhancements include grouping related metrics and visualizations, switching between pre-configured views instantly, and sharing dashboard setups with your team. Data refreshes continuously, so you always have up-to-date information. Customizable layouts let you control what you see and how, making it easy to create views for different stakeholders and use cases.  

Power pages 

Infuse intelligent experience into Power Pages sites with the new Agent API 

The Agent API for Power Pages lets site creators build custom chat and other user experiences. You can also connect these with your own Microsoft Copilot Studio agents. This gives presentations more flexibility to add intelligence to their web experiences.  

Public preview, build Power Pages sites with AI using agentic coding tools 

We are announcing the public preview of the Power Pages plugin for GitHub Copilot, CLI, and Cloud Code. Just describe the site you want in plain language. The plugin handles everything from project setup and web API integrations to permissions and site deployment.  

The plugin is designed specifically for Power Pages. It understands table permissions, web roles, site settings, authentication, and web API patterns because it generates platform-aware code. You spend less time on manual setup and more time building your site. 

Source: What’s new in Power Platform: March 2026 feature update 

OpenAI has redefined ChatGPT, transforming it into a powerful AI product discovery and shopping platform that challenges traditional search engines.  

Building on these feature enhancements, the new features will be available to all users Free, Go, Plus, and Pro starting in late March 2026.  

New Shopping And Discovery Features 

  • Conversational shopping research: users describe what they want. ChatGPT delivers tailored buyers’ guides by analyzing web data, reviews, and product details.  
  • Visual search and comparison: users load images or describe needs. ChatGPT delivers instant side-by-side comparisons of products, prices, reviews, and features, eliminating the need to browse multiple sites.  
  • Memory integration, ChatGPT recalls prior conversations to better understand your preferences and refine recommendations.  
  • In targeted categories, the system excels in detailed domains like electronics, beauty, home and garden, and fashion.  

Commerce Integration (Agentic Commerce Protocol Or ACP) 

  • Merchant Partnerships, Leading Retailers, Target, Sephora, Nordstrom, Lowes, Best Buy, Home Depot, and Wayfair are now integrated with ChatGPT.  
  • Direct product feeds. Merchants use OpenAI’s ACP to deliver real-time product feeds. This ensures data, pricing, and availability remain accurate throughout conversations.  
  • E-commerce expansion is moving on to instant checkout. OpenAI is integrating Shopify and other platforms. Merchants can build custom chat app experiences.  

Impact On Search And Marketing 

  • Rethinking speech, this update shifts product discovery from keyword searches to dynamic AI-driven recommendations.  
  • Advertisement-free experience potential. The platform features organic, unsponsored recommendations. Beginning late March 2026, OpenAI will trial free ads for Go users in the US to ensure service sustainability.  
  • SEO shift: marketers must now optimize for AI-driven discovery, not just traditional search engines. Structured data and dialogue content take priority.  

All together, this update marks a major shift toward AI as the main starting point for shopping, handling millions of shopping-related questions every day.  

AI is reaching a point where everyone can have a personal assistant to support their learning and productivity. Who gains access to this technology will decide if AI expands opportunity or reinforces existing inequalities.  

We want to make powerful AI available to everyone. Since August, we have launched ChatGPT Go, our free and low-cost subscription, in 171 countries. Now Go is coming to the US and all places where ChatGPT is available. For $8 a month, you get more features, including messaging, image creation, file uploads, and storage. Soon, we will also start testing ads in the US for the free and Go plans. This will help more people use our tools with fewer limits or for free. Pro, Business, and Enterprise plans will stay ad-free.  

As we introduce ads, our focus remains on preserving what makes ChatGPT valuable. You can trust that answers are based on helpfulness, not advertising. Your data is kept private and not sold to advertisers. You also have control over ad relevance and personalization.  

With that in mind, here are the principles that guide how we approach advertising:  

Our Advertising Principles 

  • Mission Alignment Advertising should help make AGI accessible to all.  
  • Answer Independence Ads never affect the answers you get from ChatGPT. Answers are always based on what’s most helpful to you. Ads are kept separate and clearly marked.  
  • Conversation privacy: Your ChatGPT conversations are private and are not shared with advertisers.  
  • With choice and control, you can personalize and clear ad data at any time. There will always be an ad-free paid option.  
  • Long-term value, trust, and experience matter most, not maximizing time on ChatGPT.  

We plan to start testing ads for logged-in adults in the US on the Free and Go plans soon. The testing will begin in the coming weeks and roll out gradually. Ads will appear at the bottom of ChatGPT answers. When there is a relevant sponsored product or service related to your conversation, ads will be clearly marked and kept separate from regular answers. You will be able to see why you are seeing an ad, dismiss it, and provide feedback. During this initial testing phase, we won’t show ads to users under 18 or near sensitive topics like health, mental health, or politics.  

The best ads are helpful, entertaining, and help people find new products and services. With AI, we’re excited to create new advertisement experiences that are more useful and relevant than ever before. Chat-based interfaces let people do more than just click links; for example, you might soon see an ad and be able to ask questions to help you decide what to buy.  

Ads can also help small businesses and new brands compete. AI tools make it easier for anyone to create great experiences that help people find options they might not have seen before.  

We’ll listen to feedback and keep improving how ads appear. But our promise to put users first and keep our trust remains the same as we build our ad platform. With these principles, we can ensure our goals align with what people want from ChatGPT. We are focused on creating products and experiences that people and businesses value enough to pay for. Our enterprise and subscription services are already strong, and we believe ads can help make AI even more accessible as part of a balanced revenue model.  

When ad testing begins, we’ll seek feedback to ensure ads help expand AI access while maintaining trust in ChatGPT. 

SourceOur approach to advertising and expanding access to ChatGPT 

Artificial intelligence is reshaping the landscape of computing today.   

Most companies use Kubernetes to automate the deployment, scaling, and management of AI workloads in containers worldwide to manage high-performance AI infrastructure more transparently and efficiently. NVIDIA is donating an important software tool, the NVIDIA Dynamic Resource Assignment (DRA) driver for GPUs, to the Cloud Native Computing Foundation. CNCF is an independent organization that supports the cloud-native ecosystem.  

Announced today at KubeCon Europe in Amsterdam, this donation moves driver management from NVIDIA to Kubernetes. The Kubernetes community welcomes wider contributions and faster improvements for cloud technologies. Collaboration with the Kubernetes and CNCF communities to upstream the NVIDIA DRA driver for GPUs constitutes a major milestone for open-source Kubernetes and AI infrastructure, said Chris Aniszczyk, Chief Technology Officer of CNCF. Through aligning its hardware innovations with upstream Kubernetes and AI conformance efforts, NVIDIA is making high-performance GPU orchestration effortless and accessible to all.  

NVIDIA has also worked with CNCF to add GPU support for Kata containers. Kata containers are lightweight virtual machines that behave like regular containers while providing the isolation benefits of traditional virtual machines, offering improved security for workloads. This enables hardware acceleration in a more secure environment and makes it easier for organizations to adopt confidential computing, helping keep their data safe during processing.  

Simplifying AI Infrastructure 

In the past, managing GPUs for AI in data centers was complex. Now, efforts aim to make high-performance computing easier to use. Developers will benefit in several ways:  

  • Improved efficiency: the driver shares GPU resources more effectively, leveraging NVIDIA Multi-Process Service and Multi-Instance GPU technologies. The driver natively connects systems, including through NVIDIA multi-node NVLink technology; this is key for training large AI models on NVIDIA Grace Blackwell systems and other advanced AI infrastructure.  
  • Flexibility: developers can adjust their hardware setup as needed, changing how resources are used at any time.  
  • Precision: Users request precise computing, memory, or connection resources as needed.  

NVIDIA collaborates with major industry players to advance these features for the cloud-native community, ensuring they are at the core of every successful enterprise. “AI strategy bringing standardization to the high-performance infrastructure components that fuel production AI workloads,” said Chris Wright, Chief Technology Officer and Senior Vice President of Global Engineering at Red Hat. NVIDIA’s donation of the NVIDIA DRA driver for GPUs helps to cement the role of open source in AI’s evolution, and we look forward to collaborating with NVIDIA and the wider community within the Kubernetes ecosystem.  

Open-source software and its communities are a foundation of the infrastructure used for scientific computing and research, said Ricardo Rocha, lead of Platforms Infrastructure at CERN. For organizations like CERN, efficiently analyzing petabytes of data is essential to discovery, and community-driven innovation accelerates science. NVIDIA’s donation of the DRA driver supports the ecosystem that researchers depend on for both traditional scientific computing and machine learning workloads.  

Expanding the Open Source Horizon 

NVIDIA introduced the CLAW reference stack, which provides a standardized set of software for running AI infrastructure, and the NVIDIA OpenShell runtime, which lets users securely run autonomous agents programs that perform tasks independently. OpenShell offers security and privacy controls and works directly with Linux (an open-source operating system), eBPF (a technology for running programs inside the operating system kernel), and Kubernetes.  

NVIDIA also announced today that its high-performance AI workload scheduler, the KAI scheduler, is now a CNCF sandbox project. This is an important step to encourage more collaboration and ensure the technology grows with the needs of the cloud-native community. Developers and firms can start using and contributing to the KAI scheduler now.  

NVIDIA reaffirms its commitment to maintaining and contributing to Kubernetes and CNCF projects. This ongoing involvement helps meet the high demands of enterprise AI customers.  

After releasing Dynamo 1.0, NVIDIA expands the Dynamo ecosystem with Groove, an open-source Kubernetes API (application programming interface, a set of tools for building software) for managing AI on GPUs. Integrated with the LLM D inference stack a platform for running large language model inference it lets developers describe complex inference (the process of running AI models to get results) in a single resource.   

With these advances, companies can begin using and contributing to the NVIDIA DRA driver today.  

To experience these technologies firsthand, visit the NVIDIA booth at KubeCon for live demonstrations.

Source: Advancing Open Source AI, NVIDIA Donates Dynamic Resource Allocation Driver for GPUs to Kubernetes Community 

Your organization has likely spent recent years adopting best practices such as zero-trust architecture. Still, the cybersecurity environment is becoming more challenging.  

Threat actors now use AI to find and exploit vulnerabilities. They automate password attacks, phishing, and deepfake content, join calls, request IT support, and reset passwords. Some use AI to adjust their agents in real time as they move through your network.  

Focus on these four key priorities to lead identity security effectively this year. 

  1. Demand AI-powered protection that operates rapidly, adapts instantly, and remains vigilant at all times.  
  1. Prioritize the management, oversight, and protection of both AI and AI agents with immediate attention.  
  1. Implement zero trust across the organization using a unified access fabric solution.  
  1. Establish a strong identity and access foundation for enduring security.  

Use AI-Powered Protection That Is Quick, Adaptable, and Constantly Alert 

In 2026, make it a priority to add AI agents to your workflows. This will help reduce risk, speed up decision-making, and strengthen your defenses.  

Security systems generate a lot of data, but turning that information into clear actions remains mostly manual and can lead to mistakes. Tasks like investigations, policy adjustments, and threat responses often require assembling information from many tools, often under time pressure. Since cyber attackers now use AI to move faster and at a larger scale, relying only on human workflows can hold defenders back.  

Generative and agent-based AI enable teams to proactively manage access, identify policy gaps, and strengthen controls without increasing user friction. You can interact with these agents much like co-workers, reviewing patterns and policies to identify and explain needed changes. A recent study found that identity admins using the conditional access optimization agent in Microsoft Entra finished conditional access tasks 43% faster and 48% more accurately in tested scenarios. These improvements lead to stronger identity security and fewer opportunities for cyber attackers to find weaknesses. Microsoft Entra also comes with built-in AI agents that can review users’ apps, sign-ins, risks, and settings in context. They help you investigate unusual activity, summarize risky behavior, check for sign-in changes, investigate and fix risks, and improve access policies.  

The main benefit of AI-powered protection is its speed, scalability, and flexibility. Human-only workflows can’t keep up with the pace of evolving cyberattacks. By working with AI agents, your teams can frequently assess security, strengthen access controls, and respond to new risks before they become bigger problems.  

Manage, Oversee, and Protect AI and AI Agents 

Treat every AI agent as a critical identity, managing them with the same rigor as human users to avoid security gaps.  

The rise of AI increases the risk of agent sprawl and data leaks. These tools must be secured against emerging threats.  

The good news is that you can use the same zero-trust principles for both human employees and AI agents and manage them with the same tools. You can add advanced controls, including monitoring how agents interact with outside services, setting limits on internet access, and stopping sensitive data from reaching unauthorized AI or SaaS apps.  

With Microsoft Intra Agent ID, you can register and manage agents using familiar Intra experiences. Each agent receives its own identity, which improves visibility and auditability across your security stack. Requiring a human sponsor to govern an agent’s identity and life cycle helps prevent orphaned agents and preserves accountability as agents and teams evolve. You can even automate lifecycle actions for onboarding and retiring agents using conditional access policies. You can block risky agents and set guardrails for least privilege and just-in-time access to resources.  

Microsoft Internet Access detects and secures risky or unsanctioned apps, protects against attacks, and prevents data leaks with network filtering and classification policies. Visibility over network activity lets you use AI agents safely, ensuring policy adherence.  

Extend Zero Trust Principles Everywhere With an Integrated Access Fabric Security Solution 

Identity systems manage credentials and access rights, but may miss network activity. Integrate identity and network access into your Zero Trust setup so they work through a single policy engine. This improves visibility and control over each user session.  

Many organizations use multiple identity and network solutions from different vendors, obstructing visibility. Attackers exploit gaps, using AI to automate phishing and increase breaches.  

A unified platform combines identity, network, and device data for consistent access controls, whether work happens in the cloud, on-site, or at the edge. Drawing on multiple sources, it better evaluates risk and continuously checks trust for real-time, risk-based decisions.  

Microsoft Intra secures access for AI, SaaS apps, internet traffic, and private resources by uniting identity and network controls under a single zero-trust policy engine. Microsoft Entra Conditional Access continuously tracks user and network risks and updates policies immediately when risk levels change, blocking access for users, apps, or AI agents as needed.  

With Entra, your security team sets policies centrally with assurance that they are enforced everywhere. These adaptive controls safeguard users, devices, and AI agents, closing security gaps and simplifying policy management.  

Strengthen Your Identity and Access Foundation to Start Secure and Stay Secure 

Start with a secure foundation using phishing-resistant credentials and strong identity checks to ensure only authorized people can access your systems even during authentication and recovery.  

A baseline security model sets minimum standards for identity, access, system hardening, and monitoring. Use controls like security defaults, Microsoft-managed conditional access, or Microsoft 365 baseline security mode. Move from passwords to passkeys for stronger, easier sign-ins. Use robust recovery and onboarding processes requiring government-issued identification and biometric checks to stop bad actors and AI impersonators.  

Microsoft Entra helps you enforce best practices, including using phishing-resistant credentials, which are authentication methods that protect against fraudulent login attempts for all accounts, and passkey rules. Most admins or users in regulated industries can use device-bound passkeys, such as physical security keys or codes generated by Microsoft Authenticator. Others can use synced passkeys, which are cloud-stored credentials for ease of use. Protect all admin accounts with phishing-resistant credentials and require new employees to set up a passkey before access. With Microsoft Entra Verified ID, you can add a live person check verifying that the user is present and confirm government-issued identification for enrollment and recovery.  

Combine access policies, device compliance, threat detection, and identity protection to further strengthen your foundation.  

Support Your Identity and Network Access Priorities With Microsoft 

The 2026 plan is clear. Use AI for rapid, scaled protection. Secures AI and agents. Apply zero trust with an access fabric solution and strengthen your identity foundation. These steps keep your organization agile and resilient. Evolving threats demand that you outpace advanced attacks.  
Sourcehttps://www.microsoft.com/en-us/security/blog/2026/01/20/four-priorities-for-ai-powered-identity-and-network-access-security-in-2026/ 

News Highlights 

  • Meta is collaborating with AM to speed up AI infrastructure expansion and quickly develop and deploy advanced AI models.  
  • AMD and Meta have signed a long-term partnership to deploy up to 6 gigawatts of AMD Instinct GPUs across multiple product generations.  
  • The first gigawatt based on AMD’s Helios Rack-scale architecture will ship in 2026, featuring a custom AMD Instinct GPU designed by Meta.  
  • AMD and Meta are strengthening their partnership by coordinating their plans for GPUs, CPUs, systems, and software.  

Santa Clara, California, and Menlo Park, California. AMD and Meta announced a 6-gigawatt agreement to power Meta’s next-generation AI infrastructure across multiple generations of AMD Instinct GPUs.  

The agreement builds on past collaboration and aligns hardware and software plans to serve Meta. The initial rollout in 2026 will use custom AMD Instinct GPUs, 6th-gen EPYC CPUs, and Helios rack-scale architecture developed with Meta for scalable AI infrastructure.  

“We are proud to expand our strategic partnership with Meta as they advance the boundaries of AI at unprecedented scale,” said Dr. Lisa Hu, Chair and CEO, AMD. “This multi-year, multi-generation collaboration across Instinct GPUs, EPYC CPUs, and rack-scale AI systems aligns our roadmaps to deliver high-performance, energy-efficient infrastructure optimized for NetA workloads, accelerating one of the industry’s largest AI deployments and placing AMD at the center of the global AI build-out.”  

Mark Zuckerberg, founder and CEO of Meta, said, “We are pleased to establish a long-term partnership with AMD to deploy efficient inference to compute and advance personal super intelligence.” This agreement represents a significant step for Meta as we diversify our compute resources. We anticipate that AMD will remain a valuable partner for years to come.  

AMD and Meta are expanding their partnership around EPYC processors. Meta has long used AMD CPUs and GPUs in its infrastructure. As AI systems grow, CPUs remain essential for efficiency and scale. Meta will use 6th-generation AMD EPYC CPUs and Verano, a new processor for specific workloads.  

As part of the agreement, AMD has granted Meta a performance-based warrant for up to 160 million AMD shares. These shares will be earned as Meta reaches certain milestones in purchasing AMD Instinct GPUs: initial shares vest after the first gigawatt shipment, with additional shares vesting as purchases reach 6 gigawatts. AMD must also meet certain stock price targets, and Meta must achieve specific technical and business milestones outlined in the agreement.  

This partnership supports strong revenue growth and advances our financial goals, said Jean Hu, AMD’s EVP, CFO, and Treasurer. Its performance-based structure aligns AMD and Meta on strategic execution and value creation.  

AMD and Meta are working together on hardware systems and software to build a global AI infrastructure. Their goal is to speed up AI innovation and deliver AI-powered services and experiences to billions of people.  

AMD Teleconference 

AMD will hold a conference call at 7:30 a.m. CT, 8:30 a.m. ET today to discuss this announcement. The live audio broadcast will be on the Investor Relations page at www.amd.com.  

About AMD 

AMD creates high-performance and AI computing solutions to tackle major global challenges. Today, AMD technology powers billions of experiences across cloud and AI infrastructure, embedded systems, AI PCs, and gaming, with a wide range of AI-optimized CPUs, GPUs, networking, and software. AMD offers complete AI solutions that deliver the performance and expandability needed for contemporary computing.  

About Meta 

Meta is working to shape the future of interpersonal connections using artificial intelligence and immersive technology. Since its launch in 2004, Meta has changed how people connect. Apps like Messenger, Instagram, and WhatsApp have helped billions of people worldwide. Now, Meta is moving beyond 2D screens to create experiences that foster closer connections and open new opportunities.

Source:  AMD and Meta Announce Expanded Strategic Partnership to Deploy 6 Gigawatts of AMD GPUs 

Google Cloud has introduced a new set of security controls to help organisations protect their data against mounting cyber threats. The update, published on Google Cloud’s security and identity blog, demonstrates the company’s commitment to helping businesses safeguard sensitive information across their distributed cloud environments. 

Companies that move their critical operations to the cloud now treat security as their primary focus rather than an afterthought. The latest controls enable organisations to better monitor their systems, control access to their data, and strengthen their defences against new security threats. 

Addressing a Changing Threat Landscape  

The introduction of these controls comes at a time when the threat landscape is rapidly evolving. Enterprises are experiencing cybersecurity threats that extend beyond individual incidents into ongoing, sophisticated attacks targeting their cloud infrastructure, identity systems, and data protection systems.  

According to Google Cloud’s broader security insights, attackers are using misconfigurations, weak identity controls, and visibility gaps as their main method to access sensitive systems. The structure of the cloud environment increases risk because organisations store information across multiple services and geographic regions.  

Organisations will use the new controls to meet their requirements for real-time data monitoring, management, and protection.  

Expanding Identity and Access Controls  

The primary objective of the update is to improve identity and access management capabilities. Organisations must create authentication systems that safeguard user credentials for their security identities to control resource access in their cloud environments.  

Google Cloud has developed access control systems that allow organisations to create customised permission sets that meet their operational requirements. The solution helps reduce the likelihood of attackers targeting accounts with unnecessary permissions. 

The update includes an important feature that enables organisations to continuously verify user access rights by monitoring changes in user behaviour and location information in real time. The method follows a zero-trust security framework, which requires all users and systems to prove their trustworthiness before accessing resources.  

Improving Data Visibility and Monitoring  

The update provides improved data tracking capabilities, which allow users to see how data travels through the entire system. Enterprises face difficulties when they attempt to monitor data access, sharing, and modification across their intricate cloud systems. 

The new controls enable organisations to monitor data usage patterns through enhanced monitoring features that provide better visibility. The system enables security teams to discover unusual activities while they investigate security incidents and track down possible security vulnerabilities. 

Google Cloud provides security teams with detailed log information and analytical tools, enabling them to shift from responding to threats after they occur to detecting threats before they happen.  

Strengthening Data Protection Mechanisms  

The update establishes enhanced data protection methods that go beyond access management and surveillance. The system now implements stronger data protection measures, including enhanced encryption, improved key management, and additional security against unauthorised access.  

Google Cloud uses encryption as its primary security mechanism, protecting data as it travels and while it is stored. The new controls build on this foundation by ensuring that encryption policies are consistently applied across different services.  

Data protection systems prevent accidental data breaches, which include unintentional information leaks. Organisations face substantial risks of data breaches because their storage buckets remain exposed to the internet without adequate protection measures. The updated controls aim to reduce these risks by providing clearer guidelines and automated checks.  

Supporting Enterprise Compliance Requirements  

Security measures for most organisations exist because they must meet their regulatory obligations. Data protection requirements must be followed by organisations operating in the healthcare, finance, and government sectors.  

Google Cloud has developed new security controls to help organisations meet their compliance needs through tools that enable them to demonstrate regulatory compliance. The system provides three main components, which include audit functions, policy enforcement tools, and reporting capabilities to help organisations meet their regulatory compliance needs.  

The update streamlines compliance requirements, enabling businesses to dedicate more resources to developing new products while still adhering to essential security protocols.  

The Role of Automation in Cloud Security  

The process of security operations management in cloud environments requires automated systems because they must handle security operations at their required standards, as they demand extensive operational resources and advanced technical capabilities. 

The new controls incorporate automated security features that detect risks, enforce security policies, and respond to security threats without human supervision. The system achieves better operational results by increasing efficiency while reducing the likelihood of mistakes.  

Automated systems deliver faster response times by helping organisations prevent minor security issues from escalating into major breaches.  

Implications for Enterprise IT Teams  

The update delivers advanced security systems that combine artificial intelligence with organisations data protection and monitoring functions.  

The system integration process simplifies operational tasks while providing users with complete visibility into security status. Teams can make better decisions because they have access to complete data instead of working with incomplete information. Organisations need to invest in employee development because cloud systems have become more complex to manage.  

Security as a Core Cloud Priority  

The current security controls demonstrate how organisations now treat security as an essential element of their cloud computing operations. The increasing dependence of organisations on cloud services requires them to implement security systems that can handle diverse protection needs.  

Google Cloud now implements security as a fundamental element that becomes part of its cloud infrastructure design. The system uses an integrated design that establishes security protection throughout all system components. 

What Comes Next  

As cyber threats evolve, cloud providers must continually update and refine their security measures. Google Cloud’s latest controls are one step in this ongoing effort.  

Future developments will likely focus on further automation, advanced threat detection, and deeper integration with AI-driven security tools. These advancements will help organisations. 

Source links – Cloud CISO Perspectives: New Threat Horizons report highlights current cloud threats 

Apple is increasing its use of on-device artificial intelligence to strengthen user privacy protection across its entire product ecosystem. The move reflects the company’s long-standing position that personal data should remain under user control, even as AI-driven features become more central to modern computing experiences.  

The update builds on Apple’s privacy framework, especially in areas like Siri. The company is shifting more processing to the device rather than to cloud-based systems. This approach reduces data transmission from the device while offering advanced AI functions.  

A Privacy-First Approach to AI  

Apple focuses on processing information through device-based methods, enabling it to handle the largest data volumes. The system requires transmitting data over the internet to remote servers that conduct the analysis.  

Apple uses local data storage to protect its system from external threats while reducing the risk of unauthorised access to data. The company has demonstrated that voice commands and users’ app usage patterns can be analysed without requiring cloud storage.  

This method is of great importance because AI technologies now operate across many daily activities, including messaging systems, search functions, personalised recommendation services, and voice-assistance tools.  

Siri and the Shift to On-Device Processing  

Siri is the main way Apple delivers on-device AI. The company works to ensure more voice requests are handled directly on the device rather than on external servers.  

The new system enables Siri to provide faster responses while providing better protection for user information. The system enables users to process their requests locally, as all web-based requests are unnecessary.  

Apple highlights improvements in how Siri handles user data, including minimising the amount of information it collects and using techniques such as random identifiers instead of personal accounts, performance, and privacy.  

The system faces difficulties because it must continue to perform well while maintaining access to cloud resources. The system needs both efficient hardware and optimised software to process data at local sites, enabling accurate, fast results.  

Apple needs custom silicon, which includes its Neural Engine, because this technology enables the company to achieve its operational goals. The chips enable the company to run advanced artificial intelligence models by processing machine learning operations directly on user devices.  

The system provides advanced features that protect user privacy, which Apple uses to create a competitive advantage against other companies.  

Reducing Data Collection and Storage  

Apple directs its data collection operations to avoid collecting and storing unnecessary information about users. The company processes data in real time to delete information after users complete their sessions, rather than creating comprehensive user profiles.  

The system protects against data breaches and unauthorised access through its security measures. Apple uses aggregation and anonymisation to protect user identity while still using data to enhance its services.  

Apple restricts its data storage practices to ensure its artificial intelligence systems conform to its overall privacy policies across the Apple ecosystem.  

Apple uses its core principles to extend on-device AI beyond Siri across its entire product ecosystem, including iPhone, iPad, and Mac. Local processing powers features such as predictive text, photo recognition, and app suggestions, which increasingly depend on this technology. The system protects personal information because it stores all user data, including messages, images, and usage statistics on the device.  

Deploying on-device AI across products establishes a unified privacy experience for users switching between devices.  

Implications for Users in the United States  

The United States market presents Apple with a unique value proposition, as American customers increasingly worry about data privacy and security. The company develops its solution to safeguard personal information by processing customer data locally.  

The world today places great significance on artificial intelligence, as it now forms an essential part of everyday human activities. The growing use of intelligent systems by users creates a need to implement privacy and security measures during these interactions. Apple’s approach to privacy protection will shape how customers expect products to function while pushing competitors to adopt similar privacy practices. 

Competing Approaches in the AI Landscape  

Apple’s major competitors use cloud AI systems, whereas Apple relies on on-device processing for its AI functions. The systems provide improved computational capabilities, yet they require users to gather more comprehensive data before operation.  

The different methods people choose to reveal how technology companies confront their fundamental industry conflicts. The first approach seeks to achieve optimal system performance through centralised data handling. The second approach enables us to decentralise operations.  

Apple believes that businesses can achieve a competitive edge through privacy protection, which users will increasingly demand as they become more informed about their data privacy practices. 

Challenges and Limitations  

On-device artificial intelligence systems offer benefits but also pose drawbacks. The processing power of local systems falls short of what cloud systems can deliver when handling complex tasks that require extensive resources.  

The limitations of device hardware include both its processing capacity and power consumption. The ongoing challenge involves maintaining efficient AI operations that do not consume excessive system resources.  

Apple must continue improving its technological solutions to strike the right balance between these requirements and its commitment to user privacy.  

The Future of Privacy-Centric AI  

The expansion of on-device AI shows that people now prefer computing systems that protect their private information. The data-handling methods used by everyday devices that incorporate AI technology will determine how much trust users place in them.  

Apple shows that companies can provide smart features through their products without collecting large amounts of user data. This model could become more common as regulations tighten and user expectations evolve.

Source:  Our longstanding privacy commitment with Siri

News Summary 

  • NVIDIA Nemotron 3 models enable AI agents to engage in natural conversation, perform intricate reasoning, and leverage advanced visual features.  
  • NVIDIA, ISAAC, GR00T, N1.7, Alpamayo1.5, and Cosmos 3 improve physical AI reasoning and actions for robots and self-driving vehicles. (GR00T stands for Generalist Robot Reasoning Observation and Ontology Transformer. VLA means Visual and Language Action, which refers to processing and linking visual input, language, and actions in AI systems). 
  • The Proteina Complexa model in N-Media, BioNeMo speeds protein drug discovery. It includes a new dataset of millions of AI-protected protein complexes, created in collaboration with Google DeepMind, EMBL, and Seoul National University in the United States. Quality.  
  • Companies like CodeRabbit, CrowdStrike, Cursor, Factory, ServiceNow, and Perplexity use NVIDIA open models for agentic AI. LG Electronics and Milestone Systems use them for physical AI. Novo Nordisk, Viva Biotech, and Manifold Bio use them for healthcare and AI.  

At GTC, NVIDIA announced the expansion of its model families, positioning these new models as foundational to the next generation of agentic physical and healthcare AI. This initiative is designed to help developers and scientists build intelligent systems that reason and act effectively in digital and real-world scenarios.  

Open models are essential drivers of global innovation. NVIDIA’s expanding suite includes Nemotron (Agentic Systems), Cosmos (Physical AI), Alpamayo (Self-Driving Vehicles), ISAAC, GR00T (Robotics), and BioNemo (Biomedical research), all of which are central to unlocking new abilities across industries.  

“Open source AI drives global innovation,” said Kari Vriski, Vice President of Generative AI Software at NVIDIA. NVIDIA’s open model families broaden intelligence across biology, robotics, and autonomous machines, empowering developers to build smart agents that advance both digital and physical industries.  

NVIDIA, NemoTron 3, Ultra, Omni, and VoiceChat Models Power AI Agents 

The NVIDIA NemoTron family now includes models for language, vision, voice, and safety, helping developers build specialized agentic AI.  

NVIDIA, Nemotron 3 multimodal models support natural conversation, intricate reasoning, and advanced skills for AI agents.  

  • NEMOTRON 3 ULTRA offers advanced intelligence to boost productivity. The NVF P4 format (a data format developed by NVIDIA for efficient processing and storage) on the NVIDIA Blackwell platform delivers 5 times greater efficiency. Key benefits include support for AI-native applications such as coding assistance, faster research, and complex workflow automation.  
  • NEMOTRON 3-OMNI integrates audio, vision, and language, enabling AI agents to efficiently extract actionable insights from videos and documents, aiding decision-making and saving time.  
  • NEMOTRON 3 voice chat enables real-time conversations where AI can listen and respond simultaneously. It brings together speech recognition, language processing, and text-to-speech into a single system.  
  • Nemotrons, safety models, and retrieval tools enhance trust in the multimodal system. They detect unsafe content in text and images, and agentic retrieval improves the accuracy of results.  

Langchain now uses NVIDIA, Nemotron models, and other NVIDIA Agent Toolkit software in its agent development platform. This helps businesses build, deploy, and monitor smart AI assistants that can automate complex tasks at scale.  

Companies such as Automation Anywhere, Code Rabbit, CrowdStrike, Cursor, Factory, Distil, GenSpark, Perplexity, and ServiceNow use NVIDIA NemoTron models for advanced agentic applications. Edison Scientific applies NVIDIA NemoTron in Kosmos, an autonomous AI scientist that supports over 50,000 researchers in completing hundreds of research tasks simultaneously, significantly reducing months of work to a single day.  

AI developers use NemoTron to create sovereign models for billions of people across languages and cultures. Organizations include AI Singapore, Bielik.AI, Indosat, Ooredoo, Hutchison, Linagora, Soofi, Stockmark, Trillian Labs, Viettel, and YTL AI Labs.  

NVIDIA released Nemotron personas: privacy-focused synthetic datasets based on census and demographic data. The France dataset generated with Pleias is now available, along with datasets for the US, Japan, India, Brazil, and Singapore. NVIDIA also accelerates self-driving development with new models and simulation tools, helping robots and vehicles reason and act in the real world.  

  • NVIDIA Cosmos 3 the first world foundation model uniting world generation, physical AI reasoning, and action simulation arrives soon to help physical AI in complex settings.  
  • NVIDIA ISAC GR00TN1.7 is an open source reasoning vision-language-action (VLA) model, where VLA stands for Visual and Language Action, designed for humanoids. It is now ready for actual use.  
  • NVIDIA Alpamayo 1.5 is a VLA model that boosts autonomous vehicle reasoning, offering navigation guidance, prompt conditioning, flexible multi-camera support, and adjustable camera settings.  

At GTC, NVIDIA CEO Jensen Huang previewed GR00T-N2, a next-generation robot foundation model based on Dream Zero research. GR00T-N2 completes new tasks in new environments over twice as often as top VLA models. It leads in Malmo Spaces and RoboArena for generalist robot policies and is expected by year’s end.  

Companies like HCL Tech, Johnson & Johnson, MedTech, Milestone Systems, Mimic Robotics, Skilled AI, Tulip, and Toyota Research Institute use NVIDIA Cosmos to accelerate physical AI training and video analytics. Humanoid LG Electronics Neura and Noble machines use NVIDIA ISAC GR00T N1.7 for deploying humanoid robots.  

Open Models Accelerate Healthcare and Life Sciences Research 

NVIDIA is advancing AI-driven discovery in healthcare and life sciences with open, multimodal-based models and datasets. These tools speed up biomedical research, drug discovery, medical imaging, and the understanding of scientific literature and life sciences, helping researchers develop new knowledge and model, design, and simulate biological systems at scale.  

Proteina-Complexa is a generative model for designing protein binders, speeding up structure-based drug discovery and therapy development. NOVO, Nordisk, Viva Biotic, and Manifold Bio use it to design and test proteins that bind to target proteins.  

NVIDIA worked with EMBL, Google DeepMind, and Seoul National University to expand the AlphaFold protein structure database, adding about 30 million protein-complex predictions, including 1.7 million high-confidence entries. This accelerates drug-target discovery and understanding of disease biology.  

NVIDIA also launched NVQSP, a GPU-accelerated simulation engine that allows pharmaceutical researchers to test many more treatment scenarios in computer models before clinical trials. In tests, it was up to 77 times faster than traditional single-threaded CPU simulations, letting some scientists analyze hundreds of treatment levels and patient groups in the time it used to take to simulate just a few.  

Availability 

Some NVIDIA open models, data, and frameworks are available on GitHub, Hugging Face, various cloud and AI platforms, and build.nvidia.com.  

Many models are also offered as NVIDIA NIM microservices. These enable secure, scalable deployment across any NVIDIA-accelerated infrastructure, from edge devices to the cloud.

Source: NVIDIA Expands Open Model Families to Power the Next Wave of Agentic, Physical and Healthcare AI 

ChatGPT now has over 800 million weekly users. This rapid adoption is accelerating the use of AI in workplaces and other settings.  

Historically, technologies like steam engines and semiconductors created economic value when scaled. Enterprise AI appears to be reaching this phase.  

We are pleased to present the State of Enterprise AI report, providing a comprehensive overview of how companies leverage AI, employee benefits, and how leadership translates experimentation into productivity and skill development.  

The analysis uses two new sources of data:  

  • Real-world usage data from enterprise customers of OpenAI.  
  • An OpenAI survey of 9,000 workers across almost 100 enterprises documenting patterns of AI adoption.  

We removed personal details and combined the data to protect privacy.  

AI Adoption Is Speeding Up and Becoming More Advanced 

More companies are using AI in new ways. It is changing the way teams work and how products are delivered.  

  • In the past year, weekly messages in ChatGPT Enterprise grew about 8×, and the average employee is sending 30% more messages.  
  • Use of workflows like projects and custom GPTs grew 19 times over this year, indicating a shift toward integrated, repeatable processes.  
  • Organizations now use 320 times more reasoning tokens. This shows that smarter models are built into more products.  

AI is used more for complex tasks. More employees are adopting it and doing advanced work.  

Growth Is Rapid Across Industries and Geographies 

AI is being adopted in every sector, but we see the fastest growth in:  

  • Technology, healthcare, and manufacturing are the fastest-growing sectors.  
  • Professional services, finance, and technology operate at the largest scale.  

Around the world, business customers are growing fastest in Australia, Brazil, the Netherlands, and France, each with year-on-year growth of over 140%.  

International API customers have grown by more than 70% in the past six months. Japan now has the most corporate API customers outside the US.  

Workers Are Seeing Real Benefits From Using AI 

Across surveyed enterprises, 75% of workers said AI has made their work faster or better. Many save 40 to 60 minutes a day, and heavy users save over 10 hours a week. AI is adding value in many departments:  

  • 85% of marketing and product users report faster campaign execution.  
  • 75% of HR professionals report increased employee engagement.  
  • 73% of engineers report faster code delivery.  

Importantly, AI is not just making work faster. It’s also helping people take on new types of tasks.  

  • Coding-related messages increased by 36% among workers outside technical functions.  
  • 75% of users report being able to complete new tasks they previously could not.  

AI bridges the gap between concepts and outcomes, empowering employees to realize their ideas regardless of background or technical expertise.  

Leading Users And Organizations Are Moving Ahead 

Our data shows the gap between top users and companies, and the average is growing.  

  • Top workers the 95th percentile send six times more messages than the average employee and use more advanced features.  
  • Frontier firms send 2x more messages per seat and show deeper integration of AI across teams. Leading companies send twice as many messages per user and have deeper AI integration across their teams, as users consume more intelligence and engage across more distant tasks  

AI is evolving rapidly. The main challenge now is preparing organizations to put it into practice.  

Looking Forward: AI Is Changing How Modern Businesses Operate 

The report helps organizations plan for better AI use by showing how top companies find value and achieve bigger results over time.  

We invite executives, operators, and builders to read the report and review its insights. We welcome your feedback on the questions it raises and those that may come up as we keep studying how organizations move from trying AI to using it for lasting, high-impact results. This is an ongoing report, and we will keep sharing what we learn as things develop.  

To see the full findings or discover how your organization can leverage AI responsibly, contact us today to start your AI journey. 

Source: The state of enterprise AI 

Microsoft is adding new AI features, such as Microsoft 365 Copilot and Windows 11 updates, to help people work more efficiently on complex tasks.  

Main AI Features That Improve Productivity 

Microsoft 365 Copilot, Microsoft’s AI-powered assistant, works with Word, Excel, PowerPoint, Outlook, and Teams to help automate tasks and provide intelligent suggestions.  

  • In Teams, you get smart meeting summaries, live transcriptions, and automatic task tracking.  
  • Outlook summarizes long email conversations and suggests replies, making inbox management easier.  
  • Word and PowerPoint draft proposals, summarize documents, and build presentations from simple prompts.  
  • Excel analyzes data, creates visual reports, and answers questions in plain language, such as “Show me last quarter’s top performing product.”  

Agent Workspace in Windows 11, currently in experimental mode, lets AI agents run in the background in their own secure sessions. These agents can perform tasks like file organization and task completion without constant user supervision, allowing you to focus on higher-priority work. These agents can access your documents, pictures, and folders to organize files and perform tasks independently.  

Copilot Pro and new Frontier features 

  • Subscribers receive early access to frontier features, including models that enable the creation of custom workflows.  
  • They also get higher limits for sophisticated tools such as DALL·E 3 image generation and in-depth research features.  

Microsoft Designer and AI Image Tools 

  • Users can create images, edit photos by removing objects or backgrounds, and generate visual content by describing requirements.  

Power Automate and AI Builder 

  • These tools allow anyone, even without coding experience, to set up AI-powered workflows like extracting data from invoices or sorting support tickets.  

Key Areas of Productivity Improvement 

  • 24/7 availability AI agents are designed for 24/7 availability to help employees and make teamwork smoother, adapting to work developments over time.  
  • Microsoft prioritizes trusted AI, keeping Copilot data secure within your organization. These updates were announced in late 2025 and early 2026. They reflect a shift toward smarter AI agents that can save users hours of manual work each week.  

The digital workspace is evolving rapidly. In March 2026, Microsoft introduced AI features across its products to make everyday work easier. Now, operating systems and office tools actively support task execution, the launch of the Frontier Suite, and the addition of GPT-5.4. Thinking models enable the process of more complex multi-step tasks beyond basic text generation.  

For professionals handling a lot of information, these updates reduce the mental effort required to switch between tasks and sources by integrating smart AI into Windows 11 and Microsoft 365. The software now works more closely with you.  

A New Era of Automated Workflows 

The biggest change in the 2026 update is that Copilot has grown from a simple chatbot to a true autonomous assistant.  

With Microsoft Agent 365, users can now set up digital teammates that handle entire processes from start to finish. Instead of needing AI for every step, you can give these agents a goal like “audit these supplier invoices against our procurement policy,” and they’ll work through Outlook, Excel, and SharePoint to get it done on their own.  

Work IQ is a new feature that helps AI understand your business context. It spots connections, remembers team decisions, surfaces content, and proactively brings up useful files, making drafts more tailored to your company’s data and style.  

Improving The Core Windows 11 Experience 

With the 2026 Windows 11 update, the new AI Explorer for an intelligent search tool lets you search your digital history using everyday language. Instead of searching for a file name, you can just say, “Find that chart about semiconductor trends I was looking for last Thursday,” and the system will check your browser history, screenshots, and documents to find it.  

A key part of this update is on-device processing enabled by neural processing units (NPUs), computer chips in new Copilot Plus PCs designed to speed up AI tasks. Features like live captions with real-time translation and Windows Studio effects run directly on your computer rather than in the cloud.  

This means you can stay productive even when you are travelling or when your internet connection is weak. Doing these AI tasks offline often speeds things up and keeps your data private, since sensitive information stays on your device.  

Making Communication And Joint Effort Easier 

Too many emails and meetings still slow people down, but Microsoft’s new updates seek to fix this. In Outlook, Copilot can now automatically handle meeting RSVPs. Check your calendar for conflicts and even write conditional replies that ask for an agenda before you commit.  

The new Edit with Copilot tool in the Outlook side panel lets you adjust the mood of your messages and quickly summarize long email threads. So, you can read a 20-email chain in just one paragraph.  

Microsoft Teams has also improved with the new Co-Work feature. In live meetings, the AI can join as a participant. You can mention it to look up data, create visualizations, or explain something from an earlier session. The meeting recap is now a dynamic dashboard that lists tasks, assigns them to the right people, and automatically updates project schedules in Microsoft Loop.  

Security and Governance with AI 

As AI becomes a bigger part of work, the shadow AI problem (when employees use unauthorized AI tools at work) is being managed with Microsoft Entra, an identity and access management system that controls who can use specific tools, and the new agent ID system, which assigns a digital identity to each AI agent. Now, every AI agent follows the same identity and access rules as human employees. This lets organizations expand automation safely, knowing that AI will respect permissions and keep sensitive information secure.  

With GPT 5.4 thinking, self-correction reasoning is now a key feature when working with complex spreadsheets in Excel. The AI checks its own logic and flags possible errors for unusual data before you even see the results. Such reliability is important in situations where a single mistake could have a significant financial impact.  

Gazing Forward: People and Machines Working Together 

We are heading to a future where computers don’t just need instructions; they understand what we want to do. As these AI features become standard, the line between our ideas and their digital results will get even thinner. Soon our PCs might not just wait for us to log in but start working before we do sorting through messages and planning our day. This future technology quietly helps us navigate and get our work done, so we have more time to think, explore, and create. 

Source: Microsoft Adds AI Features to Boost Everyday Productivity