The Tech Radar - Issue #18 (July 2026)

Google, the New York Jobs CEO Council and Urban Assembly hosted an AI summit for 150 education and industry leaders.

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

We’re announcing new capabilities in Managed Agents in Gemini API so developers can build reliable, production-ready agents.

You’ll be able to securely link and interact with your go-to services directly in AI Mode.

For the second consecutive year, Google has been named a Leader in the Gartner® Magic Quadrant™ for Conversational AI Platforms. Google received the furthest and highest in positioning on the "Vision" and "Execution" axes and is now ranked #1 in three out of four Critical Capabilities Use Cases. We believe this recognition reflects our continued investment in frontier AI research, enterprise infrastructure, and helping customers move AI from experimentation into production at scale.

Earlier this year, we introduced Gemini Enterprise Agent Platform , where you can build, scale, govern, and optimize agents. Today, we’re sharing 13 demos that walk you through what Agent Platform can do. Each one teaches a concept, a pattern, or an architecture you can put to work immediately. The best part? You don't have to follow them step-by-step.

We are living in the golden age of the weekend AI side project. Thanks to agentic engineering and LLMs, the time to go from a blank IDE to a functional local application has dropped from quarters to hours. You can build your wildest ideas over a cup of coffee. But inside an enterprise ecosystem with rigid infrastructure and millions of users, vibe coding hits an invisible wall.

Welcome to The Blueprint, a new feature where we highlight how Google Cloud customers are tackling unique and common challenges across industries using the latest AI and cloud technologies. We hope to inspire others looking to innovate in their work . Founded in 2018, Voicify reimagines the traditional phone call with the goal of transforming every call into a seamless and engaging experience.

It might sound counterintuitive, but Search's AI tools can actually help you make the most of your time offline whether you want to book concert tickets or find the perf…

These AI features can help you craft a menu, design a tablescape, and handle other party-planning tasks.

We’re announcing even more new capabilities in Managed Agents in Gemini API so developers can build reliable, production-ready agents.

As Best Buy expanded its use of Google Cloud for advanced analytics and AI, its technology teams faced two significant scaling challenges: Mitigating risk and managing administrative friction when syncing thousands of backend users from Microsoft Entra ID. The retailer solved both problems and paved the way for a massive cloud expansion by implementing Google Cloud's Workforce Identity Federation .

Welcome to our latest Gemini Enterprise Agent Platform deep dive, a practical walkthrough where we’ll teach you how to build real-world, production-ready agents starting from step 1. If you haven’t already, tune into our livestream to guide you through the entire agentic lifecycle and...

Since we launched Gemini Enterprise Agent Platform a few months ago, we’ve seen inspiring progress from businesses and builders alike. To stir up development, we’ve also shared 13 demos that can walk you through the versatility and power of Agent Platform, and 20 questions you can ask your teams about building a solid agentic foundation. Meanwhile at Google Cloud, our teams have been hard at work to make more features available and continue delivering on our promise to give you better ways to...

Editor’s note : Want to keep up with the latest from Google Cloud? Check back here for a monthly recap of our latest updates, announcements, resources, events, learning opportunities, and more. Since launching the Gemini Enterprise Agent Platform a few months ago, we’ve watched businesses move from basic experiments to serious, production-grade builds. We want to make it even easier — and more secure — for you to scale those systems.

Security leaders are now expected to protect business growth and clearly articulate security value to their board of directors, in addition to managing risk. While translating technical defense into measurable financial returns can be challenging, Mandiant Consulting can help you bridge the gap. Organizations that engaged with Mandiant Consulting reported an average annual benefit of $4.3 million, driving a 268% three-year ROI, with a payback period of just 4.

At Google Cloud, we are committed to providing public sector organizations around the globe with cloud technology that is highly flexible, scalable, and built with market-leading standards for data protection, sovereignty, and security. We understand that for public sector organizations in the European Union, confidence in data protection is not just a preference — it’s a prerequisite. Today, we’re excited to announce a major milestone that reinforces this commitment for Google Cloud.

Background Today, in coordination with the FBI, Lumen, and others, Google took action against the NetNut residential proxy network, also known as Popa. This action builds on our disruption of the IPIDEA proxy network that took place in January 2026, and is a continuation of Google’s objective to dismantle malicious residential proxy networks. Actions Taken As a part of this disruption we took the following actions: Disabled Google accounts and associated Google services used by NetNut for...

Being more proactive continues to be a leading goal for security organizations. As AI accelerates the pace of vulnerability discovery and exploitation, organizations will rely on the personalization of their security investments to help prioritize their defenses. To help you be more proactive by matching your real-world exposures with real-time adversary activity, we’ve begun integration efforts between Google Threat Intelligence and Wiz Attack Surface Management (ASM).

Startups are at the forefront of tackling some of the world’s most complex challenges, especially in cybersecurity, where new ideas and adaptability are always needed. These companies are embracing AI as a powerful tool, enabling them to scale their impact. Google believes that enabling the next generation of AI-native cybersecurity startups will have a positive impact across the globe.

At Google Cloud, we take our role in the financial ecosystem very seriously. We firmly believe that operational resilience is essential to driving and sustaining responsible innovation. Today, we mark a milestone in our ongoing commitment to the financial sector that’s directly relevant to our customers in the U.K. On July 10, the U.K. Treasury designated Google Cloud EMEA as a critical third party (CTP) to the U.K. financial sector under the CTP regime .

How should your security team manage shadow AI? Workloads deployed by developers without formal registration can often evade traditional security scanners, because organizations are reluctant to slow down development and compromise stability by demanding privileged Daemonsets, kernel-level access, and manual pod-spec edits. To break this deadlock, today we are open-sourcing k8s-aibom .

Written by: Jules Czarniak Introduction As highlighted in the Mandiant M-Trends 2026 report , the mean time-to-exploit (TTE) has dropped to -7 days, meaning vulnerabilities are often exploited a week before a patch even exists. To keep pace, many security teams are exploring how to integrate large language model (LLM) agents into their codebases, development environments and continuous integration and continuous delivery (CI/CD) pipelines for automated vulnerability discovery and remediation.

Welcome to the first Cloud CISO Perspectives for July 2026. Today, Francis deSouza, COO, Google Cloud and President, Security Products, explains the crucial role that deep context plays in creating an AI advantage for defenders. 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 .

As adversarial AI threats accelerate attacks on code, security teams must counter them with machine-speed defenses that can automate code remediation and fight AI with AI. CodeMender is our managed code security agent, and starting today, we're bringing its code scanning and remediation capabilities directly to you in preview. CodeMender offers access to our generally available models via Gemini Enterprise Agent Platform , or it can be deployed as a core component of AI Threat Defense .

Update (July 30): A table listing the new names of select prominent threat actors was appended to this post. Introduction Today, Google Threat Intelligence Group (GTIG) will begin rolling out a unified naming schema for tracking threat actors. This new naming taxonomy represents an effort to standardize tracking across platforms and public reporting. Why are we Adopting a Different Naming System?

Even as machine-speed attacks dominate the headlines, Mandiant’s view from the frontline reveals that the vast majority of successful intrusions still stem from fundamental human and systemic failures. This operational break-down shows up pointedly in research from the M-Trends 2026 report. Exploits remain the most common initial infection vector for the sixth consecutive year at 32%, voice phishing surged to second place at 11%, and prior compromise was the number one confirmed vector for...

With cryptographically relevant quantum computers (CRQC) on the horizon, transitioning to quantum-safe digital signatures is critical to safeguarding long-term data integrity and authenticity. Organizations are steadily recognizing this urgency. For example, the U.S. government announced an update to the timelines by which departments and agencies must transition to quantum safe digital signatures.

Written by: Kelli Vanderlee, Stuart Carrera For years, the cybersecurity industry's understanding of software supply chain compromise has been anchored by a few watershed events, including Russian cyber espionage actor ICE RELIC’s (formerly known as APT29) 2020 compromise of SolarWinds and North Korean cyber espionage actor UNC4736's 2023 compromise of 3CX .

Welcome to the second Cloud CISO Perspectives for July 2026. Today, Chris Betz, CISO, Google Cloud, and Alicja Cade, Senior Director, Office of the CISO, Google Cloud, explain what boards of directors need to know about AI security and how to prepare their organizations for security governance and business agility in the AI era. As with all Cloud CISO Perspectives, the contents of this newsletter are posted to the Google Cloud blog .

Gemini Omni and personal avatars in Google Vids make video creation easier than ever.

AlloyDB is an AI-native database—it isn’t just a passive data store, it intelligently understands and processes your data. With AlloyDB, you get industry-leading vector and hybrid search, near 100% accurate natural language-to-SQL capabilities to build conversational agents, tools to enable you to build with your agentic IDEs of choice , and the ability to bring the intelligence of foundation models like Gemini directly to your data through AI functions .

Editor’s note: SOCRadar is a leading cybersecurity company that provides threat intelligence to businesses worldwide. As the volume of cyber threats continued to grow, SOCRadar needed to modernize its data infrastructure to deliver faster insights to its customers. By migrating from PostgreSQL to AlloyDB, SOCRadar achieved a 20x performance boost, reduced operational overhead, and is now better positioned to innovate and grow.

For years, enterprise AI has been synonymous with conversational AI — the customer service bots and digital assistants we interact with every day. But today, the market has shifted. We’ve officially moved from moving from AI that answers through simple chats, to AI that takes action, automated workflows, and executes complex tasks on its own. While this unlocks entirely new use cases, there’s a catch: it places significant stress on the underlying infrastructure we’ve relied on in the past.

Deploying the Gemini Enterprise app across an organization marks a transformative leap forward in workforce productivity, providing employees with an amazing, high-performance suite of agentic AI tools, search-grounded assistants, and specialized solutions like NotebookLM. As adoption grows to a large scale, it can introduce a critical administrative scale challenge: how to audit, govern, and extract insights from a massive volume of telemetry without getting bogged down in manual overhead.

AlloyDB powers enterprise-grade search for some of the largest organizations, providing robust hybrid search capabilities that combine text, vector, and keyword searches into a simple ranked SQL query. And with our recent launch of RUM index support , AlloyDB customers now have even more powerful full-text search capabilities at their fingertips. However, database developers often face limitations when indexing continuous text in logographical languages like Chinese, Japanese, and Korean, where.

Editor’s note: Today we hear from IDC on the results of its 2026 AI in Networking Special Report Survey exploring the enterprises' concerns about networking infrastructure to support the rise of agentic AI in their organizations. The survey was sponsored by Google Cloud. Enterprises are moving quickly on AI pilots, but the move from pilot to production remains uneven.

Have you run into problems migrating your products from one model to the next? Upgrading to the latest AI models is rarely simple. For engineering teams, model updates whether migrating to an entirely new model or updating to a newer checkpoint within the same model family, like moving from an earlier Gemini version to Gemini 3.5 — often require a slow and costly process of testing, proving quality, and manually evaluating new responses.

The math behind reinforcement learning (RL) post-training for large language models (LLMs) is notoriously unforgiving. As frontier AI labs push the boundaries of reasoning and coding models using RL post-training algorithms like Group Relative Policy Optimization (GRPO), they routinely hit hard architectural and infrastructure constraints. While much of the industry's focus remains on acquiring raw accelerator capacity, infrastructure efficiency is equally critical for achieving the high...

When we introduced the Open Knowledge Format (OKF) in June 2026, we asserted that the context that agents need (table schemas, metric definitions, runbooks) should live in a format, not in a proprietary service, and not scattered across unstructured text blobs. Accordingly, OKF v0.1 started simple: just markdown, YAML frontmatter, and a handful of conventions. The strong response and contributions from the developer community informed our focus for the next version.

Traditional data replication techniques often struggle to deliver the data freshness that modern workflows require. To help organizations overcome this challenge, SAP and Google Cloud are announcing that SAP Business Data Cloud Connect for BigQuery is now generally available. As the next phase of our long-standing partnership , SAP BDC Connect for BigQuery gives you zero-copy access to data products across SAP Business Data Cloud and BigQuery – reducing silos, preserving valuable business...

Increasing the adoption of generative AI across the enterprise requires you to do more than deploy a generic chatbot with a custom wrapper. Interacting with business-critical databases demands absolute trust, strict governance, and deep grounding in enterprise semantics. Over the last year, Conversational Analytics (CA) in Google Cloud has moved from isolated experiments to scaled, enterprise-wide deployments.

Today’s data lakehouse is no longer mere data repository, but increasingly a system of action, actively executing tasks via always-on, autonomous AI agents. Rather than waiting for static reports, these agents run continuous, real-time reasoning loops, monitoring supply chains, flagging anomalies, and executing business workflows. To scale this model, AI agents need to access your entire data estate and the right context to understand what data to use and when.

In today’s agentic era, modern cloud applications are evolving from a set of passive tools to fleets of autonomous digital workers that reason, plan, and take action across a wide range of tasks. For platform engineering teams designing these environments, the simplest approach is often to deploy an agent on to an open-source framework like OpenClaw and Hermes running on a virtual machine (VM).

Database security traditionally relies on a fragile balance between the granular control developers need and the administrative overhead of managing thousands of individual database passwords. Between managing AI agent access, rotating static credentials, handling employee on-boarding and off-boarding, and auditing access logs, passwords remain an operational tax — and a potential security vulnerability.

At Google, AI is a soup-to-nuts endeavor. Obviously, we make leading AI models like Gemini and Nano Banana. We incorporate AI into the tools you use every day (think Gmail, BigQuery, AlloyDB, Google Cloud Code and Google Cloud Assist). We make software frameworks to help you build with AI, like Gemini Enterprise Agent Platform, JAX, or MaxTest. And we co-design the powerful infrastructure platform that runs underneath it all, including a broad range of standard compute, accelerators like TPUs...

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If you’re reading this, you’ve likely already done the hard work to prove your qualifications with a Google Cloud certification. And good for you — research shows that’ll help you get ahead. Certified individuals report more responses from recruiters, faster promotions, and higher salaries. In fact, 81% of organizations say certifications from Google Cloud increase their confidence in a job candidate's knowledge or ability.

Last week I had the privilege of spending three days in São Paulo with technical builders from across Latin America, brought together for a regional tech event full of deep-dive sessions, hands-on workshops, and conversations with customers and partners. What struck me most wasn’t any single session, it was the energy of a technical community that so rarely gets to be in the same room.

Last week, my team visited Seoul to meet AWS Korea User Group (AWSKRUG) leaders. AWSKRUG is the largest cloud developer community in Korea, with 20 meetup groups organized by topic and area that collectively host over 100 events each year, primarily in Seoul. My team regularly visits countries across the Asia-Pacific region, listens to feedback from user group leaders, and works to support their communities.

AWS Builder Center turned one year old last week. Launched on July 9, 2025, the platform has grown from a community hub with Wishlist voting, community profiles, and a toolbox into a full ecosystem with sandbox environments, workshops, Spaces, and a Builders’ Library. To mark the anniversary, Rick Suttles published a full feature timeline covering everything shipped over the past year: AWS Capabilities by Region (1,500+ services across 37 Regions), Spaces for community-created groups, workshops.

A couple of editions ago I wrote about what I find so energizing about working with startups. Last week I got a fresh dose of it: I spent a few days with the AWS Startups team, listening to stories of founders talking about the problems they’re actually solving. One story that stayed with me came from Marco Negreiros, founder of EyeCare Health , a Brazilian healthtech expanding access to eye care.

As organizations embrace AI-powered analytics, the value of a natural language (Text2SQL) answer is only as good as the business context behind it. We’re entering a phase where semantic richness (table and column descriptions, and relationships) must flow directly from where it’s authored in upstream data catalogs and semantic tools into the AI products that serve end users. Products like Amazon Quick can no longer operate in isolation.

As your AI agents move from prototype to production, the challenges shift from getting them to work to keeping them fast and efficient. In Part 1 of this series, we walked through debugging two common agent failures: infinite loops and tool invocation errors. Those scenarios dealt with agents that were broken. In this post, we tackle a different challenge: agents that work correctly but perform poorly.

Today, we’re releasing the HIPAA Security Rule on AWS: Technical Safeguards Implementation and Readiness Guidance . This helps covered entities and business associates configure, implement, and evidence compliance with the HIPAA Security Rule Technical Safeguard requirements (45 CFR §164.312) when building healthcare workloads on AWS. The HIPAA Security Rule’s Technical Safeguards (§164.

AI coding agents are part of the developer toolchain. Tools like Kiro and Claude Code generate features, tests, and code refactors from natural-language prompts. A single agent can open dozens of pull requests (PRs) across your repositories in an afternoon. That productivity comes with a trade-off: agents optimize for task completion at machine speed with no understanding of your organization’s risk.

Amazon Inspector is an automated vulnerability management service that continually scans Amazon Web Services (AWS) workloads for software vulnerabilities. The vulnerability management capabilities of Amazon Inspector are powered by an asset inventory engine known as the Amazon Inspector SBOM Generator (inspector-sbomgen), a standalone command-line tool that produces a software bill of materials (SBOM) from container images, directories, archives, local systems, compiled binaries, and more.

Amazon is sharing new findings about how a threat actor linked to the Democratic People’s Republic of Korea (DPRK) is targeting open source software libraries, the shared building blocks that companies around the world use to develop applications. Amazon Threat Intelligence has linked several recent compromises of popular Node Package Manager (NPM) libraries to the same DPRK-linked threat actor, a connection that hasn’t been publicly reported until now.

If you use and install packages from npm or PyPI, the first hours after a package is published are the riskiest because scanners can’t analyze packages before publication. Recent supply chain events affecting NodeJS and Python packages have been detected and removed within hours. However, while those packages were available to the general public, it’s possible that they were installed by users, creating the potential for a security incident.

Choosing the right cryptographic key management service on Amazon Web Services (AWS) starts with understanding the difference between AWS Key Management Service (AWS KMS) and AWS CloudHSM . Both provide key storage backed by a hardware security module (HSM) but serve very different needs. AWS KMS is a fully managed service that integrates with all AWS services and all AWS Regions, making it the right choice for most key management workloads.

Amazon Web Services (AWS) is excited to announce that the latest version of Information Security Registered Assessors Program (IRAP) report (Phase 1a – full assessment) is now available through AWS Artifact . An independent Australian Signals Directorate (ASD) certified IRAP assessor completed the IRAP assessment of AWS in June 2026. The new IRAP report includes four additional AWS services that are now assessed at the PROTECTED level under IRAP.

July 29, 2026 : We’ve updated this post to clarify the AWS Firewall Manager migration path. Application-layer distributed denial of service (DDoS) attacks are difficult to detect because they closely resemble legitimate traffic. HTTP request floods are now among the most common vectors targeting web applications, using valid-looking requests that blend in with normal user activity.

AWS Security Assurance Services is announcing the release of the Cloud Security Alliance (CSA) Compliance Guide on Amazon Web Service (AWS) , a new resource that maps the 17 control domains and 207 control objectives of the Cloud Controls Matrix v4.1 (CCM) to AWS services and recommended implementation practices. The guide is intended to help organizations using AWS plan, implement, and evidence the controls relevant to their CCM scope, including those pursuing or maintaining CSA STAR...

When an administrator introduces a rule change in AWS Network Firewall and network connectivity is disrupted, pinpointing the cause requires inspecting multiple points in the traffic path. The firewall gives you stateless and stateful rule engines, domain rules, and routing to the firewall endpoint inside your Amazon Virtual Private Cloud (Amazon VPC) . A network drop looks the same from the workload no matter where it started.

Black Hat 2026 (Aug 1-6, 2026) brings together over 22,000 security practitioners, researchers, and CISOs who build, break, and defend enterprise infrastructure. They’re security professionals who push the limits of offensive and defensive security and demand proof over promises. As frontier security models like Mythos reshape the enterprise landscape, they need security that operates at the same speed as the events they face.

AWS WAF classifies web traffic by attaching metadata to each request it evaluates. Managed rule groups such as AWS WAF Bot Control and AWS WAF Fraud Control account takeover prevention (ATP) attach labels that describe what they found. A label can record that a request came from a known bot category or that it matched a credential-stuffing pattern. You can forward that metadata to your origin as request headers, which gives your backend visibility into the decisions AWS WAF made at the edge.

Picture a global manufacturer that finds a critical defect in one of its products. Within minutes, a hundred things have to happen at once: orders paused, suppliers and customers notified, inventory reallocated, regulatory paperwork prepared, executives briefed. Even a year ago, that meant pulling hundreds of people into virtual war rooms, each logging into a dozen applications to work through one task after another. Increasingly, the first responders won’t all be people.

Organizations across industries struggle with labor-intensive verification and data collection processes that require manual follow-ups, phone calls, and email exchanges. These workflows consume time and resources, often taking days to complete verification tasks while generating high operational costs. Manual processes involve multiple touchpoints, repeated attempts to reach contacts, and documentation requirements that create operational bottlenecks and limit business agility.

Introduction Siemens Global Business Services (GBS) provides shared services and business process support across more than 80 countries, handling finance, procurement, HR, sales operations, and digital services for all Siemens business units. Their inbound contact operations manage a wide range of topics — from order and delivery management to employee lifecycle queries and technical support requests. GBS serves internal stakeholders and external customers at scale.

Introduction For NatWest Group , one of the UK’s largest banks, delivering consistent customer experience consistently is both a business priority and a regulatory requirement. Maintaining uninterrupted service across customer experience operations is fundamental to the bank’s ability to meet its business continuity and disaster recovery obligations. NatWest originally deployed its customer experience platform on Amazon Connect Customer in the AWS Europe (London) Region.

In this post, we walk through Claw Boutique , an open-source reference architecture that connects a web storefront, WhatsApp, email, and Telegram into a single OpenClaw-driven ecommerce experience on AWS. Buyers interact through WhatsApp and a web store. The shop owner manages everything from Telegram, where an artificial intelligence (AI) agent processes restock, refund, and order commands.

Marketing teams running large-scale campaigns often send the same message across SMS, WhatsApp, and email regardless of how each customer engages or how many messages they’ve already received that week. This pattern wastes budget on channels customers ignore and pushes promotional content toward frustrated or message-fatigued customers. A MarketingSherpa study found that 45% of consumers who unsubscribe from email marketing cite messages being too frequent as the reason.

Why the breadth of your integration architecture determines the capability of your AI agent. Introduction Autonomous resolution through agentic integration is redefining how contact centers operate. Advances in AI reasoning, open integration standards, and composable service design have converged to make something previously impossible now practical: AI agents that autonomously resolve complex, multi-system customer issues in real time.

Introduction The Amazon Connect Customer data lake gives contact centers a central, zero-extract, transform, and load (zero-ETL) location to query contact records, agent performance, conversational analytics, and other data types. However, enabling access requires navigating multiple AWS consoles to associate datasets, accept AWS Resource Access Manager resource shares, configure Lake Formation permissions, and create resource link tables using AWS Glue —a process that becomes repetitive and...

Introduction The Multilingual Support Challenge In today’s global marketplace, contact centers face a critical challenge: providing exceptional customer service across multiple languages and dialects. Traditional approaches require hiring multilingual agents or creating language-specific queues, leading to: High Operational Costs: Recruiting and training multilingual agents is expensive and time-consuming Limited Scalability: Difficult to support new languages or dialects as business expands...

Businesses rely on email to deliver critical notifications, nurture customer relationships, and grow revenue. But their success depends on more than just sending the right message. It depends on emails getting delivered to the inbox and ultimately getting read. When emails land in spam or go unread, the business impact is real and measurable: missed engagement, eroded customer trust, and lost revenue.

Every day, Amazon Customer Service handles millions of customer contacts across Amazon and its subsidiaries, spanning multiple regions including North America, Europe, South Africa, and Asia Pacific. Managing contact flows at this scale across multiple Amazon Connect instances to accommodate Retail and Amazon subsidiaries required a scalable, programmatic approach. The team set out to maintain consistency and support rapid innovation while maintaining high-quality customer experiences.

Fanatics Commerce is a leading designer, manufacturer, and retailer of licensed consumer products, including fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods. Whether it’s a championship jersey or a last-minute gift, fans trust Fanatics to deliver and that trust extends to every digital touchpoint along the way. Every order confirmation, shipping notification, and account update represents a moment of connection with a fan.

One-time passwords (OTPs) are the backbone of modern user verification, from account creation to wallet additions, to password resets. But for businesses operating globally, delivering OTP messages reliably across dozens of countries is complex. It has traditionally meant navigating a maze of country-specific registrations, originator provisioning, and carrier compliance requirements. AWS End User Messaging Notify changes that equation entirely by removing the complexity of global OTP delivery.

Only about 5% of AI initiatives successfully ship to production at scale. At Amazon, we’ve learned firsthand what separates that 5% from the rest. In this post, we share a tactical playbook for moving your AI pilot into production while keeping your customer and agent experience completely intact. Many organizations excel at launching initial artificial intelligence (AI) prototypes.

We frequently hear from customers that many Amazon WorkSpaces deployments run on operating systems (OS) that are near end-of-life. These older environments, paired with legacy streaming protocols, limit access to the latest features, security updates, and long-term support. Modernization is more than a protocol change. It is an opportunity to upgrade the OS, adopt Amazon DCV for optimal performance, and build automation to keep your fleet current.

Organizations delivering content on a global scale rely on distributed edge networks to cache and serve billions of requests daily. These architectures depend on highly aggressive Time-To-Live (TTL) configurations to maximize performance and minimize origin load. On a cache miss, the network falls through to the origin to retrieve the requested content. At this scale, maintaining data freshness is a critical challenge.

TL;DR What if you could go from raw Amazon S3 server access logs to a complete security dashboard without building a custom pipeline? The dashboard below is deployed using the CloudFormation template provided in this post. Figure 1: Amazon S3 Server Access Logs Security, Compliance & Audit Dashboard Until now, getting security visibility from Amazon S3 server access logs meant managing destination buckets, building custom parsing pipelines, and stitching together disconnected tools for alerting.

AWS CloudFormation helps you model and provision cloud infrastructure as code using JSON or YAML templates, or through tools like the AWS Cloud Development Kit (CDK) and AWS Serverless Application Model (SAM) . Whether you create stacks directly, use change sets for preview, or deploy through CI/CD pipelines and AI agents, the speed of your deployment cycle directly impacts how fast you can iterate.

Amazon Relational Database Service (Amazon RDS) for Db2 makes it straightforward to set up, operate, and scale IBM Db2 deployments in the cloud , automating time-consuming administration tasks such as provisioning, backups, software patching, and monitoring. Many organizations run IBM Db2 on AIX or Windows to support large-scale transactional and analytical workloads.

Your Java application passes every test, deploys without error, and then throws a ClassNotFoundException in production after a routine operating system update. No code changed. No dependency changed. What happened? Java workloads running on Amazon Elastic Container Service (Amazon ECS) and Amazon Elastic Kubernetes Service (Amazon EKS) can encounter two categories of production issues related to classpath and resource allocation: Nondeterministic classpath resolution that silently changes which.

Migrating your AWS Load Balancer Controller (LBC) Ingress resources to the Gateway API by hand is tedious and error prone. You need to rewrite annotations, path rules, and TLS configuration, and a mistake can disrupt the production traffic. The Ingress-to-Gateway API migration toolkit for LBC removes that risk by giving you a guided, validated path you can take at your own pace.

Organizations managing IoT at scale face a critical business challenge: every hour of equipment downtime costs thousands in lost revenue, while untapped sensor data represents missed opportunities for operational optimization. Research shows that digital maintenance and reliability transformations can increase asset availability by 5–15 percent and reduce maintenance costs by 18–25 percent ( McKinsey ), translating to significant recovered revenue annually.

Demand for generative AI has outpaced the supply of GPUs. Procurement delays and capacity blocks that sell out months ahead now gate how fast enterprises can ship AI workloads, and cost pressure compounds the problem at production scale. AWS Trainium gives customers a second path: Amazon EC2 Trn2 instances deliver 30 to 40 percent better price-performance than comparable GPU-based instances, and because AWS designs the silicon, customers gain access to capacity built and scaled by AWS directly.

Today, we are announcing delivery to streaming tables on Apache Iceberg for Amazon Managed Streaming for Apache Kafka (Amazon MSK) Express brokers , a fully managed capability that continuously materializes your streaming data as queryable Apache Iceberg tables on Amazon S3 Tables , a capability of Amazon Simple Storage Service (Amazon S3). With delivery to streaming tables, you no longer need to deploy, scale, or maintain Kafka connectors, Flink jobs, or custom consumers to make your streaming.

Cloud cost variability presents a unique challenge for FinOps and Finance professionals. Monthly variance analysis may reveal cost trends too late for timely course correction, while daily cost tracking may produce limited actionable insights. Implementing a FinOps weekly checkpoint is a proactive approach to catch spend trends sooner and generates more meaningful insights for your monthly variance analysis.

Introduction When AWS Systems Manager Patch Manager reports failures across hundreds of managed nodes spanning multiple accounts and regions, operations teams face a time-consuming investigation: logging into each account, correlating events, analyzing logs, and determining whether failures share a common root cause. A single patch cycle failure can consume hours of engineering time.

Introduction As organizations scale their AWS footprint across multiple accounts and Regions, operations teams increasingly rely on Amazon CloudWatch Metrics Insights alarms with GROUP BY to monitor entire fleets from a single alarm. When this single alarm tracks hundreds of resources, a critical operational question arises: how do you ensure that every individual breach is captured and acted upon? This is especially important when multiple resources cross the threshold in rapid succession.

AWS Transform is a collaborative enterprise IT transformation workbench powered by expert agents that accelerate cloud migration, application modernization, and continuous tech debt reduction. On May 14, 2026, AWS announced general availability of the AWS Transform Agent Toolkit Kiro Power, enabling Professional services organizations (e.g., consulting firms delivering cloud migrations), Independent Software Vendors (ISVs) embedding their tools into transformation workflows, and enterprise...

Effective cluster management requires both minimizing costs and meeting your performance SLAs. As big data workloads grow more complex with varying data volumes and runtime requirements, this challenge intensifies. Previously, customers had two options to optimize this balance: use default Amazon EMR Managed Scaling behavior or use autoscaling with custom rules. Autoscaling has risks of losing shuffle data, terminating Application Masters, and slower response times.

As organizations continue to scale their cloud environments to meet growing business demand, combining workload provisioning with IBM Instana observability in a single workflow improves operational efficiency. Teams use Terraform to provision Amazon Elastic Compute Cloud (Amazon EC2) instances and Amazon Elastic Container Service (Amazon ECS) resources. They then manually install the IBM Instana agent, configure dashboards and follow that up with alerts in the UI.

Cloud skills remain one of the most in-demand capabilities in the workforce, and the way people demonstrate them is changing fast. Learners increasingly want training that builds the skills employers actually hire for, and they want a credential they can show for it. Hiring managers and organizations want a trusted signal that confirms a candidate has the hands-on experience to design, build, and validate cloud solutions.

This post is co-written by Nishanth Charlakola from S&P Global. Organizations have a requirement to build high availability and disaster recovery (HA/DR) solutions for their complex SQL Server infrastructure to maintain data availability and integrity. With the rapid pace of cloud adoption, businesses across different industries have realized the value of a successful proof of concept (POC) for any technical project that migrates existing environments to the cloud.

Today, we are launching an open source Model Context Protocol (MCP) server that brings AI-powered dataset discovery to Registry of Open Data on AWS (RODA) . As of today, RODA hosts over 1,100 high-value datasets from more than 400 organizations, spanning satellite imagery, life sciences, climate, geospatial, and more. Ask a research question in Kiro, Claude Code, or any MCP-compatible AI assistant, and get back relevant datasets, metadata, and data previews to kickstart your project.

Insurance fraud remains a significant challenge for the insurance industry because fraudulent claims can increase loss costs, reduce trust, and consume investigation capacity that could otherwise be focused on serving customers. Traditional fraud detection approaches typically rely on rules-based controls, manual investigation triggers, historical claim patterns, and structured-data-only analysis.

When 121 million mobile devices establish persistent gRPC connections to your origin infrastructure within seconds of a live broadcast, the routing policy behind your DNS records matters far more than it does at normal traffic levels. The wrong policy can concentrate all your connections onto a single origin endpoint, turning a scaling success into an outage.

If you run critical workloads on AWS, such as a contact center on Amazon Connect Customer , database workloads on Amazon Relational Database Service (Amazon RDS) , or hybrid connectivity through AWS Direct Connect , service health events demand your attention. But not all events are equal. An operational issue, a scheduled maintenance window, and a deprecation notice buried in your inbox have very different consequences.

If you are building AI agents, you have likely encountered a growing list of protocol acronyms—MCP, A2A, UTCP, AG-UI, and x402—that can feel overwhelming. The open source community has converged on several complementary protocols. An AI agent is only as useful as the systems it can reach: internal tools and data, the external APIs your workflows depend on, other agents that own specialized tasks, and the humans who review results and act.

Organizations in regulated industries like financial services, insurance, healthcare, and government ingest large volumes of data containing personally identifiable information (PII). Your applications, claims processing systems, partner data feeds, and internal workflows produce files that may include names, addresses, Social Security numbers, and domain-specific identifiers such as policy numbers, member IDs, and medical record numbers.

According to Siemens’ 2024 report The True Cost of Downtime , Fortune 500 companies lose an estimated $1.4 trillion annually because of unplanned downtime. This downtime is often worsened by a lack of skills to detect and resolve issues quickly. Generative AI offers a promising path to address this, but deploying these capabilities in industrial environments introduces a distinct architectural challenge: how do you bring the power of large-scale AI to locations where cloud connectivity is...

AWS CloudFormation is the foundational tool of infrastructure-as-code for thousands of organizations running workloads on AWS. But as teams push the boundaries of what CloudFormation can do natively, custom resources have emerged as a powerful extension mechanism that unlocks a broad range of possibilities. Yet, when it comes to building resilient, multi-Region deployments with custom resources, customers quickly discover a gap: there is no built-in multi-Region support.

Healthcare organizations face a critical scaling challenge – how to maintain deeply personalized patient interactions as member bases grow, without overwhelming care teams or compromising quality. At Pelago , a digital health company specializing in substance use disorder support, the engineering team found a way to build an AI-powered solution to address this challenge using AWS services in just two weeks.

This post was contributed by Mao Lin, Bruno Camino, John Buckeridge and Scott M. Woodley Many advanced materials — from battery electrodes to semiconductor alloys — owe their useful properties to atomic-scale disorder. But predicting how atoms arrange themselves at a given temperature is hard: the number of possible configurations explodes combinatorially and sampling them according to their thermodynamic weights can overwhelm classical computation.

Cloud learning is most effective when teams can engage with it in ways that fit their work. Learners need opportunities to reinforce what they have learned, even when they are spread across time zones, working different schedules, or attending a multi-day event. Facilitators also need a way to understand how their audience feels, what participants know, where they need support, and what they want to learn next, without turning every question into a scored knowledge check.

In automotive software, costly problems often are not the ones that violate a coding rule or fail a compiler check. They are the ones that pass linters, traceability gates, static analyzers, and still surface as problem reports when components interact on real hardware for the first time. In a previous blog post, we described how AUMOVIO built an AI-powered engineering assistant on Amazon Bedrock that generates automotive-grade embedded code. That system accelerates development.

You build streaming pipelines, manage lakehouse architectures, and deliver dashboards that drive decisions. Now you can earn a credential that validates your hands-on skills. Today, we’re launching three new microcredentials focused on Data Analytics: AWS Data Streaming Demonstrated , AWS Data Lakehouse Demonstrated , and AWS Data Visualization Demonstrated .

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

OpenAI shares how its safety, security, transparency, and provenance practices support responsible AI governance in Europe. The work will continue as the EU AI Act advances.

A full-stack approach to making advanced AI more capable, more affordable, and more widely useful.

See how Univé built an AI-ready workforce with ChatGPT Enterprise by combining leadership, responsible governance, and employee-led innovation to transform work at scale.

OpenAI disrupted a Cambodia-based scam operation using ChatGPT to support investment, romance, gambling, and impersonation schemes.

Explore lower GPT‑5.6 pricing for Luna and Terra—and how OpenAI’s more efficient models help enterprises deploy AI workflows at scale.

avatarin uses OpenAI’s GPT-Realtime to give Yamada Denki shoppers 24/7 multilingual support. In two weeks, 30,000 people used the agent and 92% of survey responses were positive.

How two API settings improved GPT-5.6 performance on ARC-AGI-3, boosting scores and efficiency by retaining reasoning and enabling compaction.

OpenAI is giving 100,000 academic researchers free access to ChatGPT's most advanced AI models to accelerate scientific research, collaboration, and discovery.

GPT-5.6 improves AI efficiency across models, inference, and agentic workflows, helping deliver more useful intelligence per dollar.

A new field report shows how scientists use AI coding agents to modernize scientific computing, accelerating software development and discovery in genomics and beyond.

New OpenAI research shows how AI is expanding what workers do, with ChatGPT users taking on tasks across roles and reshaping job boundaries.

Health in ChatGPT now lets eligible U.S. users securely connect medical records and Apple Health to get more personalized insights and better understand their health.

OpenAI announces Project Camellia in Effingham County, Georgia, with commitments to responsible energy, community investment, jobs, and access to Codex.

News organizations are using AI to strengthen reporting, grow audiences, and improve business operations, with OpenAI tools supporting journalists and publishers worldwide.

OpenAI outlines its commitment to advancing American science working with the U.S. Department of Energy and national labs to use frontier AI to accelerate discovery.

Introducing OpenAI Presence, a proven enterprise AI agent platform that helps organizations deploy trusted voice and chat agents for customer and internal workflows.

NTT DATA Group uses ChatGPT Enterprise and Codex to help 9,000 employees automate work, cut incident analysis to 30 minutes, and scale secure AI adoption.

OpenAI launches the ChatGPT for Small Businesses program, helping entrepreneurs build AI skills, automate work, and grow with ChatGPT Work.

OpenAI and Hugging Face share early findings from a security incident during AI model evaluation, highlighting advanced cyber capabilities and lessons for defenders.

David Vélez and Robin Vince join the boards of the OpenAI Foundation and OpenAI Group PBC, bringing global leadership in finance, technology, and governance.

OpenAI shares lessons from deploying long-running AI models, highlighting new safety risks, observed failures, and improved safeguards through iterative deployment.

Sarah Friar, CFO of OpenAI, introduces a practical AI scorecard to measure ROI through useful work, cost per successful task, dependability, and return on compute.

Learn how OpenAI is making ChatGPT safer for teens with age-appropriate protections, learning tools, parental controls, and expert partnerships.

How OpenAI’s creative team uses Codex to build custom creative tools, accelerate ideation, and prototype faster with context-aware AI.

Cars24 uses OpenAI-powered voice and chat agents to handle 1M+ monthly conversation minutes, recover 12% of lost leads, and bring agentic workflows to teams across the company.

OpenAI outlines a “reverse federalism” approach to AI governance, where state laws help build a national framework for safe, democratic AI.

Explore GPT-Red, OpenAI’s automated red teaming system that uses self-play to improve AI safety, alignment, and prompt injection robustness.

Learn how enterprises can manage AI investments in the agentic era by measuring useful work per dollar, improving efficiency, and scaling high-value workflows.

See how data science teams can use ChatGPT Work to build root-cause briefs, impact readouts, KPI memos, scoped analyses, and dashboard specs from real work inputs.

See how sales teams can use ChatGPT Work to create pipeline briefs, meeting prep packets, forecast reviews, account plans, and stalled-deal diagnoses from real work inputs.

How Deutsche Telekom is becoming an AI-native telco with OpenAI-transforming customer service, employee workflows, network operations, and the future of voice.

Learn how to use ChatGPT, start your first conversation, and discover simple ways to write, brainstorm, and solve problems with AI.

Learn how GPT-5.6 powers Microsoft 365 Copilot with stronger AI capabilities across Word, Excel, PowerPoint, Chat, and Cowork for faster, higher-quality work.

ChatGPT Work is an agent that can take action across your apps and files, stay with a project for hours if needed, and turn a goal into finished work.

More intelligence from every token, stronger performance per dollar, and more capability on demand for your hardest work.

Details about the OpenAI Bio Bounty program...

Learn how OpenAI approaches government and national security partnerships, with principles for responsible AI use, democratic accountability, and public safety.

A new analysis from OpenAI reveals issues in SWE-Bench Pro, a popular coding benchmark, raising concerns about reliability and accuracy in evaluating AI models.

OpenAI Academy and the Walton Family Foundation are bringing hands-on AI Skills Jams to help K–12 educators build practical AI skills for the classroom.

A new generation of voice models for natural human-AI interaction, now powering ChatGPT Voice.

See how Australian Payments Plus uses ChatGPT Enterprise and Codex to move faster through payments complexity. AP+ saves time, improves quality, and keeps human judgment central.

MUFG uses ChatGPT Enterprise to build an AI-native organization, improve workflows, and deliver new AI-powered financial services at scale.

Giving thousands of software engineers access to agentic tooling is straightforward. Helping them fundamentally change how they build software is another matter entirely; one every engineering organization eventually runs into. The real constraint on enterprise agentic engineering is not model power, rather, it is an organization’s ability to build new skills, establish shared expectations, and create a common language for human-agent collaboration.

Building an AI prototype has never been easier. You send a prompt to a model, receive a response, and present the result to a user. As long as each request is independent, the interaction is straightforward to reason about, test, and debug. That is why so many early AI applications feel deceptively simple. Production AI systems tell a different story. Imagine generating AI output across 10,000 records. Thousands of model calls begin executing simultaneously.

In our Engineering Energizers Q&A series, we highlight the engineering minds driving innovation across Salesforce. Today, we spotlight Teresa Marshall, Vice President of Localization. Teresa’s team delivers every Salesforce release in up to 34 languages. As Salesforce engineering accelerated, product volume grew by more than 35% between releas es while localization budgets and release windows remained essentially fixed, forcing a pipeline that had supported Salesforce for decades to deliver...

By Priya Sethuraman, Abhishek Ghose, Lovish Agarwal, and Aditya Pandey. In our Engineering Energizers Q&A series, we highlight the engineering minds driving innovation across Salesforce. Today, we spotlight Priya Sethuraman, Director of Software Engineering. Priya leads the Sales Cloud BugWiser initiative, an AI-powered system that standardizes customer bug classification and transforms customer bug signals into faster engineering action.

After six cycles, the system ran out of things to fix. That sentence probably raises more questions than it answers. Here is how we got there. The first skill PR took three days to merge. Twelve comments on structure. Six on conventions. The contributor fixed everything, merged, moved on. The next contributor hit the same twelve walls. If you have reviewed enough pull requests , you have probably seen this pattern. An expert writes a thoughtful review comment. That comment fixes one PR.

Ever had an experience onboarding someone, where you had to provide them a handful of documents, all authored at different times, and in various states of completeness? Ever had your AI agent burn cycles pulling down that same documentation, understanding it, and summarizing it, before it finally responds? If you’ve experienced either, then you’ve probably watched the same expensive reasoning happen over and over again.

In our Engineering Energizers Q&A series, we highlight the engineering minds driving innovation across Salesforce. Today, we spotlight Nancy Chen, Vice President of Engineering at Informatica . Nancy leads the development of Copilot, an AI-powered experience that enables users to generate data integration pipelines using natural language. Since launching, customers have generated approximately 10,000 pipelines and submitted more than 25,000 expression-generation requests.

While red-teaming an early refund agent early last year, one of our engineers typed a deliberately absurd line: “ my very valid and very verified email .” The agent, running on a frontier LLM, accepted it as proof of identity and prepared to issue the refund. Nobody had jailbroken anything. The model simply did what language models are built to do, which is to interpret language plausibly rather than enforce a rule.

SAP has been recognized as a Leader in the first-ever Gartner® Magic Quadrant™ for Digital Twin of an Organization. This recognition follows closely behind SAP’s acknowledgement as a Leader for Process Intelligence Platforms earlier in 2026. In today’s dynamic business landscape, characterized by the ongoing rise of AI and the need for adaptation in the face of rapid change, companies that understand the impact of operational adjustments—before those changes actually take effect—are best-placed.

WALLDORF — SAP welcomes the decision of the German Federal Cartel Office (Bundeskartellamt) to conclude its preliminary inquiries and not to initiate abuse proceedings against SAP. As the authority states, SAP customers and partners have sufficient and permissible technical options to extract data from SAP systems and use it in solutions from other providers. The SAP API Policy does not restrict these capabilities.

The state of customer experience in 2026 can be summed up simply: customers have never had more ways to interact with your brand, and they’ve never been less tolerant about friction when engaging. While the power of technology is at its apex, so are expectations. And the gap between the two is where revenue goes to die. Explore features designed to improve engagement and accelerate growth through product trials and tours Try our solutions now Brands using AI to deepen human connection by...

Modern B2B buyers expect seamless experiences across web, mobile, marketplaces, and partner portals. In fact, 84% of B2B buyers say it is important for suppliers to operate across multiple online and offline channels.* Turn transformation strategies into action through a coordinated set of services and guidance for every stage of your journey Learn how To meet these expectations, organizations must move beyond siloed commerce channels toward a connected autonomous CX model that integrates...

Sport has always been a mirror of society. It reflects community values, connecting people despite boundaries that might otherwise divide them. The most forward-thinking organizations in sport are no longer content to simply reflect the world as it is. They are actively working to shape the world as it should be. Explore San Jose Sharks’ journey with SAP Learn more The NHL/NHLPA Hockey Innovation Competition presented by SAP is one of the ways SAP, the NHL , and the NHLPA turn that ambition...

Hapag-Lloyd has equipped 2 million shipping containers with tracking devices that transmit location data in real time. SAP uses this data in its ERP systems to help businesses identify potential delays and adjust their production schedules accordingly. Carriers, buyers, and production planners all over the world are benefiting. Managing logistics operations has become increasingly challenging in recent years.

WALLDORF — SAP SE (NYSE: SAP) today announced its financial results for the second quarter and half year 2026. At a glance Current cloud backlog of €22.9 billion, up 27% and up 26% at constant currencies Cloud revenue up 22% and up 24% at constant currencies Cloud ERP Suite revenue up 25% and up 27% at constant currencies Total revenue up 9% and up 11% at constant currencies IFRS operating profit up 8%, non-IFRS operating profit up 7% and up 9% at constant currencies 2026 non-IFRS operating...

The challenge business leaders face today is not any single disruption, it is the collision of all of them at once. Geopolitical volatility is redrawing supply chains faster than procurement cycles can adapt. Regulatory frameworks are shifting across multiple jurisdictions simultaneously. Energy costs, labor markets, and customer expectations are each moving in their own direction, often in direct conflict.

Brazilian food producer São Salvador Alimentos S.A. improves its personal protective equipment (PPE) processes with SAP Build and Cloud Foundry tools, saving 150 manual signatures per day and improving warehouse management. Humanizing business software and making innovation real Explore SAP AppHaus Headquartered in Itaberaí, Goiás, São Salvador Alimentos S.A. (SSA) is one of Brazil’s leading food companies.

Damen Shipyards is charting a course toward a more intelligent, sustainable maritime future with SAP. The Netherlands-based, family-owned maritime group has been building vessels since 1927 and today operates internationally with more than 12,500 people and over 35 yards across six continents. With an ambition to become the world’s most sustainable maritime solution provider, Damen is combining its long-standing craftsmanship with innovation, digitalization, and operational excellence.

Every business wants to move faster, make better decisions, and empower its people to focus on what matters most. This year at SAP Sapphire, we shared our vision for the Autonomous Enterprise — the next evolution of how businesses run, where AI agents execute critical workflows so people can focus on innovation, customer value, and business growth. This vision comes to life through a reimagined Joule Work , evolving from an AI assistant into the central workspace for enterprise AI.

This year’s SAP for Energy and Utilities Conference, held in Toulouse, France, marked a notable first: the inaugural presentation of the Energy and Utilities Innovation Award. Companies whose projects stood out were honored in the categories AI, Innovation, Transformation, Customer Experience, and Best Team. AI as a key element In the AI category, the Austrian energy company OMV prevailed with its SAP Business AI transformation project.

WALLDORF — SAP SE (NYSE: SAP) today announced it has completed the acquisition of Prior Labs, the pioneer of Tabular Foundation Models (TFMs). The acquisition will accelerate SAP’s success in TFMs that started with SAP-RPT-1 and bring one of the world’s leading TFM research teams into the SAP family. Prior Labs will continue to operate as an independent entity, with SAP committing to investing more than €1 billion over the next four years to scale it into a globally leading frontier AI lab for..

AI has made it easier than ever to identify the next best action. Yet for many organizations, executing those actions consistently across teams, channels, and systems remains the greater challenge. Harmonize your CRM and CX with a single autonomous system Learn how As customer journeys become more connected and complex, gaps in execution can lead to inconsistent experiences, slower response times, and missed opportunities.

For decades, enterprise transformation followed a familiar playbook. Digitize processes. Move to the cloud. Standardize operations. Then optimize them over time. Those investments are critical. But they weren’t the finish line. They were the foundation. And today, they’re paying off in new ways as organizations adopt AI to drive measurable business outcomes. Welcome to the Autonomous Enterprise Learn more But there’s another part of that foundation which is becoming just as important: data.

Each day, businesses invest in new software tools: marketing platforms, commerce engines, service systems, and sales technology. They are told that assembling the right combination will unlock their digital transformation journey and finally deliver that personalized and seamless experience they wish to provide to their customers. Harmonize your CRM and CX with a single autonomous system Learn how But what if more or better software is not necessarily the answer?

A new study by SAP and Oxford Economics has revealed businesses around the world are increasingly driving positive return on investment (ROI) from AI, even as challenges continue to accrue. Infographic: SAP and Oxford Economics and the value of AI in 2026 Download the document While the amount the average global business spends on AI increased slightly to US$28 million this year, the level of ROI from that investment has spiked. Globally, companies expect to drive ROI of 21% this year (US$6.

In an environment shaped by constant change, workforce planning is no longer defined by predictable hiring cycles or seasonal demand. Shifting market conditions, evolving customer expectations, and persistent skills shortages mean that the line between permanent and temporary labor has all but broken down. Manage external talent and services to stay competitive while maintaining control over costs and compliance Learn how External talent, including contractors, consultants, and project-based...

The biggest problem in financial services is not AI readiness, it’s structural complexity. Video: How SAP and SAP Fioneer Are Shaping the Future Watch now That was the takeaway from a recent conversation between SAP CFO Dominik Asam and SAP Fioneer CEO Matthias Tomann. Their conversation touched on topics like the future of financial services , the role of AI, and the growing importance of integrated enterprise platforms.

Swarovski has followed its cloud transformation from 2023 with a global go-live of SAP Cloud ERP Private after choosing an exciting brownfield approach for the rollout. With its migration, the luxury brand is laying the foundation for using AI and for reaching its strategic targets by 2030. Anyone who is looking for a prime example of how migration to the cloud can do far more than just simplification and standardization should take a closer look at Swarovski.

Winning deals is hard enough for our partners. Building quotes, navigating pricing, and waiting on approvals can make it even harder. A straightforward transaction could stretch into weeks of back and forth. With updates to SAP Store and SAP for Me , partners now get a self-service purchasing experience that cuts out that complexity, with pricing transparency comparable to what partners get on AWS and Azure marketplaces.

With a record-breaking heatwave gripping the UK in late June, the “action” in London Climate Action Week 2026 needed no explanation. Much like the temperatures outside, the conversations inside intensified, and the soaring mercury served as a live stress test for the very subjects under discussion: infrastructure, public health, business continuity, and the resilience of the systems everyone depends on.

At SAP, our mission has always been to help the world run better and improve people’s lives. Thousands of organizations worldwide rely on SAP’s enterprise resource planning (ERP) and other software to manage their most critical business operations—from corporate finance and human resources to supply chain management and project delivery. Discover the new success plans and services that deliver the results your business needs to be future-ready Learn more Equally important to our customers are...

WALLDORF — SAP welcomes the European Commission’s decision to conclude its competition investigation into certain aspects of SAP’s on-premise maintenance and support practices through a commitment decision, following a constructive and cooperative dialogue. SAP remains committed to open competition, customer choice and innovation. The commitments provide greater clarity, choice and safeguards for customers managing complex on-premise environments, while supporting flexible IT strategies aligned.