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IBM Launches New Power Systems and Software Built for Enterprises to Address Risk, Productivity, and Flexibility

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New IBM Power Autonomous Operations software identifies and resolves capacity constraints up to 15×1 faster than manually performing the operationIBM Bob™ Premium Package for i helps accelerate application development on IBM iEntry-level Power S1112 server helps enterprises innovate at every scale

ARMONK, N.Y., July 15, 2026 /CNW/ — IBM (NYSE: IBM) today announced IBM Power Autonomous Operations, an AI agent that can help continuously monitor Power systems and autonomously resolve issues to keep operations running smoothly. It complements the recently launched IBM Bob™ Premium Package for i, which brings agentic-driven software designed to accelerate application development on IBM i. These capabilities can accelerate building modern applications so enterprises can innovate at the pace required by their business. Additionally, the entry-level Power S1112 server provides a new compact, efficient option powerful enough to run AI inference locally.

IBM Power has long been IBM’s platform for mission-critical enterprise workloads. As AI becomes part of that critical infrastructure, Power is built to support it.  IBM introduced Power11 last year as autonomous IT for the AI era, built for availability, resiliency, and scale across on-premises and IBM Cloud environments. IBM Power Virtual Server is a fully managed cloud service on which enterprises can run AIX, IBM i and Linux workloads while offloading much of the routine management for system operations. Now, IBM is embedding autonomous IT across the Power platform, from code to runtime, with new capabilities and systems.

According to the IBM IBV 2026 Tech Leader Study: Building the IT foundation for agentic AI at scale, by 2027, enterprises expect to deploy an average of 1,661 AI agents–a 38% increase. At that rate, tech leaders are tasked with managing hundreds of thousands of autonomous decisions daily. And manual governance can’t keep up with that math.2 Additionally, according to the IBM Institute for Business Value, Enterprise 2030 study, AI is changing what companies do and how they do it.3 Closing that gap in scale requires an IT foundation that can run and optimize itself while teams focus on innovation.

These newly announced capabilities utilize AI agents to build automation directly into IBM Power across operations, security, and application development so clients can innovate with AI while prioritizing control and resilience. Power Autonomous Operations automates running and optimizing systems, with an embedded agent that lets teams manage Power through simple chat-style prompts. IBM Bob Premium Package for i makes IBM i development accessible to a broad range of engineers, expanding who can build and modernize their applications on the platform.

“Enterprises should not need to choose between moving at the speed of AI and keeping their systems stable and secure,” said Hillery Hunter, General Manager for IBM Power and CTO, IBM Infrastructure. “We’re making Power increasingly self-operating, so the routine work of helping to keep systems available, optimized, and secured can happen autonomously, and our clients’ teams can spend their time on innovation instead of upkeep. That’s how a business scales AI with control and resilience.”

IBM Power S1112: Extending the Capabilities of Power Servers

As enterprises push AI workloads beyond the data center, the IBM Power S1112 is a new one-socket Power11 system built for compact on-prem deployment. The S1112 runs AI workloads locally using Power11 on-chip Matrix Math Acceleration (MMA) for faster inferencing. Power S1112 offers 2x better core performance versus Power S9144 and 3x better core performance versus Power S8145  — with up to 69% greater energy efficiency than the S9146.

To provide clients with the right level of support for this new system, IBM Technology Lifecycle Services is introducing IBM Power Expert Care Premium Essentials, a new incident-focused support tier available exclusively for the Power S1112. Premium Essentials delivers priority access to IBM experts, accelerated response, and intelligent support automation.

IBM Power Autonomous Operations: Managing Infrastructure Through Conversation

IBM Power Autonomous Operations resolves capacity constraint issues up to 15x faster than manual intervention7. Today’s enterprise systems can seem to demand constant attention, but manual operations management can make it difficult to manage. IBM Power Autonomous Operations redefines this model by automating and optimizing day-to-day operations across the IBM Power environment. An embedded AI agent that enables natural, conversational interaction can help teams to manage, tune, and streamline their environments without relying on deep domain expertise for every task. The result is a resilient, self-optimizing infrastructure architected to reduce operational burden while accelerating performance and uptime.

IBM Bob Premium Package for i: Making IBM i Development Accessible to More Engineers

IBM i is a fully integrated operating system that remains a vital part of the core business of many companies across major industries, yet modernizing IBM i applications has historically required specialized skills for RPG applications. To help address this challenge, IBM Bob is an AI-powered development assistant that offers an agentic SDLC experience for enterprise developers.

IBM Bob Premium Package for i is engineered to provide built-in support for IBM i conventions and patterns across the full development lifecycle, to help engineers make changes faster, onboard sooner, and evolve applications while prioritizing team capacity along the way. From understanding complex code to moving modernization and AI projects forward, IBM Bob can expand the pool of developers who improve the IBM i applications that organizations depend on every day. Early adopters are already seeing results: Heartland Co-Op estimates 60% faster time for new-to-platform developers to understand complex applications.8

Client Momentum

Clients and partners are already running IBM Power on premises and in the cloud, drawn by its performance, resilience, and hybrid flexibility:

“For a business like ours, reliability and simplicity matter because our customers depend on us every day. IBM Power and IBM i have consistently delivered the stability and security we need to support our operations with confidence. And that continues with the introduction of IBM Bob and the IBM Power S1112. What excites me most about the new Power S1112 is the ability to do more with less through increased capacity, energy efficiency, and the growing focus IBM has on automation, making systems easier to manage for small and midsized businesses. We are also excited about how IBM Bob for IBM i can help our team accelerate modernization by quickly interpreting older RPG code, tracing field logic, generating documentation, and making decades of system knowledge easier to understand and act on. Together, IBM Power, IBM i, and IBM Bob give us a forward-looking foundation to modernize with confidence while continuing to deliver the reliability our business depends on.” Jasmine Kaczmarek, vice president of technology, M.R. Williams.

“What I noticed about IBM Bob almost immediately was the level of detail provided as compared to other AIs. I like using AI to build and execute plans for specific projects. Given the exact same prompt, Bob’s planning was always 10-fold more detailed than other AIs. More specifics, more details, and provided a better understanding of the steps through the project from beginning to end.” Bob Richardson, ERP Support Analyst, Wynne Systems, Inc.

“The new IBM Power S1112 provides us with the flexibility to expand beyond traditional workloads and explore new AI opportunities by running Linux partitions alongside our IBM i environment,” said Andy Buchholtz, Owner, Innovative Software Solutions. “Combining that flexibility with the security, reliability, and resilience we trust from the IBM Power platform gives us confidence as we continue to innovate and modernize our business.”

“We’re no longer reacting to weather. We’re prepared for it,” said Chad Simpson, CIO, City Home. “Our infrastructure is built to keep the business running, no matter what. We’ve honed our process to perform role swaps every quarter, and this capability gives us great confidence in our business continuity posture. It’s a powerful thing, and it’s all thanks to IBM Cloud and Power Virtual Server.”

Availability

IBM Power S1112 is expected to be generally available on July 24, 2026, IBM Power Autonomous Operations is expected to be generally available on September 23, 2026, and IBM Bob Premium Package for i was made generally available on June 24, 2026. To learn more, visit ibm.com/power.

Statements regarding IBM’s future direction and intent are subject to change or withdrawal without notice and represent goals and objectives only.

About IBM

IBM is a leading provider of global hybrid cloud and AI, and consulting expertise. We help clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. Thousands of government and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM’s hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently and securely. IBM’s breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and consulting deliver open and flexible options to our clients. All of this is backed by IBM’s long-standing commitment to trust, transparency, responsibility, inclusivity and service.

Additional Sources

Power S1112 and autonomous IT capabilities blogIBM Power S1112 product page IBM Institute for Business Value Enterprise 2030 study 

Media contact:

Sarah Fraser
IBM Infrastructure Communications
sarah.fraser@ibm.com

1 Disclaimer 1: The performance and capacity management efficiency claim is based on IBM internal testing conducted in a controlled, representative IBM Power infrastructure environment consisting of eleven IBM Power systems. Capacity thresholds and alerting policies were preconfigured prior to test execution. Under this configuration, the manual operational process entailed–navigating to the performance dashboard for each system, exporting performance data to CSV/XLS format, reviewing and analyzing the data to identify required capacity adjustments, and implementing the changes–required on average 52.59 minutes to detect and resolve capacity‑related conditions across the eleven systems. In a comparable scenario, IBM Power Autonomous Operations, which includes alert ingestion and AI-based, agent-driven diagnostic analysis producing recommended and remedial actions with human-in-the-loop approval to remediate, completed the same process in on average 3.33 minutes.
https://www.ibm.com/thought-leadership/institute-business-value/en-us/c-suite-study/cxo
3 https://www.ibm.com/thought-leadership/institute-business-value/en-us/report/enterprise-2030
4 Based on published CPW results comparing Power S1112/4 core to IBM Power S914/4 core. Valid as of 7/14/2026 and available at: https://www.ibm.com/downloads/documents/us-en/10c31775c5d40fed
5 Based on published CPW results comparing Power S1112/4 core to IBM Power S814/4 core. Valid as of 7/14/2026 and available at: https://www.ibm.com/downloads/documents/us-en/10c31775c5d40fed
6 Based on system capability of Power S1112/10c performance 291,300E CPW (extrapolated from 116,500 CPW for 4-cores) @ 540E Watts (539 Performance/Watt) compared to Power S914/8cperformance of 122,500 CPW @ 383 Watts (319 Performance/Watt); 539 / 319 = 1.69 more Performance/Watt
7 Disclaimer 1: The performance and capacity management efficiency claim is based on IBM internal testing conducted in a controlled, representative IBM Power infrastructure environment consisting of eleven IBM Power systems. Capacity thresholds and alerting policies were preconfigured prior to test execution. Under this configuration, the manual operational process entailed–navigating to the performance dashboard for each system, exporting performance data to CSV/XLS format, reviewing and analyzing the data to identify required capacity adjustments, and implementing the changes–required on average 52.59 minutes to detect and resolve capacity‑related conditions across the eleven systems. In a comparable scenario, IBM Power Autonomous Operations, which includes alert ingestion and AI-based, agent-driven diagnostic analysis producing recommended and remedial actions with human-in-the-loop approval to remediate, completed the same process in on average 3.33 minutes.
Heartland Co-op Modernizes Grain Operations with IBM i and IBM Bob

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SOURCE IBM

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JAMS Launches AI for Enterprise Job Scheduling: JAX and JAMS MCP, on the Model You Choose

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A new AI agent and an open-standard connector let IT teams query, diagnose, and manage automation in plain language, on the model they choose, with operational data staying inside their own network

LONDON, July 24, 2026 /PRNewswire/ — JAMS Software, an orchestration solution for scheduled and event-driven automation, today announced the general availability of two AI capabilities for enterprise job scheduling: JAX, an AI agent built into the JAMS Web Client, and JAMS MCP, a connector built on the open Model Context Protocol standard that brings JAMS into external AI coding tools. Both capabilities ship at no additional cost as part of JAMS Web.

Automation environments grow faster than the teams that run them. Jobs multiply across SQL Server, Azure Data Factory, Airflow, SAP, JDE, and Banner, and when one fails, finding the root cause often means searching several consoles at once, frequently outside business hours. At the same time, IT leaders carry pressure to adopt AI while staying accountable for where operational data goes. JAX and JAMS MCP close both gaps together.

Full details on how JAX and JAMS MCP work, including the control model behind every action, are available at jamsscheduler.com/product/ai.

JAX is an AI agent that runs inside the JAMS Web Client. It finds jobs, troubleshoots failures, and answers how-to questions in plain language, with each response grounded in the JAMS user guide and checked against a built-in glossary. JAX acts only when a user asks it to. Reads flow freely, and every write action pauses for the user’s explicit approval before it runs. JAX does not learn between sessions, and conversations are not retained on the server.

JAMS MCP is a connector, built on the open Model Context Protocol standard, that brings JAMS into the AI tools engineering teams already use, including Cursor, VS Code with Copilot, Claude Code, Claude Desktop, and Codex. Users query jobs, investigate failures, and manage runs in plain language without leaving their tool.

Both capabilities run inside the customer’s own network and act as the signed-in user, with that user’s exact JAMS permissions. There is no elevated AI account: whatever a user cannot do in the JAMS interface, JAX and JAMS MCP cannot do on that user’s behalf. Every JAX and MCP operation is recorded in its own dedicated log, and changes made through the JAMS API land in the JAMS audit trail like any other change. Customers choose their own AI model, whether a commercial provider such as OpenAI or Anthropic or a model running entirely on their own hardware, and JAMS never trains on customer data. In the current release, neither feature edits or deletes a job, folder, schedule, or agent definition. For teams that must keep operational data within a defined boundary, JAX runs on a local model entirely inside the customer’s own network, so nothing leaves at all.

“Adopting AI usually means giving something up, most often visibility into where your data goes,” said Pete Hegland, Chief Executive Officer of JAMS Software. “We built JAX and JAMS MCP so that trade does not have to happen. Every action runs as the signed-in user, every change waits for approval, and the model itself can run entirely inside your own network.”

“IT teams across the United Kingdom and EMEA tell us the same thing: they want the benefit of AI without losing sight of where their data goes,” said Greg McLaughlin, Account Executive for EMEA at JAMS Software. “JAX and JAMS MCP let them keep operational data inside their own network and still get answers in plain language. That combination is what makes this practical for the teams I work with.”

JAX and JAMS MCP are available now to all JAMS Web customers across the United Kingdom and EMEA, with no separate licence, SKU, or additional cost. AI-assisted creation of new jobs and workflows from a plain-language description is on the roadmap for a future release, gated by the same approvals and permissions as every other action.

Learn how JAX and JAMS MCP work at https://jamsscheduler.com/product/ai.

Fast facts

JAX is an AI agent built into the JAMS Web Client for job scheduling and workflow automation.JAMS MCP is a connector built on the open Model Context Protocol standard, for Cursor, VS Code with Copilot, Claude Code, Claude Desktop, and Codex.Both act as the signed-in user, with that user’s exact JAMS permissions, and there is no elevated AI account.Customers choose the AI model, including a local model that runs entirely inside their own network.JAMS never trains on customer data.Both are available now at no additional cost as part of JAMS Web.

About JAMS Software

Founded in 1987, JAMS Software is an orchestration solution that helps IT teams centralize, automate, and manage scheduled and event-driven jobs across complex, hybrid environments. Over 850 customers rely on JAMS to run their automated workloads. JAMS Software, LLC is headquartered at 108 Patriot Drive, Suite A, Middletown, DE 19709.

Media Contact
Bobby Schmidt, Vice President of Marketing
press@jamssoftware.com
800.261.4267

 

 

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Video: CNPC offers green chemical answer

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BEIJING, July 24, 2026 /PRNewswire/ — A news report from chinadaily.com.cn:

Located on the edge of the Taklamakan Desert in Northwest China’s Xinjiang Uygur autonomous region, the Tarim 1.2 MTA Phase II Ethylene Project and its supporting green and low-carbon demonstration facility of PetroChina Dushanzi Petrochemical Company, a subsidiary of China National Petroleum Corporation, are offering a new example of China’s low-carbon industrial transformation.

Watch the video to discover how CNPC is exploring a cleaner and more circular future for the industry.

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SOURCE chinadaily.com.cn

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Shanghai Electric showcases embodied intelligence robot matrix and AI-native smart factory solutions at WAIC 2026

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Featuring humanoid robots with 41 degrees of freedom, pipe‑inspection robots with ±1mm positioning accuracy, and 51 industrial‑grade AI agents

SHANGHAI, July 24, 2026 /PRNewswire/ — Operations in high-end equipment manufacturing often involve confined spaces, complex objects, and fine manipulation tasks that demand sustained and stable precision. At the recent 2026 World Artificial Intelligence Conference and High-Level Meeting on Global AI Governance (WAIC 2026), Shanghai Electric (SEHK: 02727, SSE: 601727) showcased its comprehensive portfolio of embodied intelligence solutions tailored to a range of industrial scenarios.

Themed “AI for All: Smart Squad, Shining Without Limits,” Shanghai Electric highlighted its capabilities across embodied AI robots, robot core components, and AI-native smart factory solutions, demonstrating end-to-end capabilities spanning complete robot systems, critical parts, industrial software, and smart factory architecture.

“The true value of embodied intelligence lies in understanding real industrial tasks: combining the strength, precision, and stability of machines with human experience and judgment to drive a genuine paradigm of ‘machine-assisted, human-machine collaboration,'” said Wang Chunlei, deputy general manager of the Robotics Business Unit at Shanghai Electric Automation Group.

Shanghai Electric’s robotics portfolio covers five key industrial scenarios: connector insertion, electrical operations, flexible sorting, intelligent assembly, and pipe processing. Highlights include:

“SUYUAN” bipedal humanoid robot: With 41 degrees of freedom for enhanced mobility, it is equipped with a multimodal visual sensing system on the head and torso, along with a dual-battery hot-swap system. It is well-suited for inspection, material handling, and assembly tasks.”TUOYUAN” industrial wheeled humanoid robot: Powered by an embodied intelligence foundation model and force-position hybrid control, it is capable of multi-spec connector insertion, material sorting, and loading/unloading of automotive sheet metal parts.”Mermaid” bionic wheeled humanoid robot: Capable of autonomously identifying buttons, knobs, and air switches, it generates real-time operation paths.Autonomous pipe inner-wall chamfering robot: Designed for confined spaces, it can position and process thousands of hole edges with accuracy within 1 millimeter while transmitting data in real time.

Shanghai Electric also showcased its portfolio of core components ranging from power-output to end effectors. Among them, the planetary roller screw offers more than three times the load capacity of traditional ball screws, while the DexHand dexterous hand is designed to meet diverse gripping and manipulation requirements.

Shanghai Electric launched 51 AI models and agents under its “StarCloud Intelligent Manufacturing” series across three domains: R&D and design, production and manufacturing, and operations and maintenance—covering critical equipment processes such as process optimization and wind power facility maintenance.

These industrial agents are embedded in robotic decision-making systems and the operational logic of AI-native smart factories, transforming industrial expertise into digitized, reusable capabilities. They support production-line scheduling, quality inspection, and predictive maintenance, driving the evolution of manufacturing systems from experience-driven to data-driven operations.

Shanghai Electric also released the “AI-Native Smart Factory Technology White Paper,” proposing an active evolution architecture that enables real‑time, closed‑loop optimization of production data, giving the factory self‑perception, self‑decision, and self‑execution capabilities. Built on First Principles, the AI‑native smart factory vertically integrates process flows, industrial software, agents, and smart equipment to dismantle traditional hierarchies while horizontally bridging data silos. The architecture features three core layers: the AI factory brain as the “control center,” industrial agents and embodied robots as the “execution network,” and the physical twin as the “digital mirror.”

Leveraging its deep industrial expertise and comprehensive solution capabilities, Shanghai Electric will continue to drive the implementation of AI in industrial settings, tackle technical challenges facing embodied intelligence in complex scenarios, accelerate the large‑scale deployment of AI‑native smart factories, and deliver replicable solutions across diverse manufacturing environments.

SOURCE Shanghai Electric

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