Meta expands AWS partnership for agentic AI workloads

The deployment begins with tens of millions of Graviton cores, with flexibility to expand as Meta’s AI capabilities grow, making Meta one of the largest Graviton customers in the world.

The agreement reflects a broader shift in enterprise AI infrastructure, where agentic AI workloads are creating growing demand for CPU-intensive processing alongside traditional GPU-heavy model training.

AWS said the deal builds on Meta’s long-standing relationship with the cloud provider and its use of Amazon Bedrock at scale to support next-generation AI.

While GPUs remain critical for training large models, AWS said the rise of agentic AI is driving demand for CPU-intensive workloads such as real-time reasoning, code generation, search, and orchestrating multi-step tasks.

Graviton5 was designed for these workloads, providing the processing power needed to support billions of interactions while coordinating complex, multi-step agent workflows.

The chips will support a range of Meta workloads, including the company’s broader AI efforts.

Why Graviton5 matters for enterprise AI infrastructure

The Graviton5 chip features 192 cores and a cache five times larger than the previous generation, reducing delays in how quickly those cores communicate by up to 33%.

AWS said this enables faster data processing and greater bandwidth—both critical for agentic AI systems that must continuously reason through and execute multi-step tasks.

The chip is built on the AWS Nitro System, combining dedicated hardware and software for high performance, high availability, and high security.

This allows bare-metal access while maintaining the familiar Elastic Network Adapter and Amazon Elastic Block Store devices that enable Meta to run its own virtual machines without performance compromises.

Graviton5 instances also support the Elastic Fabric Adapter (EFA), enabling low-latency, high-bandwidth communication between instances—an essential requirement for large-scale distributed AI workloads.

Amazon: Purpose-built silicon is powering the next generation of AI

Nafea Bshara, vice president and distinguished engineer at Amazon, said the deal goes beyond hardware.

“This isn’t just about chips; it’s about giving customers the infrastructure foundation, as well as data and inference services, to build AI that understands, anticipates, and scales efficiently to billions of people worldwide,” he said.

“Meta’s expanded partnership, deploying tens of millions of Graviton cores, shows what happens when you combine purpose-built silicon with the full AWS AI stack to power the next generation of agentic AI.”

Meta focuses on diversified compute for AI scale

Santosh Janardhan, head of infrastructure at Meta, said expanding compute options is a strategic priority.

“As we scale the infrastructure behind Meta’s AI ambitions, diversifying our compute sources is a strategic imperative,” he said.

“AWS has been a trusted cloud partner for years, and expanding to Graviton allows us to run the CPU-intensive workloads behind agentic AI with the performance and efficiency we need at our scale.”

Energy efficiency becomes central to AI infrastructure strategy

Graviton5 is built on 3-nanometer chip technology, allowing for smaller and more efficient processors.

Because AWS controls the full process from chip design through server architecture, it said it can optimize both performance and efficiency beyond what off-the-shelf processors can deliver.

The company said Graviton5 delivers up to 25% better performance than the previous generation while helping Meta stay aligned with sustainability targets.

As AI compute demand continues to grow, AWS said the efficiency of the underlying infrastructure is becoming increasingly important for both cost management and environmental impact.

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SNOWFLAKE ADVANCES AGENTIC ENTERPRISE  

Snowflake, the artificial intelligence (AI) data cloud company, has announced a series of enhancements across Snowflake Intelligence and Cortex Code, furthering its ambition to become the control plane for agentic enterprises. 

As AI evolves beyond answering questions to taking action, the latest updates are designed to help organizations connect more data sources, enterprise systems, and AI models within a single, unified experience.  

This approach enables businesses to better align their data, workflows, and tools with AI agents built on Snowflake, supporting more seamless and practical execution of tasks across the enterprise. 

Central to this development is Snowflake Intelligence, which is positioned as a personalized work agent for business users. The platform evolves over time by learning individual preferences and workflows, delivering increasingly relevant outputs while automating routine processes. Importantly, all insights are grounded in governed enterprise data, ensuring both trust and accuracy. 

Cortex Code, meanwhile, continues to expand as a development layer for enterprise AI. It provides a governed, data-native environment that allows developers to build, orchestrate, and operationalize AI directly within existing systems and tools. Together, these capabilities support a broad range of users, from business teams to technical specialists, while centralizing how organizations manage and connect their data, models, and applications. 

“AI is changing how every company operates, and the platforms that win will make it easy to put AI into practice with the right data and guardrails,” says Baris Gultekin, VP of AI, Snowflake.  

“Snowflake gives customers one place to bring their data together, connect the systems they rely on, and turn AI into something that actually helps teams get work done.” 

Over 9,100 use Snowflake’s products on a weekly basis, including leading enterprises like Capita, Logitech, Telenav, United Rentals, and Wolfspeed, and are using Snowflake Intelligence and Cortex Code together to accelerate how they build, deploy, and operate AI. 

ENHANCING PRODUCTIVITY  

Snowflake Intelligence sets itself apart from conventional AI assistants by combining enterprise-grade governance, security, and contextual understanding of business data. The latest updates introduce a more unified experience, enabling users to interact with data, analyze it, and take action across multiple enterprise systems. 

New capabilities include the introduction of ‘Skills’, which allow users to describe workflows in natural language – such as preparing presentations or conducting multi-step analysis – which the system can then execute automatically.  

Integration is also being strengthened through new Model Context Protocol (MCP) connectors, enabling direct connections with widely used tools, including Gmail, Google Calendar, Google Docs, Jira, Salesforce, and Slack. 

Mobility is another key focus, with a new iOS mobile app set to enter public preview, allowing users to engage with their data and workflows remotely. In addition, deep research functionality will support more complex queries by generating multi-step, fully cited reports that draw on structured data, unstructured content, and external context. 

The platform is also becoming more personalized, learning from user behavior over time to refine responses and automate recurring tasks.  

Elsewhere, the new “Artifacts” functionality will allow users to save and share analyses, visualizations, and workflows, helping teams build on existing insights and scale knowledge across the organization. 

These developments have been informed by customer feedback, including insights gathered during the research preview of Project SnowWork. 

SCALING AI DEVELOPMENT  

Cortex Code is evolving to support developers working across increasingly complex data environments. Since its launch in November 2025, adoption has grown rapidly, with more than half of Snowflake customers now using the platform to drive productivity and innovation. 

Recent updates extend its capabilities across the modern data stack, with expanded support for external systems such as AWS Glue, Databricks, and PostgreSQL. This reinforces Snowflake’s vision of enabling organizations to work with data wherever it resides. 

Integration with the broader AI ecosystem is also advancing. Through the MCP and Agent Communication Protocol (ACP), Cortex Code can connect with other AI systems, allowing developers to incorporate it into existing workflows more easily. 

To improve flexibility, Snowflake is introducing new tools that allow developers to work within their preferred environments, including a VS Code extension and a Claude Code plugin. In addition, a new Agent Software Development Kit, supporting Python and TypeScript, enables teams to embed Cortex Code capabilities directly into their own applications. 

Further enhancements within Snowsight, including Cloud Agents, allow users to run code and execute workflows directly in the browser without local setup. Additional features such as Plan Mode and Snap & Ask provide greater control and more intuitive interaction with data, helping teams improve both efficiency and accuracy. 

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Democratizing AI on the Factory Floor

Announced at Cloud Next ’26, the initiative has already seen the company roll out more than 800 AI agents across manufacturing, logistics, and supply chain functions—marking a significant step toward what it describes as the future of AI-enabled industrial operations.

A key focus of the strategy is putting AI tools directly into the hands of frontline workers.

“AI is now integral to the way work gets done at GE Appliances,” said Mandar Deo, Vice President of Digital Technology & Chief Digital Officer. “With hundreds of AI agents already in use across manufacturing and operations, our Digital Technology team is accelerating this AI transformation with Gemini Enterprise to build the secure, connected data foundations necessary to lead the industry in the AI era.”

The company is leveraging both the Gemini Enterprise Agent Platform and app—enabling technical teams to build and govern AI agents, while allowing non-technical employees to create low-code or no-code solutions to solve operational challenges.

AI-Powered “Brilliant Factory” Drives Real-Time Manufacturing Decisions

GE Appliances has embedded Gemini Enterprise into its Brilliant Factory platform, which tracks production performance, part genealogy, and workforce activity across plants.

This integration is shifting operations from reactive problem-solving to real-time, data-driven decision-making.

Key manufacturing gains include:

• Faster shift analysis: AI agents process shift data in minutes instead of hours, accelerating root-cause identification
• Natural language data access: Workers can interact with production data conversationally, reducing reliance on data specialists
• Real-time optimization: Continuous monitoring of line yields and equipment health helps reduce downtime and improve performance

Supply Chain and Logistics: From Manual to AI-Assisted Operations

Beyond the factory floor, AI is delivering measurable impact across logistics and supply chain operations.

GE Appliances developed a Quality Insights AI tool to analyze customer feedback and improve product design and logistics processes.

“We used Gemini Enterprise to create and deploy Quality Insights Assistant to help our teams identify visual patterns faster from customer feedback,” said Marcia Brey, Vice President of Logistics. “At our scale, that means we can catch defects sooner and improve product quality, ultimately delivering a better consumer experience.”

The company reports that shifting from manual reviews to AI-assisted analysis has uncovered millions of dollars in improvement opportunities across logistics and internal operations.

Managing Complex Global Supply Networks with AI Agents

GE Appliances’ supply chain spans more than 700 service parts suppliers and includes the shipment of approximately 27 million parts annually, with availability maintained for at least seven years after production ends.

To manage this complexity, the company introduced a Supplier Collaboration Agent in 2025 to automate communication with more than 600 suppliers.

The result:

• 25% reduction in backorders
• Improved efficiency in order status management
• Greater focus on strategic, high-value activities

A Model for the Agentic Enterprise

Matt Renner, President and Chief Revenue Officer at Google Cloud, highlighted the broader implications of the deployment:

“GE Appliances serves as a model for the agentic enterprise, demonstrating how Gemini Enterprise can be deployed at scale to solve complex, real-world industrial challenges. By building AI agents into their manufacturing processes, they are combining their deep industry experience with modern AI to make faster, better decisions.”

Scaling AI Across Industrial Operations

With more than a century of manufacturing experience, GE Appliances is now embedding AI across its workforce and operations—reshaping how products are built, how supply chains are managed, and how decisions are made at scale.

By combining industrial expertise with AI-driven automation, the company is positioning itself at the forefront of a new era in manufacturing and supply chain transformation—where data, speed, and intelligence define competitive advantage.

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Building on Packaging and Circular Economy Progress

The strategy centers on integrating sustainability into core operations, with an emphasis on value creation for the business, communities, and the environment.

The new roadmap builds on progress achieved under the company’s 2025 strategy, particularly in packaging innovation.

Since introducing a recyclable toothpaste tube in 2019, Colgate-Palmolive has transitioned approximately 97% of toothpaste SKUs in North America and 98% globally to recyclable formats. These tubes are now sold in more than 70 countries worldwide.

Across its broader portfolio, around 96% of packaging is currently designed for recycling, with a target of reaching 100% by 2030.

Embedding Sustainability into Business Strategy

Colgate-Palmolive emphasized that sustainability is being integrated directly into its business model to drive innovation and long-term value.

Ann Tracy, Chief Sustainability Officer at Colgate-Palmolive, said:

“Our 2030 Strategy targets the areas where we can make the greatest difference, fostering growth for our business and our communities.”

“This work involves Colgate-Palmolive People around the world and supports our purpose to reimagine a healthier future for all.”

Expanding Social Impact Through Global Health Programs

Colgate-Palmolive continues to scale its social impact initiatives as part of its sustainability agenda.

The Colgate Bright Smiles, Bright Futures program has reached approximately 2 billion children and their families in over 100 countries since 1991, providing oral health education and support. The company aims to expand this to 2.7 billion people by 2030.

In parallel, its Hill’s Food, Shelter & Love program in the United States has delivered over $300 million in pet food donations, supporting more than 1,000 shelters and helping over 16 million pets find homes since 2002.

Advancing Renewable Energy and Climate Targets

Colgate-Palmolive is also progressing its climate transition plan. As of the end of 2025, approximately 83% of its global electricity use comes from renewable energy sources, with a target of reaching 100% by 2030.

These efforts form part of a broader push to build a climate-resilient value chain and improve operational sustainability.

Three Strategic Pillars Drive 2030 Roadmap

The company’s 2030 strategy is structured around three core ambitions:

•             Driving Social Impact through inclusion, wellbeing, and healthier habits

•             Helping Millions of Homes by delivering sustainable product innovation and improving lives for people and pets

•             Preserving the Environment by addressing plastic waste, climate resilience, water security, operational efficiency, and biodiversity

Together, these pillars are designed to align sustainability goals with business performance.

Committing to Impact

“I continue to be inspired and optimistic about our future, especially as CP People around the world are committing to impact and innovating to support a healthier planet,” adds Ann Tracy.

“As we look toward 2030, we will focus on how our actions drive value creation, fostering long-term growth and resilience for people, pets and the planet – we call this our win-win-win principle. We Make more Smiles when we create this positive fly-wheel.”

Focus on Value Creation and Operational Resilience

The company highlighted that its approach prioritizes high-impact initiatives designed to deliver benefits across consumers, the business, and the planet.

By embedding sustainability into operations, Colgate-Palmolive aims to strengthen resilience, support innovation, and meet evolving expectations from stakeholders, including customers, employees, partners, and investors.

Next Steps and 2030 Outlook

The 2030 Sustainability & Social Impact Strategy is fully integrated into the company’s broader strategic plan.

Colgate-Palmolive plans to report progress and introduce additional 2030 targets in its upcoming Sustainability and Social Impact Report later this year.

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AI-Driven Supply Chains: From Insight to Action

Announced at Cloud Next ’26, the partnership centers on leveraging Google Cloud’s Gemini Enterprise Agent Platform to help PepsiCo move “from insight to action more quickly and consistently at scale,” while strengthening its digital and multi-cloud foundations.

At the core of the collaboration is a push to modernize PepsiCo’s supply chain and go-to-market capabilities using AI.

“As market dynamics and customer expectations evolve, PepsiCo is re-examining how we bring products to market and how we make decisions at scale,” said Athina Kanioura, CEO, Latin America Foods, and Chief Strategy & Transformation Officer, PepsiCo.

She added: “Google Cloud’s deep expertise in AI and engineering strengthens our best-in-class supply chain and go-to-market capabilities — giving us unprecedented speed and precision to model scenarios that were previously impossible to run. The result is faster decisions, improved frontline experiences, and a step change in how we design and operate our business.”

The partnership enables PepsiCo to apply AI to complex challenges such as supply chain management and in-store execution—key priorities for global food and beverage operators navigating volatility and shifting demand.

Building a Resilient, AI-Powered Value Chain

PepsiCo will use Gemini Enterprise Agent Platform across three core areas:

• Scaling Global Intelligence

The company is expanding its data and analytics capabilities through an AI-driven digital platform built on Google Cloud’s global infrastructure, creating a more resilient foundation for operations and digital transformation.

• Optimizing the End-to-End Value Chain

AI capabilities will support faster, more informed decision-making—from long-term strategic planning to real-time execution in stores—helping drive productivity and cost efficiency.

• Empowering the Workforce

AI-enabled workflows will reduce manual effort and accelerate insight generation, allowing employees to focus on higher-value tasks while improving overall operational performance.

Multi-Cloud Strategy Strengthens Global Operations

A key component of the collaboration is PepsiCo’s continued investment in a flexible, multi-cloud environment.

By migrating to Google Cloud’s secure global infrastructure, the company aims to build new digital capabilities that support its worldwide supply chain network and enable it to “leverage the best available AI technology” across use cases.

This approach is designed to enhance agility across markets while ensuring consistent performance at scale.

AI at the Core of Food and Beverage Transformation

Thomas Kurian, CEO of Google Cloud, emphasized the role of AI in advancing supply chain resilience:

“PepsiCo has a long history of using data to understand consumer demand. With Gemini Enterprise, it is putting AI into the hands of its global workforce and empowering them with the tools to build a more resilient supply chain.”

Linking AI Strategy to Sustainability and Growth

The collaboration also aligns with PepsiCo’s broader transformation strategy, including its pep+ (PepsiCo Positive) framework, which places sustainability at the center of business growth.

By embedding AI across supply chain and operational workflows, PepsiCo is aiming to improve efficiency, reduce costs, and strengthen resilience—critical priorities for the global food and beverage sector.

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ACCELERATING DIGITAL TRANSFORMATION 

Vodafone Business (Vodafone) has strengthened its collaboration with Google Cloud (Google) with the launch of new artificial intelligence (AI) and cybersecurity solutions aimed at small to medium-sized (SME) businesses. 

Announced at Google Cloud Next 2026, the initiative builds on the companies’ USD$1 billion, 10-year strategic partnership established in October 2024. The collaboration is focused on equipping SMEs with accessible, enterprise-grade digital tools to support growth and resilience in an increasingly digital economy. 

By combining Vodafone’s connectivity and customer reach with Google’s expertise in AI and cloud technologies, the partnership seeks to simplify the adoption of advanced digital capabilities for businesses of all sizes. 

ENHANCING CYBERSECURITY CAPABILITIES 

A key component of the announcement is a new managed detection and response (MDR) service, powered by Google Security Operations (SecOps). 

The solution integrates Google’s security analytics and AI-driven threat intelligence with Vodafone’s understanding of the SME market, enabling businesses to detect, investigate, and respond to cyber threats in real time. 

The service will initially launch in Germany, ensuring compliance with regional data protection requirements, before being rolled out more widely across Europe later in the year. 

INTRODUCING AI CONCIERGE 

Alongside its cybersecurity offering, Vodafone has introduced AI Concierge, developed using Google’s Gemini models and Enterprise Agent Platform. 

Designed as a multimodal AI agent, the solution is capable of autonomously managing customer interactions, including responding to enquiries and booking appointments. 

By handling routine yet critical business tasks, AI Concierge enables SMEs to remain responsive outside of standard operating hours whilst allowing employees to focus on higher-value activities. The service is set to launch initially in Germany and Greece. 

“Vodafone Business is helping millions of small and medium-sized businesses (SMBs)unlock the power of AI without the complexity or risk,” said Fánan Henriques, Vodafone Business Product and International Business Director.  

“By combining our network and support with Google Cloud’s AI expertise, we’re making advanced, secure AI practical for everyday business use – starting with innovations like AI Concierge, one of the first telephony integrations with Gemini.” 

SUPPORTING SMALL BUSINESSES AT SCALE 

The partnership reflects a shared commitment to supporting SMEs as they navigate an evolving digital landscape. 

“Small businesses are the backbone of the global economy, yet they are often the most underserved when it comes to cutting-edge tech,” said Oliver Parker, Vice President of global generative AI for Google.  

“Together with Vodafone Business, we are changing that. By combining our Gemini models and enterprise-grade security expertise with Vodafone’s deep connectivity and customer reach, we are giving SMBs the tools they need to stay protected and remain competitive in a rapidly evolving digital landscape.” 

With the introduction of these new solutions, Vodafone continues to expand its role as a provider of integrated digital services, helping SMEs adopt AI and strengthen cybersecurity through a streamlined, end-to-end approach.

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Emissions Fall as Business Growth Continues

The company’s latest update outlines how carbon-aware software engineering, hardware optimization, and data-driven decision-making are reshaping its global technology stack.

Mastercard reported strong progress against its interim climate targets in 2025, cutting Scope 1 and 2 emissions by 44% and Scope 3 emissions by 46% from 2016 levels.

This came alongside continued commercial growth, with net revenue rising 16% while overall emissions declined by 1% year over year — marking a third consecutive year of emissions reduction and signaling early evidence that growth can be decoupled from environmental impact.

Sustainability Positioned as a Performance Driver

“This Earth Day, Mastercard is demonstrating that we can scale the digital economy, without scaling emissions,” said Ellen Jackowski, Chief Sustainability Officer at Mastercard, writing on LinkedIn on Earth Day.

“These results reinforce a simple but important point: with focus, discipline and support from across the company, environmental sustainability does not have to be a constraint on performance. It can be a catalyst for it.”

Technology Infrastructure Drives Sustainability Focus

The company identified its technology footprint as central to its emissions profile. Data centers represent around 60% of Scope 1 and 2 emissions, while technology goods and services account for roughly one-third of Scope 3 emissions.

This has driven a strategy focused on improving efficiency across applications, hardware, and the energy systems that support them.

Renewable Energy and Governance Underpin Strategy

Renewable energy remains a key driver of emissions reduction, supported by broader efforts spanning procurement, supply chain engagement, and embedding sustainability into day-to-day business decisions.

A dedicated Sustainable Technology Steering Committee oversees execution, ensuring accountability and alignment with company-wide objectives.

Data-Driven Sustainability Across the Tech Stack

Since 2023, Mastercard has built a patent-pending dashboard that assigns a Sustainability Score to each technology asset.

By integrating metrics such as real-time energy consumption, carbon intensity, server utilization, and system consolidation, the platform provides visibility into performance and enables targeted action across operations.

Embedding Carbon Awareness in Software Engineering

Sustainability is now integrated into how Mastercard designs and deploys applications.

Through its engineering community, the company has adopted principles from the Green Software Foundation, focusing on efficient design, runtime optimization, and carbon-aware decision-making. These practices are embedded into engineering standards and review processes, ensuring environmental impact is considered before deployment.

Hardware Optimization Accelerates Efficiency Gains

On the infrastructure side, Mastercard is improving efficiency by consolidating and decommissioning underutilized hardware.

More than 3,700 devices have been removed since 2024, with the pace of decommissioning increasing significantly into 2026. The company is also expanding the use of dynamic power settings to adjust energy consumption in real time based on workload demands.

Optimizing Cloud and Data Center Operations

Mastercard operates across owned, co-located, and cloud environments, requiring close collaboration with suppliers to manage emissions.

Efforts include improving visibility into energy and emissions data and standardizing reporting, including work with Greenpixie. This enables more precise workload placement based on carbon intensity and energy availability.

Net Zero Ambition Backed by Technology Innovation

The company’s approach links emissions reduction directly to its broader mission of powering the digital economy.

“Today, we are celebrating our progress while remaining focused on the work ahead as we continue our journey to reach net zero emissions by 2040,” added Ellen Jackowski.

Mastercard’s strategy demonstrates how aligning technology innovation with sustainability goals can enable both environmental progress and business growth at scale.

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Next-gen silicon carbide technology

The company is already supplying samples to global automakers, signalling the next phase of deployment in electric vehicle (EV) power electronics.

The latest generation of SiC chips delivers a 20% performance increase compared to previous iterations, while also being significantly smaller. This combination of higher power density and reduced size enables greater efficiency in drive electronics and allows more chips to be produced per wafer.

“Silicon-carbide semiconductors are the key drivers of electromobility. They control the flow of energy and make it as efficient as possible. With our next-generation SiC chips, we’re systematically expanding our technological leadership in this field and helping our customers put even more powerful and efficient electric vehicles onto the road,” said Markus Heyn, member of the Bosch board of management and chairman of the Bosch Mobility business sector.

“Our next-generation chips deliver 20 percent higher performance and are also significantly smaller than the previous generation. This miniaturization is the key to greater cost efficiency, as we can produce many more chips per wafer. That means we’re playing a key role in making high-performance electronics more widely available.”

Bosch targets global leadership in SiC chips

Bosch is positioning itself to lead in the rapidly expanding SiC semiconductor market, driven largely by electrification trends.

“Our ambition is clear: we want to be a globally leading manufacturer of SiC chips,” said Markus Heyn.

Since starting production in 2021, Bosch has already delivered more than 60 million SiC chips worldwide, underscoring growing adoption across the automotive sector.

Billions invested to scale global semiconductor manufacturing

To support demand and scale production, Bosch has invested heavily in its global semiconductor manufacturing footprint:

• Around €3 billion invested in semiconductors through European IPCEI programs
• Additional €1.9 billion investment in its U.S. facility

The company’s third-generation SiC chips are produced on 200-millimeter wafers at its Reutlingen, Germany fab, while a second facility in Roseville, California is being equipped for production, with initial samples already planned for customer trials.

“In the future, Bosch will supply its innovative SiC chips from these two fabs in Germany and the U.S.,” Heyn said, highlighting a strategy aimed at building more robust and resilient supply chains for automotive electrification.

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Multi-agent AI orchestration across platforms

The collaboration introduces new integrations between SAP Customer Experience (SAP CX), SAP Engagement Cloud, and Joule solutions with Google Cloud’s Gemini Enterprise—creating a unified environment where AI agents can securely access and act on data across both platforms.

At the core of the partnership is a multi-agent architecture designed to connect systems, data, and workflows. Gemini Enterprise serves as a central hub, enabling AI agents to coordinate actions across SAP and Google Cloud environments.

These integrations are supported by SAP Business Data Cloud Connect for Google and BigQuery, allowing bidirectional, zero-copy data access with enterprise-grade security and governance. This foundation enables agents to exchange context, trigger actions, and optimize outcomes across platforms.

AI agents turn insights into action

The joint solution addresses a key challenge for many organizations: fragmented and outdated data. According to SAP Engagement Cloud research, more than half of marketers say this limits their ability to act in real time.

With the new capabilities, AI agents can operate on unified data to execute complex tasks. For example, users can define high-level goals such as increasing repeat purchases or maximizing customer lifetime value, and an AI agent will manage the full workflow—from content personalization to campaign execution.

Automation of end-to-end business processes

Using Joule Agents within SAP Engagement Cloud, businesses can automate campaign planning, execution, and optimization without manual intervention across multiple tools.

This enables:

• Autonomous campaign generation and optimization
• Continuous performance improvement
• Reduced operational overhead
• Faster time-to-market

The result is more efficient operations and the ability for teams to focus on higher-value strategic activities.

Executive perspectives on agentic AI transformation

“This is more than a data integration; it’s a leap forward for AI agents that can collaborate naturally and execute seamlessly,” said Balaji Balasubramanian, President and Chief Product Officer, SAP Customer Experience and Consumer Industries. “By combining SAP Business Data Cloud Connect for Google with interoperable AI agents across SAP and Google Cloud, we’re giving organizations a path from AI experimentation to AI-enabled customer experience at scale. Marketers can spend less time on manual tasks and more time shaping the customer journey.”

“To realize the full potential of agentic AI, businesses need their systems to speak the same language,” said Kevin Ichhpurani, President, Global Partner Ecosystem at Google Cloud. “By uniting SAP’s enterprise data and customer engagement platform with Google Cloud’s AI, we’re enabling marketers to move beyond simple automation to multi-agent orchestration, driving dynamic campaigns that reason and adapt to market shifts in real time.”

Expanding beyond marketing use cases

While marketing is the initial focus—with availability expected in the second half of 2026—the multi-agent orchestration model is designed to extend across the full SAP CX portfolio.

This positions the partnership as a foundation for broader enterprise adoption of AI agents, enabling organizations to connect data, systems, and workflows into a unified, AI-driven operating model.

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IT/OT convergence and virtual twin technology

The two companies announced a collaboration to integrate virtual twin technology with industrial automation, enabling manufacturers to design, simulate, and operate production systems through a unified digital and physical environment.

The partnership addresses a common issue across industrial environments, where “product design, automation, and production systems operate in silos,” leading to “longer commissioning times, higher error risks, and limited flexibility.”

By linking 3D design and simulation with real-world equipment such as robots and sensors, the companies aim to replace fragmented systems with a more connected, software-defined manufacturing model.

Virtual twins enable pre-validation and continuous optimization

At the core of the collaboration is the integration of Dassault Systèmes’ 3D UNIV+RSES platform with OMRON’s Sysmac automation platform.

This enables the creation of a “Virtual Twin of Production Systems,” allowing manufacturers to “test a new production line, validate robot behavior, or optimize logistics flows—prior to building anything physically.”

The approach extends beyond initial deployment. Once production lines are operational, real-time data from sensors and controllers feeds back into the virtual environment, enabling comparison between simulated and actual performance, as well as predictive maintenance and ongoing optimization.

From automation to autonomy

For Dassault Systèmes, the partnership reflects a broader shift toward intelligent, adaptive manufacturing systems.

“Manufacturing is entering a new era. With OMRON, we are building living production systems, AI-driven, self-improving, and software-defined, where the virtual and physical worlds are fused into one continuous loop of learning,” said Pascal Daloz.

“Our industry world models transform complexity into intelligence, making factories not just automated, but autonomous. This is how we reinvent industrial systems, from reactive to predictive, from rigid to adaptive and define the next frontier of manufacturing.”

Delivering a unified IT/OT manufacturing model

For OMRON Corporation, the collaboration strengthens its ability to deliver integrated solutions spanning both operational and information technologies.

“Our partnership with Dassault Systèmes strengthens our ability to integrate the OT and IT worlds and provide customers with a holistic solution from simulated to fully implemented, intelligent production,” said Motohiro Yamanishi.

Toward a continuous digital manufacturing loop

By converging IT and OT systems into a continuous digital loop, the partnership is positioned to help manufacturers reduce errors, lower costs, and improve flexibility across increasingly complex production environments.

The combined platform enables a lifecycle approach—from simulation and validation to real-time optimization—marking a shift toward fully connected, AI-driven manufacturing systems.

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A POWERFUL FRAMEWORK

A new chapter in automotive innovation is unfolding as Stellantis strengthens its strategic collaboration with Microsoft, accelerating a sweeping AI-led transformation across its global operations. Announced on April 16, 2026, the five-year partnership signals a decisive push towards a more agile, data-driven, and digitally interconnected future.

Building on a longstanding alliance, the two companies are combining Stellantis’ engineering expertise and multibrand scale with Microsoft’s advanced cloud, AI, and security capabilities. The result is a powerful framework designed to embed intelligence across every layer of the automotive value chain, from design and manufacturing to customer interaction.

AI AT SCALE

Central to the collaboration is the co-development of more than 100 AI initiatives spanning sales, customer care, product development, and operational processes. These initiatives are designed to unlock faster, smarter innovation through advanced analytics and secure data insights.

Key focus areas include AI-powered product development and validation, predictive maintenance and testing, and the rapid deployment of new digital features and services. Together, these capabilities are reshaping how vehicles are designed, built, and experienced.

For customers, this translates into tangible benefits. Drivers can expect intelligent, real-time insights that enhance efficiency and usability, such as personalised recommendations for energy-efficient driving or proactive vehicle health updates. By placing AI at the heart of its ecosystem, Stellantis is reinforcing its commitment to customer-centric innovation.

CYBERSECURITY REINVENTED

As vehicles and services become increasingly connected, cybersecurity has emerged as a critical priority. Stellantis is addressing this challenge head-on through the deployment of an AI-driven global cyberdefense centre.

This unified platform spans IT systems, connected vehicles, manufacturing sites, and digital services, enabling faster threat detection, consistent protection of customer data, and enhanced resilience across operations. AI-driven analytics will allow Stellantis to anticipate and respond to cyberthreats with unprecedented speed and precision.

Importantly, cybersecurity is being embedded directly into the digital vehicle experience. From mobile applications to in-vehicle systems, customers will benefit from secure, reliable connectivity wherever they travel, ensuring confidence in an increasingly digital driving environment.

CLOUD-POWERED TRANSFORMATION

Underpinning these advancements is a major cloud modernisation programme powered by Microsoft Azure. Stellantis is targeting a 60 percent reduction in its datacentre footprint by 2029, a move that will significantly enhance agility, scalability, and performance.

This transition is enabling a more interconnected digital ecosystem capable of supporting seamless global delivery of connected services. At the same time, it strengthens operational resilience across manufacturing and logistics, ensuring the company can respond quickly to evolving market demands.

EMPOWERING THE WORKFORCE

Beyond technology, the collaboration is also transforming how Stellantis employees work. The company is equipping its global workforce with enterprise-grade AI tools, including widespread access to Copilot Chat and the rollout of 20,000 Microsoft 365 Copilot licences.

Supported by a dedicated training programme, these tools are enhancing productivity, streamlining collaboration, and enabling teams to integrate AI into their daily workflows. This people-centric approach ensures that innovation is not only driven by technology, but also by the individuals using it.

A SHARED VISION FOR THE FUTURE

As the partnership evolves, Stellantis and Microsoft will continue to work closely alongside certified partners to accelerate priority programmes and unlock new opportunities across engineering, manufacturing, and supply chain operations.

With AI, cybersecurity, and cloud innovation converging at scale, Stellantis is positioning itself at the forefront of the automotive industry’s digital evolution. Through its collaboration with Microsoft, the company is not only redefining mobility, but also shaping the future of connected, intelligent transportation.

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Renewable energy moves from ESG to core business strategy

For General Motors, energy strategy is no longer a sustainability side initiative—it is central to business performance.

“Managing energy use isn’t just a checkbox for a corporate environmental report these days; it’s a business necessity,” said Cassandra Garber.

That framing comes as GM reached a major milestone in 2025, securing enough renewable energy to match 100% of its electricity consumption across all U.S. facilities—making it the first U.S. automaker to achieve the benchmark.

Scaling renewable energy across a complex manufacturing footprint

The milestone reflects the scale of GM’s U.S. operations, which include assembly plants, design centers, and corporate offices nationwide.

The company’s approach is based on annual “energy matching,” ensuring that every kilowatt-hour of electricity consumed is offset by renewable energy procurement.

“GM contracts for enough clean energy… to equal every kilowatt-hour it pulls from the grid,” Garber wrote, comparing the model to balancing a bank account: “As long as you deposit as much money as you withdraw, your account is balanced.”

Projects such as Newport Solar and Hilltopper Wind Farm are part of that portfolio, with GM prioritizing developments located on the same regional grids as its facilities.

Global progress accelerates alongside U.S. leadership

While the U.S. milestone marks a first for the domestic auto sector, GM is also scaling internationally.

Globally, the company matched 70% of its electricity usage with renewables in 2025—nearly double its 2023 level—supported by projects in Mexico and Brazil, and continues to pursue 100% worldwide.

At the same time, GM reports it has reduced operational emissions (Scope 1 and 2) by 52% since 2018, aligning energy strategy with its broader zero-emissions ambitions.

Economic impact strengthens the business case

GM’s renewable energy investments are also delivering measurable economic value across its supply chain and communities.

Since 2015, domestic renewable projects have generated approximately $1.9 billion in GDP impact, with contracted projects through 2026 expected to add a further $333 million.

These developments support an average of 1,500 construction jobs annually across multiple states, while contributing local tax revenues that fund schools and emergency services.

Energy transition delivers operational advantages

Garber emphasized that the shift to renewable energy is not only about emissions reduction but also about strengthening operational resilience and cost stability.

“GM’s transition to clean energy isn’t just better for the environment — it’s smart business,” she said.

The company points to several key benefits:

• “Price stability: Long-term renewable contracts insulate GM from energy market volatility.”

• “Grid resilience: More clean energy on the grid means a more dependable system for everyone.”

• “Energy independence: Reduced reliance on foreign energy imports strengthens the local communities our facilities depend on.”

Supply chain engagement becomes the next frontier

GM is now extending its decarbonization efforts beyond its own operations, signaling expectations across its supplier ecosystem.

“GM is also sending a clear signal to suppliers and partners: join this decarbonization journey,” Garber noted, highlighting initiatives such as Transform: Auto aimed at accelerating renewable energy adoption across the automotive value chain.

From factory floor to EV future

The company’s renewable energy strategy is already embedded in key manufacturing sites.

Facilities such as Factory ZERO in Detroit and Spring Hill Manufacturing in Tennessee are powered through clean energy programs, supporting production of electric vehicles including the Chevrolet Silverado EV, GMC Sierra EV, and Cadillac LYRIQ.

For Garber, the connection between clean energy and electrification is direct.

“The zero-emissions journey starts before an EV customer ever hits the accelerator,” she said.

Decarbonization and growth go hand in hand

Looking ahead, GM’s progress is positioned as proof that sustainability and economic performance can align at scale.

“Achieving GM’s renewable goal in the U.S., and making continued progress internationally, proves that decarbonizing its footprint and driving economic growth aren’t in conflict,” Garber said. “GM is building the vehicles — and the energy systems — that will help us all enjoy an all-electric future.”

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Strategic collaboration scales global AI capacity, custom silicon adoption and enterprise access

The agreement includes a commitment from Anthropic to spend more than $100 billion over the next decade on Amazon Web Services (AWS) technologies, alongside Amazon’s plan to invest $5 billion immediately and up to an additional $20 billion in the future, tied to commercial milestones.

At the core of the partnership is a significant expansion of compute capacity. Anthropic will secure up to 5 gigawatts (GW) of infrastructure capacity using Amazon’s Trainium chips to train and power advanced AI models.

The collaboration spans multiple generations of custom silicon, including Trainium2, Trainium3 and future iterations, alongside tens of millions of Graviton CPU cores. This is designed to deliver improved price performance and scalability for large-scale AI workloads.

The companies are also continuing joint development efforts through Project Rainier—one of the world’s largest AI compute clusters—which uses nearly half a million Trainium2 chips to train and deploy Anthropic’s Claude models.

Expanding global AI deployment across cloud ecosystems

The partnership also strengthens international reach, with expanded inference capabilities planned across Asia and Europe to support growing enterprise demand.

Anthropic’s Claude Platform will now be available directly within AWS, allowing customers to access the full developer experience through existing AWS accounts without additional credentials or billing relationships. This complements availability via Amazon Bedrock, giving enterprises flexibility in how they deploy and scale AI applications.

More than 100,000 customers are already running Claude models on AWS, making it one of the most widely adopted model families on the platform.

Driving enterprise AI adoption across industries

The collaboration is focused on enabling organisations to build, deploy and scale AI applications more efficiently across sectors.

Andy Jassy, CEO of Amazon, said:

“Our custom AI silicon offers high performance at significantly lower cost for customers, which is why it’s in such hot demand. Anthropic’s commitment to run its large language models on AWS Trainium for the next decade reflects the progress we’ve made together on custom silicon, as we continue delivering the technology and infrastructure our customers need to build with generative AI.”

Dario Amodei, CEO and co-founder of Anthropic, added:

“Our users tell us Claude is increasingly essential to how they work, and we need to build the infrastructure to keep pace with rapidly growing demand. Our collaboration with Amazon will allow us to continue advancing AI research while delivering Claude to our customers, including the more than 100,000 building on AWS.”

Strengthening engineering collaboration and innovation pipeline

Beyond infrastructure, the partnership includes close engineering collaboration between Anthropic and Amazon’s Annapurna Labs to optimise future generations of Trainium chips. This includes direct feedback from AI training workloads to inform chip design and performance improvements.

Anthropic continues to use AWS as its primary training and cloud provider for mission-critical workloads, while Amazon developers are also leveraging Claude models to enhance customer-facing services across its ecosystem.

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New Yard Operating System integrates automation, AI and electrification for multi-site yard operations

The system reflects a broader shift in logistics toward integrating physical yard operations with digital intelligence, enabling more consistent and measurable performance in one of the supply chain’s most operationally complex areas.

The enhanced platform, YMX OS, is positioned to help enterprise shippers improve visibility, efficiency and sustainability across multi-site supply chain networks.

End-to-end yard orchestration combines data, AI and automation

The expanded YMX OS brings together multiple technologies into a unified operating model. Core components include an embedded Yard Management System (YMS) for real-time visibility and control, alongside automated data capture tools such as self-service kiosks, computer vision-enabled location systems and mobile applications.

At the centre of the platform is an “Autonomous Operational Twin,” a digital twin decision engine powered by artificial intelligence and predictive analytics. This enables continuous optimisation of yard operations, including layout design, fleet sizing, labour planning, traffic flow and electrification strategies, while quantifying both operational and financial impacts.

YMX is also integrating electric vehicle (EV) operations into the system, aligning workflows, charging infrastructure and energy management to improve utilisation and reduce costs.

From labour-driven operations to system-led performance models

A key element of the launch is a shift in commercial structure. YMX is introducing a performance-aligned pricing model tied to execution and system efficiency, moving away from traditional labour- or equipment-based pricing approaches that often limit visibility into true cost drivers.

Matt Yearling, Chief Executive Officer of YMX Logistics said:

“What’s been missing in yard operations isn’t more tools. It’s a system that connects execution to measurable outcomes. The Yard Operating System standardizes how yards are run, allowing enterprise shippers to continuously improve transportation and warehousing performance, resulting in major financial, sustainability, and safety gains across their networks.”

Erin Mitchell, Chief Operating Officer of YMX Logistics, added:

“Most yard operations today are managed as labor-driven functions rather than controlled systems. By standardizing execution, instrumenting the yard with digital intelligence, and aligning operations to performance outcomes, we’re giving enterprise shippers the most predictable and measurable way to operate one of the most challenging parts of their network.”

Early deployments show efficiency, cost and sustainability gains

The system has already been implemented in large-scale environments. At a major distribution centre operated by a top-five U.S. grocery retailer, YMX reports reduced yard truck fleet requirements, alongside improvements in throughput and safety performance.

Fuel consumption, emissions and operating costs also declined, with the programme expanded to nine additional facilities within six months.

Industry observers highlight the strategic importance of this shift

Bart De Muynck, founder of Better Supply Chains, said:

“In an era defined by global volatility, yard operations can no longer remain a dark spot in the supply chain. What YMX has built is a new operating model for the yard. By converging physical execution with digital intelligence, their teams are enabling autonomous orchestration and continuous optimization, giving enterprise shippers predictable performance and genuine resilience across their distribution networks.”

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Tree-planting commitment expands beyond supply chains to support long-term sustainability goals

The initiative reflects a broader sustainability strategy focused not only on responsible sourcing, but also on ecosystem restoration and community resilience beyond direct supply chains.

The move builds on an earlier phase that saw 1 million trees planted between 2020 and 2025 in areas affected by natural disasters.

Chris Reeves, Certified Forester and Senior Scientific Communications Leader at P&G, said:

“Charmin is committed to helping keep forests as forests, which is why we participate in several initiatives to protect, grow and restore forests. Our partnership with the Arbor Day Foundation helps us make an impact in areas beyond our supply chain that have been affected by natural disasters.”

Restoration efforts target climate-impacted regions and community resilience

The programme prioritises reforestation in areas where forests have been damaged by events such as wildfires and hurricanes. According to the Arbor Day Foundation, its approach combines ecological restoration with community engagement, working with local planting partners to ensure appropriate tree selection and long-term recovery outcomes.

Dan Lambe, Chief Executive at the Arbor Day Foundation, said:

“A more hopeful future can be shaped through the power of trees. We are proud to partner with brands like Charmin that are bold enough to be part of our effort to plant trees in the areas that need them most. Our partnership with Charmin has already made a positive impact in multiple disaster-affected communities and we’re eager to continue this important work.”

Linking responsible sourcing with ecosystem restoration

The initiative complements Charmin’s broader forestry approach, which is structured around three pillars: protecting, growing and restoring forests. The company states that it uses pulp certified by the Forest Stewardship Council, regrows at least two trees for every tree used, and supports restoration through partnerships such as the Arbor Day Foundation.

For sustainability and supply chain stakeholders, the programme highlights how companies are increasingly linking upstream sourcing practices with downstream environmental and social impact—particularly in response to rising climate risks and stakeholder expectations.

Long-term partnership driving measurable impact

P&G and the Arbor Day Foundation have worked together since 2020, including through the Foundation’s Evergreen Alliance, which supports large-scale tree planting and awareness initiatives. The collaboration contributed to broader efforts to plant 100 million trees and engage 5 million tree planters by 2022.

With forests supporting 1.6 billion people globally and 80% of plant and animal species, the partners emphasise that restoration initiatives can deliver wide-ranging benefits, from biodiversity protection to improved air and water quality.

The expanded commitment signals continued investment in nature-based solutions as companies seek to balance operational sustainability with broader environmental stewardship.

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