The Tech Radar - Issue #19 (August 2026)

Kaggle’s AI Agents Intensive with Google brought learners together in a no-cost course to build and deploy the next frontier of AI.

Learn how new AI and agentic experiences across Google Ads and Google Analytics can simplify your marketing workflow.

Between chaotic levels of market fragmentation and economic volatility, marketing and communications agencies can no longer rely on the human intuition they’ve traditionally used to win clients and optimize their ad spend. WPP is replacing that guesswork with an AI-powered view of shifting market dynamics, giving brands predictive certainty that lets them invest with confidence while moving at the speed of the market. That’s the value of WPP Open , its agentic marketing system.

Google Gemini and Pixel partner with five global football clubs to elevate the fan matchday experience through AI and Smartphone Technology.

For financial institutions, operational resilience has long been embedded in regulatory and supervisory expectations — to say nothing of the high expectations of consumers. With the implementation of the European Union’s Digital Operational Resiliency Act (DORA), those expectations have become even more stringent, with more explicit, harmonized, and evidence-driven requirements.

Enterprise content management is experiencing its biggest architectural shift since the cloud migration era. For years, enterprises have stored trillions of gigabytes of critical data in Box: financial models, clinical trial protocols, M&A due diligence rooms, engineering schematics, and legal compliance playbooks. Up to this point, text-based search and retrieval-augmented generation (RAG) have successfully unlocked the vast narrative knowledge within these repositories, establishing a...

Here’s how you can use Google Search tools to study for classes and standardized tests.

Since announcing Google Antigravity in Gemini Enterprise Agent Platform at I/O in May, we’ve heard helpful feedback from our customers. Your developers want easy access to coding agents across surfaces. Your enterprise governance team wants security controls and license management. And your finance team wants pooled usage so that no prepaid token ever goes unused.

In any organizational behavior class, students will learn that effective delegation is among the most important skills for a seasoned leader. Getting meaningful work done involves careful coordination, starting with a subdivision of projects into manageable tasks, mapped onto the skills of the team, and assigned to the right people. At Google Cloud, we’re learning a similar lesson when it comes to building and deploying AI agents in enterprise workflows.

Few professions are as exacting as the practice of law. A team reviewing a contract or building a case works inside strictly privileged information, firm-specific playbooks, and a body of law that changes constantly. The work thrives on nuanced, professional judgment — and the systems supporting it inherit real obligations: ethical walls that cannot be crossed, matter permissions that cannot be flattened, and a duty of confidentiality that does not bend for convenience.

Protecting capital in today's markets requires immense speed and precision. A financial analyst preparing a deal memo works across licensed market data, internal models, and confidential client files. General-purpose AI lacks the real-time accuracy, verifiable data lineage, and strict security that financial institutions demand. While model intelligence is necessary, without deep integration into trusted financial systems, it is not sufficient.

Learn how to use Google Search tools to find home decor inspiration, shop for furniture, and tackle DIY projects.

Editor's note: A product image was updated after initial publication. As AI takes on more complex work, business leaders face a new challenge: enabling rapid innovation using agents while protecting their margins and budgets. To get a real return on AI, financial operations (FinOps) and cost management must evolve alongside technology, giving you clear visibility, proactive cost controls, and flexible payment models that fit your needs.

Book hotels and track airfares, plus view miles and rewards with AI Mode in Google Search.

When Pythian rolled out Google Cloud’s Gemini Enterprise across our 500-person company in 27 countries, the goal was simple: use our own company as a proving ground to discover how enterprise AI actually delivers ROI. What we found changed our strategy entirely. Since the rollout of Gemini Enterprise and our previous enterprise AI deployments, Pythian observed firsthand why so many enterprise AI initiatives stall out or fail.

Welcome to the first Cloud CISO Perspectives for August 2026. Today, Chris Betz explains why the AI era makes it more important than ever to lean into security fundamentals. As with all Cloud CISO Perspectives, the contents of this newsletter are posted to the Google Cloud blog . If you’re reading this on the website and you’d like to receive the email version, you can subscribe here . aside_block ), ('btn_text', 'Visit the hub'), ('href', 'https://cloud.google.

As enterprises increasingly adopt multicloud architectures, bring your own key (BYOK) has become a fundamental pillar for maintaining data sovereignty and helping protect critical cloud workloads. At the same time, quantum computing has rapidly advanced, and security teams need to re-evaluate how they securely transfer encryption keys across networks.

Securing infrastructure and services against a future cryptographically-relevant quantum computer has been a goal for Google for a decade, and we’ve dedicated ourselves to help developers by advancing open standards that can benefit everyone. As post-quantum cryptography (PQC) has matured, we’ve been rolling it out in our infrastructure for internal and customer-facing services. Today, we're sharing our updated Google Cloud roadmap to migrate to PQC by 2029 .

At Google Cloud, securing your data and business systems is our foundational commitment. We empower our customers with the tools, governance, and infrastructure needed to securely deploy workloads and maintain long-term trust. We approach security from a shared fate model , and we continuously work to proactively identify and mitigate potential threats before they can compromise your data and misuse your infrastructure.

The intersection of medicine and AI has led to remarkable innovations. However, developers now face the thorny challenge of building robust medical AI tools that have been tested and evaluated on diverse, real-world patient data while also protecting patient privacy. At Google Cloud, our approach combines strategic collaboration with Confidential Computing. To help protect both patient privacy and AI models during validation, we’re collaborating with MLCommons t hrough the MedPerf initiative .

Written by: Gabby Roncone, Wesley Shields Overview Google Threat Intelligence Group (GTIG) is tracking three distinct suspected Russian cyber espionage threat clusters abusing legitimate authentication flows to target individuals working in academia, aerospace and defense, governments and think tanks across Europe, as well as academia and think tanks within the United States. Examples of these techniques can be found in our previous blog on UNC6293’s phishing operations.

Written by: Alex Tselevich, Michael Maturi Introduction Adversarial misuse of AI has increased the risk of data theft and extortion events, because when proprietary source code is exposed, defenders must scramble to identify and patch vulnerabilities while attackers deploy machine-speed AI tools against them. By structuring the analysis process, enforcing skeptical validation steps, and injecting domain-specific human expertise directly into the pipeline, we’ve achieved a leap in efficacy.

Written by: Tyler McLellan, Austin Larsen Introduction Google Threat Intelligence Group (GTIG) continues to track UNC6671 actively conducting compromises leading to data theft extortion, despite the alleged announced retirement of the BlackFile extortion brand in May 2026. Telemetry and infrastructure analysis reveal that rather than disbanding, UNC6671 has diversified its operations across multiple extortion fronts including Redact, Pink, Helix, and Falcon.

Sheets canvas turns data into interactive dashboards, custom study trackers, seating charts, and more, all with a simple prompt.

Editor's Note: Our Future Mode series will give businesses insight into how Chrome Enterprise is approaching AI in the browser. Stay tuned for more blogs in this series. Future Mode Part 2: The foundation for securing agentic browsing Today, autonomous AI agents aren't just drafting emails. They’re navigating SaaS applications, synthesizing data across multiple tabs, and completing multi-step tasks on our behalf.

Get a jump on this semester by using Gemini in Google Workspace to organize your notes, track deadlines, prep for projects, and more.

Here are Google’s latest AI updates from July 2026...

To make informed decisions, businesses often need to connect their internal data with public reference data, to create a knowledge graph that connects real-world things and their relationships. However, bridging data from public and private worlds has traditionally been complex. Today, we are streamlining these connections with the general availability of Data Commons on Spanner Graph and the preview of the new Data Commons Platform to unify your private knowledge with knowledge graphs from...

Businesses want to quickly and safely deploy AI agents to drive revenue, mitigate risk, and optimize capital, all without disrupting mission-critical ERP systems. And to power AI agents, you need more than raw data: You need interoperable data products that act as a single, reusable source of truth, turning cryptic source system records into clear business terms. Today, we are announcing the general availability of Google Cloud Cortex Framework version 7 .

For too long, enterprises with legacy mainframe estates have been faced with a high-stakes dilemma: continue maintaining their mainframes, essentially kicking the modernization can down the road (fully aware that delayed action only compounds future technical debt), or perform "big bang" modernization with more unknowns and risks. At Google Cloud, we propose an alternative: a modernization strategy that leverages the power of AI, agility of the cloud and allows for iterative and continuous...

In a fast-paced digital economy, data is your most critical engine. Yet, many enterprises find themselves trapped in a costly paradox, spending over 100 hours a week building and fixing fragile, in-house ETL pipelines or wrestling with unpredictable third-party tools. Trusted by thousands of customers every single day , BigQuery Data Transfer Service (DTS) eliminates this engineering burden.

What’s the best way to recommend products to little-known users? We’ve spent our careers trying to solve this problem for major companies like Spotify and Priceline, and it’s why Sidd founded Malachyte , an AI-powered ecommerce recommendation platform. These days, consumers have come to expect content that feels personalized and relevant, and online services competing for their attention have no choice but to do this exceptionally well.

Managing network security in a multi-tenant Kubernetes environment typically requires balancing two distinct needs: developers need their microservices to communicate effectively, while platform and security teams must maintain compliance, prevent lateral movement, and establish cluster-wide guardrails. Historically, the standard Kubernetes NetworkPolicy has been the primary tool for this.

Most enterprises connect with their customers through a device. Whether it’s using a mobile app to order a product, contact customer service, view content, or manage their account, the customer experience depends on how well an app can run locally on the customer’s device. For this reason, building and testing applications across a wide variety of devices is critical for any enterprise launch that involves locally running components.

We are thrilled to announce that Google has been recognized as a Leader for the third year in a row in the 2026 Gartner® Magic Quadrant™ for Cloud-Native Application Platforms (CNAP) . We believe this placement in the Leaders quadrant validates our commitment to providing an accessible, developer-centric platform that accelerates onboarding and supports rapid prototyping across modern workloads.

AI agents are the ultimate insiders. We grant them permission to read emails, query databases, and trigger API calls. They don’t just retrieve information, they take action. Agents offer incredible potential for increased productivity and better customer experiences, but they also come with new security concerns. In our new State of AI infrastructure report , 79% of tech leaders cite security, governance, or operations as their most significant challenge to scaling inference.

Technology leaders are under mounting pressure to modernize infrastructure, control multi-cloud operational spend, and build data foundations for generative AI. However, the discovery required for that level of transformation can entail weeks of manual spreadsheet analysis, mapping in-house infrastructure, and reconciling siloed, piecemeal cost estimates across disparate teams and sources.

The reinforcement learning (RL) ecosystem is rapidly adopting Ray as the unified compute runtime for complex post-training workflows. Across Google Cloud, we see customers using Ray for workloads ranging from multimodal data pipelines to frontier RL. But as agentic and reasoning models evolve, a critical bottleneck has emerged: orchestrating secure, isolated sandboxes at scale to safely execute dynamic rollouts, code generation, and multi-turn tool interactions.

The internet connected billions of people and mobile devices, putting computers in every hand. Now, we’re in the middle of the next big technology shift, deploying millions of autonomous AI agents to work alongside employees and end users. Today, we announced new FinOps controls for Gemini Enterprise to help organizations manage project-level AI spend and eliminate token shock.

When databases fail and network paths falter, you still need your mission-critical cloud services to stay online. Yet guaranteeing high availability has become increasingly difficult because of the complexity of modern distributed systems. To help you maintain availability and reliability during adverse events, we’re announcing Fault Injection Testing in preview.

We continue to iterate on the Open Knowledge Format (OKF), an open specification that formalizes the LLM-wiki pattern into a portable, interoperable format. But a big question remains: How can you share and govern access to an OKF bundle across an organization? OKF v0.1 established a portable format for the context agents need: markdown files with YAML frontmatter, one required field, and five conventions. Then, OKF v0.

Uber has a lot in common with the cities it serves. Both are always changing and growing, both must carefully manage the resulting traffic to prevent congestion and sprawl. Uber has continuously evolved its technical strategies to manage its expanding network, and this careful planning and constant evolution helps ensure that application traffic across its entire platform runs smoothly.

Earth AI

Health & Bioscience...

Human-Computer Interaction and Visualization...

Generative AI...

Algorithms & Theory...

General Science...

Generative AI...

Health & Bioscience...

I’ve talked to developers, IT leaders, and builders who all ask the same question: How do we actually get agents into production? The answer isn't theoretical — it's hands-on. Whether it’s designing a system that allows your agents to interact with external data sources while maintaining strict security guardrails or creating self-optimizing supply chain workflows or whatever you can think up, we’ve got you covered.

Twenty years ago today, Jeff Barr wrote a blog post that launched the Amazon EC2 Beta . That single post introduced resizable Linux virtual servers in the cloud, billed by the hour, with one instance type ( m1.small ) in one Region (US East). It was minimal yet useful, and it changed how the world thinks about computing infrastructure. In 2021, Jeff covered the fifteen years of EC2 with the backstory and memorable EC2 launches.

During my time at AWS, I have always looked for opportunities to work with students. I have delivered over 50 talks at universities across the region, and watching the potential in the room is always a strong motivator. It reminds me of why I do this work, and that the students I meet today may well become our customers and collaborators tomorrow. That is why I am happy to open this week with Student Rewards on AWS Builder Center.

Last week, AWS contributors joined the OpenSearch and Valkey communities at Open Source Summit Korea 2026 and MCP DevSummit Seoul 2026 to meet open source developers and contributors. At the four-day event, community leaders and users of these Linux Foundation open source projects gathered to share knowledge, collaborate on solutions, and push the projects forward.

Last week, we brought together AWS Heroes from around the world to connect, collaborate, and celebrate the builders who go above and beyond for the AWS community. The AWS Heroes Summit, an invite-only annual gathering, brings global experts specializing in fields like AI, serverless, and containers together for direct collaboration, technical deep-dives, and feedback sessions with internal AWS product and service teams. Day 1 started with an inspiring fireside chat from AWS CEO Matt Garman.

When you move AI agents from prototype to production, the infrastructure challenges multiply. Your agents need to persist state across multi-step workflows that run for hours or days. They need to coordinate with other agents, share context, and sometimes access GPUs for specialized tasks. Amazon Bedrock AgentCore runtime microVMs provide a fully managed environment for invocations that can run for up to 8 hours and support stateful workflows through managed session storage.

Today, we’re announcing the general availability of vector search in Amazon DynamoDB . You can now store vector embeddings alongside your operational data in DynamoDB and run similarity searches directly against that data, without replicating it to a separate vector store. DynamoDB supports native vector search with single-digit millisecond latency at 99%+ recall, and is designed for any scale, even trillions of vectors.

Last week I had the joy of participating in Amazon’s “Bring Your Kids to Work Day” with my 7 year old son. We commuted together into the New York City office, his first real rush hour train ride, and spent the day exploring how Amazon uses AI, machine learning, and robotics to deliver packages to customers all over the world. Watching his eyes light up as he saw robots navigating a fulfillment center reminded me why so many of us got into technology in the first place.

Organizations in regulated industries such as financial services, government, defense, and healthcare restrict their sensitive workloads to isolated network environments with no access to the public internet. Until now, customers could restrict AWS Management Console access to authorized AWS accounts and corporate networks, but the console itself required internet connectivity. This was creating tension between operational convenience and network security controls.

If you’re running AI agents in production, Amazon Bedrock Guardrails protects the model boundary. But your agents also invoke tools, fetch external data, and communicate with other systems. That data flows outside the model boundary, where model-level guardrails can’t reach. You can extend guardrail coverage to those interactions using three validation checkpoints built with the Strands Agents SDK lifecycle hooks and Amazon Bedrock guardrails.

If you found time for a bit of vacation this summer, you might be in catch-up mode. Here’s a list to help: all the expert blog posts, new service capabilities, code samples, and workshops, in case you missed it, from July 2026. AWS Security Blog post This month’s AWS Security Blog posts covered AI agent security, supply chain protection, network firewall automation, DDoS mitigation, and compliance readiness.

A single alert from one security service tells you something happened. Read that signal alongside activity from other services and your own business context, and you will know whether what happened is part of a multi-stage attack. Consider a short sequence. An identity calls GetCallerIdentity from a source address it hasn’t previously used. Within minutes, that same identity runs a burst of List and Describe calls across several services, and some of them fail with AccessDenied .

This post announces the availability of a new independent assessment report available on AWS Artifact analyzing how Landing Zone Accelerator on AWS (LZA) can automatically deploy multi-account environments in Amazon Web Services (AWS) with Australian Government Information Security Manual (ISM) security controls coverage at scale. The report includes findings from an independent third-party analysis conducted by AWS Partner gwi.digital .

As firewall rule sets grow in complexity, security teams face a common challenge: manual log analysis is used to determine which rules are actively matching traffic and which are consuming capacity without being triggered. This lack of visibility creates operational and compliance gaps. Organizations with governance policies that require removal of dormant rules after a defined period have no mechanism to identify them.

Many teams now deploy AI agents that pull from Amazon DynamoDB tables, document repositories, software as a service (SaaS) platforms, and internal knowledge bases to answer questions and automate workflows. A key risk in these deployments is that the agent has no awareness of who’s asking, so it might return data the user shouldn’t see. If you’re using Amazon Bedrock AgentCore to build AI agents that access multiple data sources, you need each user to see only the data they’re authorized to...

When deploying AI agents with Amazon Bedrock AgentCore , organizations benefit from built-in modern support for OAuth 2.0, AWS Identity and Access Management (IAM) , and API key authentication through Amazon Bedrock AgentCore Gateway . However, some enterprise environments still use legacy authentication mechanisms such as HTTP Basic Authentication (Basic Auth) ( RFC 7617) .

Since February, we’ve grown AWS Security Hub Extended from 14 curated partners across 9 categories to 23 partners across 10. At Black Hat this month, 14 of those partners were at the Amazon Web Services (AWS) booth demoing live. Four of those partners delivered theater talks and ten were featured on SecurityLive streaming. We hosted a partner reception that brought our leadership together with partner executives to plan what comes next.

Amazon Web Services (AWS) is gradually introducing updates to the AWS Sign-In and sign-up experience to a limited number of customers. We’re sharing these changes so you will know what to expect as we gradually make the updated experience available to more customers. These updates include new options for creating and accessing AWS accounts. To support these options and provide a more consistent experience, we’ve redesigned the AWS sign-in page and refreshed the session selection page.

Today, we’re announcing that AWS Certificate Manager (ACM) will discontinue support for email-validated public certificates by September 30, 2027. If you use email validation for your ACM public certificates, you need to migrate to DNS validation before that date. This change aligns with the Certification Authority/Browser (CA/B) Forum’s industry-wide deprecation of email-based domain validation and gives you a full year to migrate ahead of the Forum’s March 2028 deadline.

When you build a new application or capability on Amazon Web Services (AWS) , you want to focus on what you’re building. Getting a service running almost always begins with AWS Identity and Access Management (IAM) . Many AWS services that act on your behalf need an IAM role, an identity the service assumes to access your resources with a defined set of permissions. You then author a trust policy so the service can assume the role, choose the permissions the workload needs, and attach it.

Organizations operating in Germany and across Europe increasingly need to demonstrate cloud security compliance under the Cloud Computing Compliance Criteria Catalogue (C5:2020) , published by Germany’s Federal Office for Information Security (BSI). Last year, we introduced Landing Zone Accelerator on AWS support for digital sovereignty and today we’re announcing the availability of a new independent assessment report available on AWS Artifact which evaluates how the Landing Zone Accelerator...

We’re launching the next chapter of our digital enablement program for Amazon WorkSpaces : the Amazon WorkSpaces Migrations Badge . Organizations are increasingly moving from on-premises VDI to the cloud. Your technical team needs the right expertise to plan, execute, and optimize these transitions for customers. The Migrations Badge validates your team’s ability to move Citrix , Omnissa Horizon , and other VDI workloads to Amazon WorkSpaces.

Learn how to build an automated evaluation pipeline for Amazon Connect AI Agents using DeepEval and Amazon Bedrock to meet Model Risk Management requirements. When you deploy an Amazon Connect Customer AI Agent that manages account operations and routes service requests, it becomes a model subject to formal governance. Before deploying any model that influences customer outcomes to production, it must undergo a Model Risk Management (MRM) review.

Processing inbound email attachments at scale involves extracting files, routing them by recipient, scanning for malware, and classifying content. This traditionally requires stitching together polling loops, event rules, and multiple integration points. Amazon Simple Email Service (Amazon SES) Mail Manager now provides two new rule actions that simplify this pattern. The Lambda action invokes AWS Lambda functions directly from rule sets, and the Bounce action returns rejection responses.

In a modern contact center, a customer is three sentences into explaining why her shipment never showed up. The agent, twelve hundred miles away in a spare bedroom that doubles as a home office, catches maybe half of it. Not because she’s a bad listener. Because the neighbor’s dog has strong opinions about the mail carrier, and those opinions are traveling straight through two walls and a headset mic. “Sorry, can you say that again?” Once is forgivable. Twice is awkward.

Your Amazon Connect contact center is running at 92% of its concurrent call capacity, and no service quota monitor is watching. The dashboard shows green. Agents are handling calls. Then one more call comes in, and the next 50 callers receive no response. Amazon Connect enforces quotas on more than 300 resource types and API rate limits. These quotas protect the service, but Amazon Connect doesn’t natively alert you when you’re approaching them. You find out when something breaks.

What you will learn: How Amazon Connect’s enhanced module nesting (up to five levels deep) and universal cross-flow compatibility enable you to build maintainable, reusable contact center workflows, illustrated through a real-world travel booking reservation use case. Introduction In November 2025, we announced three powerful new capabilities for Amazon Connect flow modules: custom blocks with JSON schema support for precise input/output control, versioning and aliasing for confident...

Authentication during chat is a balancing act: require it too early and you lose customers who need quick answers; skip it entirely and you face compliance challenges when conversations shift to account-specific topics. When customers start a chat in Amazon Connect Customer, they might begin with a simple question but then need account-specific assistance that requires identity verification.

The quiet exit The issue is resolved, but the customer won’t remember your company until the next time you give them a reason to leave. And when a competitor offers them a better deal next quarter, the customer will take it without hesitation. Because nothing in their interaction with your brand was so exceptional that it gave them a reason to stay. That is the quiet exit. No complaint, no escalation, just a pattern hiding in your data that most teams never surface.

AWS has been positioned as a Leader in both the 2026 IDC MarketScape for Worldwide Desktop as a Service (DaaS)* and Virtual Client Computing (VCC)** vendor assessments, evaluated on strategy and capabilities. We believe this recognition is a testament of the investments Amazon WorkSpaces has made to deliver secure cloud desktops that unlock real value for customers today and provide the foundation they need to prepare for what comes next, including AI-driven operations and agentic workloads.

AWS has been named a Leader in the 2026 Gartner Magic Quadrant for Desktop as a Service (DaaS) for the third consecutive year, evaluated on Completeness of Vision and Ability to Execute. We believe this recognition reflects our sustained commitment to building the cloud desktop that organizations can grow with, one that delivers operational value and security confidence today while providing the foundation for how businesses will need to work in an AI-enabled future.

Introduction Developers and engineers increasingly rely on tools that require hardware virtualization support – Docker Desktop, WSL2, Android Studio emulators, and AI agents such as Claude Cowork. Until now, using these tools on a virtual desktop meant choosing between self-managed infrastructure or asking users to work on local hardware outside of your managed environment. Nested virtualization on Amazon WorkSpaces Personal and Amazon WorkSpaces Core bundles solves this.

Development teams want cloud desktops that feel like local machines. Until now, that meant giving up containers. Today, Amazon WorkSpaces Personal supports nested virtualization. All WorkSpaces Personal and Core bundles, including Custom, support nested virtualization except on Value bundles, Amazon Linux 2, Windows Server 2016, or Windows 10. For the best experience, we recommend enabling it on Power, PowerPro, and General Purpose bundles, providing full Docker Desktop functionality, including.

Clone a repo, open it in your AI coding assistant, type “go,” and walk away with a working RCS agent. Creating an RCS agent on AWS End User Messaging normally means juggling 23 registration fields, three different CLI parameter types, brand asset requirements, and a multi-step approval process. An AI coding assistant can handle all of that for you. With AWS End User Messaging , you can create RCS agents that send and receive rich messages complete with your brand’s logo, colors, and verified...

A step-by-step walkthrough for setting up a Rich Communication Services (RCS) test agent, from brand assets to verified inbound messaging. If you’re still sending plain SMS, you’re leaving a significant experience gap on the table. SMS gives you 160 characters of unformatted text, no branding, and zero confirmation that your message was even read. Rich Communication Services (RCS) changes that entirely.

Sending mass email campaigns presents significant challenges for many organizations. Enterprises often spend millions annually on proprietary email systems that are inflexible and expensive to maintain. These legacy platforms can restrict sending capacity, offer limited control, and require costly licensing agreements. The challenges intensify when handling large-scale communications like automated notifications, bulk marketing campaigns, and system-generated alerts.

Introduction Modernizing SQL Server databases to Aurora PostgreSQL often stalls before it starts. Infrastructure setup, network configurations, credential sharing, and security reviews create weeks of friction before teams can even assess what the migration involves. With Offline Source in AWS Transform full-stack Windows modernization , you can skip those barriers and begin modernizing your Microsoft SQL Server databases to Amazon Aurora PostgreSQL-Compatible Edition (Aurora PostgreSQL) by...

The AWS Lambda Durable Execution SDK for .NET is now generally available. AWS Lambda now supports durable executions for .NET, joining the existing Python, TypeScript, and Java SDKs. You install the SDK from NuGet, write your workflows in familiar C#, and deploy them with the AWS Extensions for .NET CLI – the same tools you already use for Lambda functions today. Your multi-step processes that charge cards, wait for approvals, or call external APIs need to survive interruptions.

Meetup details: March 12, 2026 | Chicago, Illinois Chicago’s Amazon Quick User Group brought together innovators from leading enterprises to explore how generative AI and agentic workflows are transforming business intelligence (BI). The event featured the “Insight Weaver” modernization journey from HERE Technologies , live demonstrations of voice-enabled AI with Amazon Nova Sonic from Wavicle Data Solutions , and a hands-on workflow automation workshop by Amazon Web Services (AWS) with support.

Agentic AI workflows issue sudden bursts of database queries. SaaS platforms trigger batch jobs at unpredictable hours. Social media apps absorb viral traffic spikes. These workloads need a database that responds instantly when demand spikes. Aurora serverless is built for exactly this. Aurora serverless is an on-demand, autoscaling configuration for Amazon Aurora.

Your most sensitive data—patient records, financial data, classified documents—lives in a private Amazon Virtual Private Cloud (Amazon VPC) with no internet access, and for good reason. That network isolation is a deliberate security posture, not an oversight. The problem is that your AI agents need to reason over that data, and traditional networking approaches force you to choose between connectivity and isolation.

We’re excited to announce Managed Dashboards in AWS Billing and Cost Management (BCM) . Starting today, a collection of preconfigured, read-only dashboards appear automatically in your BCM Dashboards list. They are populated with your account data and ready to deliver actionable cost insights the moment you open them. No widget selection, no configuration, no layout decisions. You get five curated dashboards covering three layers of cloud financial visibility.

You can accelerate .NET application modernization with AWS Transform for full-stack Windows modernization —but there may be some follow on work. End-to-end modernization often involves post-transformation tasks to finalize your application for production readiness. By finalize , I mean validating, debugging, and completing your modernized application so that it is ready for use.

In an earlier post , we walked through how Amazon Managed Streaming for Apache Kafka (Amazon MSK) Replicator migrates external and self-managed Apache Kafka clusters to Amazon MSK. It replicates your topics and their configurations, keeps topic and consumer-group names intact, and synchronizes consumer-group offsets, so your producers and consumers can cut over on their own schedule instead of all at once. MSK Replicator now supports OAuth 2.

As organizations build data lakes that combine geospatial data, high-frequency event streams, and heterogeneous payloads, the limitations of older table formats become acute. Without a native geospatial type, coordinates require separate float columns (latitude/longitude) with no spatial predicates. Without nanosecond-precision timestamps, sub-microsecond event ordering is lost. Without a variant type, semi-structured data forces a choice between rigid flattening and untyped JSON strings.

This post is co-written with Oscar Mapfumo Sibanda from Picnic. Picnic is an Amsterdam-based tech scale-up that reinvents how people buy food. It isn’t a supermarket with a digital layer but a tech company that happens to deliver groceries. Picnic is engineered in-house: the customer app, the fulfillment platform, the supply chain, and the routing technology that guides a fleet of thousands of electric vehicles through the Netherlands, Germany, and France.

Modern cloud-native applications generate rich telemetry across metrics, logs, and deployment histories. When performance degrades, operations teams have the data, but the challenge is correlating signals across multiple tools quickly enough to minimize customer impact. Root cause analysis remains a largely manual process dependent on institutional knowledge and operator experience.

A little over a year ago, we made Amazon EVS generally available. It was a milestone for customers running VMware workloads who wanted more options in the cloud, while keeping the investments they’d already made in their people, tooling, and operational workflows. With Amazon EVS, you can run VMware Cloud Foundation (VCF) on Amazon EC2 bare-metal instances that integrate with your AWS environment.

Introduction Development velocity has reached new heights with AI-driven development tools and practices. Organizations are generating code faster than ever before. But that speed carries risk. Researchers Anderson, Parker, and Tan warned in MIT Sloan Management Review, “Legacy systems tend to carry hidden debt; layering AI-generated code on top of them creates additional tangled dependencies.

Razor Group is one of Europe’s leading ecommerce aggregators, operating 250+ brands across multiple global marketplaces. With a portfolio exceeding $400M in revenue, the company relies on data to power every critical business decision, from dynamic pricing and inventory optimization to advertising spend and supply chain orchestration. At the heart of this operation sits the Razor Operating System (ROS), a proprietary platform that processes 370M+ API calls monthly through 9,300+ data pipelines,.

Organizations that replicate data across storage locations for disaster recovery, compliance, or analytics need a way to detect when replication stalls, because without early warning, unreplicated objects accumulate silently and drive unexpected storage costs. Most teams rely on automated retention policies to clean up the source copy after a defined period, but when replication breaks due to a permissions change or misconfiguration, those policies might be unable to act on the affected objects.

This post was contributed by Martin Schuetz and Ruben Andrist from the Amazon Advanced Solutions Lab, and Romina Yalovetzky and Atithi Acharya from Global Technology Applied Research at JPMorganChase. Quantum researchers at JPMorganChase and the Amazon Advanced Solutions Lab are working together to explore how quantum technologies may help address complex optimization problems in finance and beyond.

Part of what makes AI agents so useful is their ability to interact with the external world by running tools. But these tool calls are also the source of the biggest risks when it comes to making agents safe to use. The best way to address these risks in a dependable and reliable manner is to put a layer of control at the tool-call boundary that regulates what an agent is allowed to do.

If you’ve ever built an MCP server or agent skill, you know that packaging it means adapting for one client, re-writing for another, and repeating that for every tool your team uses. Agent Plugins 1.0.0 is an open source, vendor-neutral specification that gives AI agent extensions a common packaging format so you can package an extension once and ship it to any client, including Kiro, VS Code, Cursor, or any tool that implements the spec.

When Bosch Mobility Platform Solutions set out to unify vehicle tracking across India’s fragmented spot logistics market, they faced a daunting reality: dozens of telematics providers, incompatible data formats, and thousands of concurrent tracking requests — all needing real-time resolution. The result was L.OS, a serverless platform on AWS that standardizes this chaos into a single visibility layer.

As AI applications scale from reactive bots to autonomous agents, their reliability is bound to the speed and accuracy of the data layer beneath them. The integrity crisis nobody is talking about There’s a quiet assumption baked into most AI architectures today regarding data layer consistency, and it’s costing companies more than they realize. The assumption is that the data your AI agent reads is the current state of reality.

AI agents built on Amazon Bedrock AgentCore let clinical trial teams make fast, accurate enrollment decisions while keeping clinicians in control through human-in-the-loop oversight. According to the Tufts Center for the Study of Drug Development , 80 percent of clinical trials miss their enrollment timelines, and each day of delay costs an estimated $500,000 .

Clario, part of Thermo Fisher Scientific, uses Amazon Bedrock to automate PHI (Protected Health Information) and PII (Personally Identifiable Information) detection across thousands of DICOM (Digital Imaging and Communications in Medicine) image slices in clinical trials. Each image slice may carry PII or PHI hidden in metadata tags, in custom vendor fields, or burned directly into the pixels.

Accounts move between organizations in AWS Organizations whenever a business changes shape. A merger folds one estate into another. A divestiture carves one out, and some companies run more than one organization by design. The moves take more care when AWS Resource Access Manager (AWS RAM) resource shares are involved. An organization-bound share trusts an account through its organization membership, so when the account leaves, AWS RAM removes that association.

The Centers for Medicare & Medicaid Services (CMS) estimate that prior authorization costs payers and providers $20–50 per hour and takes an average of 13 hours per week , adding up to hundreds of hours and tens of thousands of dollars per physician annually. For healthcare payers navigating Fast Healthcare Interoperability Resources (FHIR)-based compliance with the CMS Interoperability and Prior Authorization Final Rule (CMS-0057-F), the strategic question isn’t whether to comply.

Cloud learning is more effective when learners can apply what they have learned, compare approaches with others, and choose an experience that fits the moment. Sometimes a team needs a flexible challenge that participants can complete across a week or across time zones. Other times, a community wants the energy of direct competition, a live bracket, and a shared final. AWS Card Clash is a free, mobile-first Architecture Design Game on AWS Skill Builder.

Introduction As one of the world’s largest direct-selling beauty companies, Mary Kay supports millions of Independent Beauty Consultants across 40 markets around the world through a highly connected global digital ecosystem. These platforms power critical business capabilities – from order management and inventory visibility to commission processing and consultant engagement – helping entrepreneurs around the world serve their customers seamlessly.

Today, we’re excited to announce Build, Save, and Share for Lab Maker on AWS Skill Builder. With this launch AWS Skill Builder Team Subscription customers can now save their AI-generated custom labs, relaunch them with one click, and share them with their organization through a new Lab Creation Hub. Building custom labs is powerful. Sharing them is transformative.

How much to trust an AI agent is now a daily operational question. Agents read customer data, open tickets, process refunds, and delete accounts, yet most teams pick up a binary: full access or read-only. Full access is risky because agents fail unpredictably. Read-only leaves most of the agent’s value unused. The distance between what an agent could do and what an operator trusts it to do is the agent’s trust gap.

How Gallup turned 90 years of workplace science into an AI assistant that gives leaders personalized guidance in seconds, powered by Amazon Bedrock . Gallup delivers analytics and advice to help leaders and organizations solve their most pressing problems. With more than 90 years of experience and a global reach, Gallup has developed a uniquely deep understanding of workplace behavior and performance. However, this knowledge wasn’t centralized or delivered in context.

Financial services institutions (FSIs), including banks, payment processors, capital markets firms, and global insurers, typically begin their cloud journey in one AWS Region. They often choose the Region nearest to their primary operations. Over time, they build layers of complexity on top of that foundation: governance frameworks, security controls, networking architectures, identity federation, and compliance evidence pipelines, all tuned to one Region. Then the trigger arrives.

Our decision to wind down our contract providing OpenAI models to Cursor following its acquisition by SpaceX.

OpenAI and Thailand’s MHESI launch an eight-week accelerator helping 10 health, wellness, and education startups turn AI prototypes into trusted products.

A randomized study of more than 1,000 students examines ChatGPT, critical thinking, originality, and student performance on a real-world university assignment.

OpenAI is expanding its presence in Brazil, deepening engagement with developers, businesses, and communities to support AI adoption across the country.

OpenAI’s new report explores how students and educators use ChatGPT to make learning more continuous, with support that extends beyond the classroom.

ChatGPT for Teachers is expanding to 55 U.S. school systems, bringing secure AI tools, training, and support to over 100,000 more educators and staff.

OpenAI shares findings from the Hugging Face security incident and the steps we’re taking to strengthen AI model security, monitoring, and alignment.

Discover how loveholidays uses OpenAI Codex to make software development accessible across the business, helping teams turn ideas into products faster.

OpenAI CFO Sarah Friar explains how advances across chips, compute, models, and products compound to deliver more useful intelligence at greater scale and lower cost.

Jalapeño is a custom inference chip from OpenAI that delivers faster, more power-efficient AI inference, with higher throughput and lower latency for modern models.

OpenAI banned Russia-origin accounts using AI to promote a fake Israel-based think tank and a “sovereignty” index praising Russia and criticizing the West.

Use the Admin plugin for ChatGPT Work and Codex to analyze workspace usage, manage members and permissions, adjust limits, and act on admin requests.

GPT‑5.6 is now available in Kiro, helping developers plan, build, review, and test software with better price-performance.

Introducing Intelligence Age, a new OpenAI blog exploring how transformative AI could reshape power, governance, the economy, and individual freedom.

With a fixed deadline and design resources committed elsewhere, Stampli used Codex and ChatGPT Work to compress weeks of launch production into days.

OpenAI reaffirms Zero Data Retention for eligible API customers and previews Private Safety Processing for advanced AI safety without compromising data privacy.

Replit introduces Free Mode, powered by GPT-5.6 Luna, so anyone can turn ideas into working software without worrying about token costs.

ChatGPT Ads is expanding to 31 European markets. Learn how advertisers can reach people as they explore, compare options, and make decisions.

OpenAI launches an initiative to strengthen democratic oversight of AI in national security, supporting government institutions with tools, training, and expertise.

OpenAI and CodeAI are partnering to help students build AI literacy, think critically about AI, and develop the skills to use and shape it responsibly.

OpenAI is strengthening monitoring, alignment, and security for frontier AI models. See how new safeguards are guiding the pace of model development.

ChatGPT for Teens helps teens learn, think critically, and use AI with confidence, with stronger built-in protections, healthy-use features, and additional controls for parents.

NVIDIA teams use ChatGPT Work to reduce manual tasks, connect fast-moving signals, and scale successful workflows globally.

Asana used OpenAI Codex to replace an outdated testing system in two weeks, completing work expected to take five years for about $12K.

AI is reshaping cybersecurity for attackers and defenders alike. Learn how OpenAI is strengthening its defenses and what security teams can do now.

OpenAI joins PORTS-Pike project, expanding community investment and supporting thousands of Southern Ohio jobs...

OpenAI funds 14 independent projects exploring new AI policy ideas to expand economic opportunity and strengthen societal resilience in the Intelligence Age.

Learn how startups use GPT-5.6 to build faster, more cost-efficient AI agents with smarter model selection and new Responses API capabilities.

Preview Ultrafast, a new OpenAI API service tier that runs GPT-5.6 Sol up to 14× faster. Powered by Cerebras, it delivers up to 750 output tokens per second.

OpenAI appoints Dali Rajic as Chief Revenue Officer to lead its global revenue organization and help businesses realize the full value of AI.

OpenAI research reveals how enterprises are adopting agentic AI, using ChatGPT and Codex, and how frontier firms are pulling ahead in AI adoption.

See how RingCentral uses ChatGPT Work and Codex to accelerate AI product development and centralize operational intelligence across engineering and operations.

OpenAI and AWS are making Daybreak cybersecurity capabilities available through Amazon Bedrock to support enterprise security workflows.

OpenAI begins testing ads in ChatGPT to support free access, with clear labeling, answer independence, strong privacy protections, and user control.

OpenAI sent Governor Greg Abbott a letter outlining its commitment to responsible AI infrastructure in Texas. The letter supports reliable, transparent growth that benefits Texans.

Model ML uses GPT-5.6 Sol to carry finance work from research and analysis through editable, traceable PowerPoint decks and Excel workbooks.

OpenAI CFO Sarah Friar shares five lessons for building an AI-native finance function, from automated forecasting to stronger controls and AI ROI.

Approved Daybreak partners can use OpenAI’s frontier cyber models to deliver authorized, governed cybersecurity services to customers.

Meet GPT-5.6-Cyber, OpenAI’s cybersecurity-specific model available through Daybreak Red for authorized vulnerability research, exploit validation, and security testing.

Premium seats are now available on ChatGPT Business, with 5x more usage, no five-hour usage limit, and flexible seat options for every teammate.

Virgin Atlantic is accelerating research, product planning, and decision-making with ChatGPT Work, helping teams connect signals across the customer journey.

The enterprise marketing team at Zapier uses ChatGPT Work to reduce the number of drop-offs in its lead funnel, build campaign assets, and automate reporting.

OpenAI is sharing preliminary cybersecurity evaluations for Astra and the steps we’re taking to strengthen safeguards and security controls.

Discover how HSP GRUPPE uses ChatGPT Enterprise to boost productivity, improve work quality, and create more capacity for tax advisory and client service.

ChatGPT introduces improved GPT-5.6 Sol with better accuracy and consistency, plus expanded access for free users and unlimited everyday chats with GPT-5.6 Luna.

OpenAI and the American Psychological Association advance evidence-based guidance, resources, and safeguards for responsible AI use and youth mental health.

New OpenAI Signals data shows how people use ChatGPT worldwide, with country-level insights on adoption, usage trends, and evolving behavior.

OpenAI explains recent third-party cybersecurity evaluation incidents and outlines new safeguards to strengthen AI model testing and evaluation.

Explore new education plugins for ChatGPT Work and Codex that help K–12 teachers, college educators, and students learn, teach, research, and build.

OpenAI addresses Apple’s baseless lawsuit, corrects claims about its employees, and shares messages documenting what happened.

GPT-Live enables continuous voice interaction with AI, using a turnless speech model and low-latency architecture for faster, more natural conversations.

Circles uses the OpenAI API and Codex to power AI-native telco experiences, increasing ARPU by 22%, reducing churn by 9%, and improving development efficiency.

OpenAI shares new results on long-standing open problems in mathematics and theoretical computer science, including advances in geometry, cryptography, and complexity.

In our Engineering Energizers Q&A series, we spotlight the engineering leaders driving innovation across Salesforce. Today, we meet Herman Kwong, EVP of Software Engineering, whose team developed DREAM (DDoS Response and Mitigation), an AI-powered DDoS mitigation platform protecting Salesforce’s global cloud infrastructure against machine-speed attacks. DREAM reduced time to first mitigation by 5x across a shared cloud that processes roughly 20 trillion transactions annually.

By Ali Nahvi, Akshit Behera, Yvonne Fan, and Melissa Ramey. Your models are accurate. Your pipelines are healthy. Your dashboards are working. And your system is still failing its users. Imagine thousands of dashboards and more than 20 applications continuously producing machine learning predictions, alerts, scores, and recommendations. Nothing is technically broken. Yet the people consuming those signals still have to determine which ones matter, what they mean, and what to do next.

Imagine an AI coding agent generating a large pull request filled with AI-generated code. Everything looks exactly as it should: The build passes. Every automated test is green. Code review finds no major issues. The change is merged. Later, your team discovers the agent quietly misinterpreted an ambiguous requirement near the beginning of the implementation. Every decision that followed was internally consistent. The tests validated the implementation. The reviewer approved the diff.

Imagine deploying a production AI agent that confidently tells a customer, “I have processed your refund.” The customer leaves satisfied. The conversation looks perfect. Your monitoring shows no obvious errors. Then someone checks the billing system and discovers the invoice is still open. The refund tool was never called. Nothing actually happened. As AI agents move from chatbots into production workflows that issue refunds, schedule technicians, update customer records, and manage campaigns,..

In our Engineering Energizers Q&A series, we highlight the engineering minds driving innovation across Salesforce. Today, we spotlight Zac Taylor, a software engineering architect on the Trusted Services team. Zac and his team are building Security Center, an Agentforce -powered visibility tool that helps accelerate AI-powered security investigations and remediation workflows.

By Rounak Mehta, Adrian Eng, Sandeep Singh, and Kishore Kanchapalli. In our Engineering Energizers Q&A series, we highlight the engineering minds driving innovation across Salesforce. Today, we spotlight Adrian Eng, Director of Product Management, who helped lead efforts to standardize product telemetry across Salesforce so engineering teams can automatically generate trusted product adoption metrics.

By Priyanka Singla, Aaron Stockton, and Vincent Poon In our Engineering Energizers Q&A series, we highlight the engineering minds driving innovation across Salesforce. Today, we spotlight Priyanka Singla, Senior Software Engineer on our Argus team, who operates and evolves the internal observability platform ingesting approximately 4 billion metrics per minute for thousands of engineering teams.

By Pallavi Rajan Udmalpet and Janhavi Deshpande . As enterprises accelerate secure AI adoption with Agentforce and Data 360 , organizations across healthcare, banking, government, and critical infrastructure face a sobering reality. The bottleneck to enterprise AI adoption is no longer model capability, rather, it is governance. Agentforce can only reason on the data available to it, but patient records, financial transactions, taxpayer information, and operational systems often sit behind...

Organizations today face increasing pressure to align workforce strategies with rapidly changing business needs. Whether planning for future skills, addressing talent gaps, or improving organizational agility, leaders need more than data. They need clear, actionable intelligence that helps them make informed decisions with confidence. As a result, people analytics is evolving from a reporting function into a strategic capability.

TrustRadius has announced its Top Rated awards for 2026, and SAP Customer Experience ( SAP CX ) is proud to share that SAP Sales Cloud, SAP Service Cloud, and SAP Commerce Cloud have each been recognized as Top Rated products in their respective categories. In a landscape crowded with vendor-sponsored rankings and paid analyst reports, TrustRadius stands apart. These awards are driven entirely by verified customer reviews: no paid placement, no analyst opinion.

Large transformation programs are complex by nature. But after years of working with difficult transformation programs, we have found that organizations often make that complexity much harder to manage than it needs to be. Complexity is not always the problem. Unmanaged, and often self-created, complexity is. A practitioner’s perspective Some years ago, after helping turn around a large global SAP Customer Experience program, I was contacted by several customers asking a surprisingly simple...

A favorite vacation spot. A childhood neighborhood. A beloved pet. A lifelong hobby. For someone living with dementia, as memory and communication become more difficult, these details can turn into powerful prompts, sparking memories, stories, and joyful moments of connection. Memory Lane Games has long used frustration-free, quiz-style games to create these connection moments for people living with Alzheimer’s and dementia.

Artificial intelligence has entered a new phase. The conversation is no longer about whether organizations should adopt AI. Solve complex business challenges and drive digital transformation with SAP Learn how Across industries, businesses are already experimenting with AI to automate tasks, improve productivity, and create better customer experiences. The real question now is how do we move from experimentation to enterprise-wide transformation that delivers meaningful business outcomes?

For more than a decade, SAP customers have been wrestling with a familiar challenge: how to move from legacy SAP ERP Central Component (SAP ECC) environments to SAP S/4HANA without creating transformation programs that are prohibitively expensive, complex, or time-consuming. Get started with a modular ERP solution designed to bring built-in AI to your core business processes Learn how Now, agentic AI could fundamentally change that equation, creating a different model for SAP transformation:...

At a time when many boardrooms are still asking whether AI will disrupt software revenue, go-to-market (GTM) leaders are asking a more practical question: how can AI help us find and keep more customers? Capture business-wide AI value with speed and confidence Learn how The honest answer is that most GTM teams don’t have an AI problem. They have a decision-flow problem. I’m seeing this across some of the world’s largest enterprises.

At NASA, a moonshot is not a metaphor. It is an operating model. Returning humans to the Moon—and building the foundation for an enduring presence in deep space—requires thousands of people, multiple government agencies, international partners, commercial providers, and highly complex systems to work together with extraordinary precision. Unify every mission-critical function to drive government efficiency and innovation Learn how During the SAP NOW event in Washington, D.C., Dr.

WALLDORF — SAP SE (NYSE: SAP) today announced that NTT DATA has selected SAP SuccessFactors solutions and SAP Business Data Cloud, integrated with Joule, SAP’s AI orchestrator, to power the next phase of its global People and Culture transformation. Turn HR into a strategic growth engine with AI Learn how NTT DATA is a $30+ billion global leader in AI, digital business and technology services, serving 75% of the Fortune Global 100.

AI agents are writing code and translating legacy applications for use in the SAP cloud. Sonja Liénard, head of ABAP platform at SAP, explains what this means for the ABAP programming language and ABAP platform. In an interview, Liénard talks about the evolution of SAP’s proprietary programming language and ABAP platform, and discusses what the innovations announced at SAP Sapphire will mean for customers.

Despite rapid advancements in frontier AI models, many enterprise problems remain hard to solve. The challenge goes beyond just accessing better AI-generated suggestions. Solve complex business challenges and drive digital transformation with SAP Learn how It’s about making consequential decisions inside complex processes that require a deep industry specific context of data, regulations, human workflows, and processes.

Building a resilient, future-ready supply chain is one of the most complex challenges organizations face today. For more than 50 years, SAP has helped organizations navigate supply chain volatility by connecting planning, execution, and business processes across the enterprise. We are proud to share that SAP has been positioned as a Leader in the inaugural Gartner® Magic Quadrant™ for Supply Chain Management Suites *, a recognition that, in our view, reflects not just where we are today, but...

IDC has named SAP a Leader in the IDC MarketScape: Worldwide AI-Enabled Order Orchestration and Fulfillment Applications for Retail and B2C 2026 Vendor Assessment . Run orders intelligently by connecting channels, inventory, and fulfillment systems with real-time insights Learn how The recognition reflects SAP’s continued commitment to innovation in order management and the confidence customers place in SAP Order Management Services to run some of the world’s most complex, high-volume order...

Organizations often look at AI, automation, or new service tools as the starting point for service-led growth. In reality, service-led growth starts with a business model. Technology can help scale a service business, but it does not define how value is created, delivered, or monetized. Service-led growth is one of the seven macro trends within Autonomous CX, SAP’s vision introduced at SAP Sapphire in 2026.

Lemvigh-Müller, a 180-year-old Danish wholesaler of industrial building material, technical, and steel products, has built an AI use case that reads incoming business documents—automatically and within seconds. For Lemvigh-Müller, an efficient supply chain isn’t a nice-to-have—it’s the business model. “Our company is low margin, and we are living from a very efficient supply chain,” says Frederik Aakerlund, CIO of Lemvigh-Müller.

Artificial intelligence is changing procurement at two speeds. It can compress work that once took days into minutes, helping teams analyze spend, review contracts, identify supplier concerns, and guide employees toward compliant purchases. At the same time, every new AI-enabled action creates another vulnerability where poor data or weak oversight affects a business decision.

For audiences, Cirque du Soleil is about wonder: gravity-defying performers, breathtaking costumes, immersive music, and moments that feel almost impossible. But behind every performance is something just as remarkable: a highly complex global business operation. It reinvented circus arts and became a world leader in live entertainment, performing for more than 365 million spectators in 90 countries.

Many organizations are currently undergoing an SAP S/4HANA transformation, and some are already investing in AI technology. But how do new technologies actually work in day-to-day operations? Between technical deployment and actual adoption, there is often a gap. What is needed goes beyond tools—it requires enablement, communication, and organizational change management that puts people first. Experiences from SAP customers show how this can succeed.

What if you, as an SAP consultant, could resolve issues faster, work more independently, and stay ahead of AI-driven innovation—all in just over 60 minutes of learning? Picture this: You are an IT manager at a mid-sized enterprise running SAP. A critical issue surfaces midweek. Your team scrambles to fix the problem, searching through documentation, reviewing the multiple support channels available, and monitoring the situation to ensure the issue does not snowball further.

Salling Group is northern Europe’s largest retail group, serving 15 million customers each week in its more than 2,100 stores across Denmark, Germany, Poland, Estonia, Latvia, and Lithuania. Move your ERP to the cloud so it can power AI to drive real business outcomes Learn more The company’s history goes back more than 100 years, and what began as a small textile shop in Aarhus, Denmark, is now an international retailer with €12 billion in revenue.

Digital transformation is often associated with cutting-edge technologies like AI. But according to Mirela Siani, real transformation starts somewhere much less glamorous. Provide reliable, affordable, and sustainable energy to your customers Learn how “We started by fixing the basics,” said Siani, Transformation and Technology director at Ipiranga, one of Brazil’s largest fuel distributors. Ipiranga operates almost 6,000 service stations nationwide.