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07/05/2026

About IBM Sovereign Core: It combines platform services, the control plane and security capabilities into a single deployment model. The platform is designed to run on customer-provided infrastructure across compute, storage and network layers.

The customer operated control plane is deployed within the sovereign boundary to manage provisioning, configuration, and lifecycle operations across platform services and tenant environments. Core services for identity, access control and encryption key management also operate in-boundary, with logs and audit records operate in-boundary, helping organizations maintain operational authority over the environment.

IBM Sovereign Core’s open, modular architecture enables customers to extend sovereign environments while maintaining control over data, operations and technology within the sovereign boundary.

IBM Sovereign Core is built on an open-source foundation, providing customers with enhanced visibility, certainty and control of the key technology. IBM’s published Statement of Direction outlines a commitment to open-source core components of the software foundation, reinforcing IBM’s commitment to openness, transparency and client choice.

07/05/2026

May 5

IBM has announced general availability of IBM Sovereign Core. It is a new software platform designed to help organizations build and operate AI-ready sovereign environments and verify their control — giving enterprises and governments an end-to-end approach to digital sovereignty.

As AI adoption accelerates, digital sovereignty has become a critical requirement, extending beyond data residency to include control over infrastructure, operations, and AI systems. Organizations must balance maintaining necessary authority with the pace of innovation, while facing increasing scrutiny from regulators, auditors, and boards. Yet most platforms can struggle to provide consistent, auditable answers to these requirements — creating a gap between policy and operational reality.

"AI has made sovereignty a runtime requirement, not a policy statement. With IBM Sovereign Core, organizations don't have to choose between deploying AI at speed and verifying their control. Sovereignty shouldn't be a constraint on innovation — with the right software foundation, it's an enabler of it," said Dinesh Nirmal, SVP, IBM Software.

Defining Digital Sovereignty for the AI Era
IBM defines digital sovereignty across four pillars:

Operational Sovereignty — Control over how environments are operated

Data Sovereignty — Control over data at rest, in use, and in motion

Technology Sovereignty — Open, modular architecture that avoids vendor lock-in

AI Sovereignty — Control over where models run and how inference is governed.

Together, these pillars form the foundation of IBM's unified approach to digital sovereignty—bringing control across operations, data, technology, and AI.

A Unified Approach for Digital Sovereignty
IBM Sovereign Core introduces a new model for operational sovereignty, where governance, compliance, and control are built into the system from the start to enable organizations to scale AI while maintaining their sovereignty, trust, and operational independence. IBM Sovereign Core delivers an integrated sovereign software platform that combines control plane, identity, security, compliance, and AI ex*****on functions operate within a single deployment model.

Key capabilities include:
Customer-operated control plane enabling full authority over configuration, operations, and lifecycle management
In-boundary identity, encryption, and data services, ensuring all access, secrets, keys, logs, and audit evidence remain under customer control
Continuous compliance monitoring and evidence generation, providing real-time audit readiness
Preloaded regulatory frameworks to accelerate company defined compliance postures across regions and industries
Governed AI ex*****on, ensuring models, inference, and agent operations run within defined sovereign boundaries
Open, modular architecture built on open standards, supporting portability and avoiding vendor lock-in
Together, these capabilities establish a sovereign control plane that enables organizations to operate environments and verify their control across data, operations, and AI.

Continuous, Verifiable Compliance

IBM Sovereign Core enables organizations to move from static compliance models to dynamic continuous, verifiable compliance models that are verifiable. Integrated monitoring, drift detection, and automated evidence generation allow organizations to:
Validate compliance in real time
Maintain audit-ready evidence within the sovereign boundary
Reduce reliance on manual validation and point-in-time audits
This ensures sovereignty is not only defined, but observable, enforceable, and provable at scale.

07/05/2026

Global Smartphone Shipments Decline 4.1 percent amid memory constraints, according to IDC

Limited memory supply and record high memory prices increase pressure on smartphone OEMs to reduce shipments and increase prices that dampen demand.

According to preliminary data from the International Data Corporation (IDC) Worldwide Quarterly Mobile Phone Tracker, global smartphone shipments decreased 4.1 percent year-over-year (YoY) to 289.7 million units in the first quarter of 2026 (1Q26). This broke the 10 consecutive quarters growth streak that the market had seen since mid 2023. We expect the first quarter slowdown to be a mild precursor for what lies ahead in 2026 as the supply constraints around memory and price increases further dampen the market growth.

06/05/2026

https://youtu.be/OjO54dFcxI0

Looking back before we look ahead. From product innovation to customer impact, here’s a snapshot of what we accomplished in 2025. ▬▬▬▬▬ Connect with PTC► You...

06/05/2026

OMRON and Dassault Systèmes Partner to Revolutionize Manufacturing with Virtual and Real Integration

Dassault Systèmes and OMRON combine their respective expertise in virtual twins and industrial automation technologies to transform industrial production.

Information technology and operational technology converge to replace fragmented industrial systems with AI-driven, software-defined manufacturing.

Manufacturers can validate production systems virtually before deploying and during operations, reducing errors, costs and risks.

Dassault Systèmes and OMRON a global leader in industrial automation technologies, has announced their partnership to bridge the gap between information technology (IT) and operational technology (OT). This collaboration enables manufacturers and machine builders to design, simulate, and deploy smarter, more flexible, and higher-performing production systems through a unified approach that merges virtual and real environments.

Today’s factories often face a critical issue: product design, automation, and production systems operate in silos. This fragmentation leads to longer commissioning times, higher error risks, and limited flexibility. OMRON and Dassault Systèmes are breaking down these barriers by creating a seamless link between 3D design and simulation in the virtual world, and robots, sensors and production lines in the physical world.

The collaboration combines Dassault Systèmes’ 3D UNIV+RSES with OMRON’s Sysmac industrial automation platform, enabling manufacturers to design, simulate, validate and deploy production systems within a continuous virtual environment. At the core of the partnership is the Virtual Twin of Production Systems, which allows companies to test a new production line, validate robot behavior, or optimize logistics flows—prior to building anything physically.

Thanks to this IT/OT convergence, manufacturers benefit from a digital continuum before deployment and during operations. Production lines are designed, simulated, and validated in a virtual environment augmented by Virtual Companions. Performance, safety, maintenance and other scenarios are tested to correct errors before real-world deployment. Once the physical line is installed, real-time data from sensors, controllers, and robots is fed back into the virtual twin. This enables comparison between real and simulated behavior, fine-tuning, and predictive maintenance to reduce costs and risks.

05/05/2026

Dassault Systèmes and cosmetica

Groupe Rocher it Embarks on New Collaboration with Dassault Systèmes to Transform Natural Cosmetics Formulation Through Virtual Twin Technology

French pioneer of natural, effective and committed beauty and wellness products will rely on Dassault Systèmes’ science-based technology to accelerate the research and development of ever more effective cosmetic products.

Dassault Systèmes will build and deliver virtual twins capable of simulating and predicting how active ingredients interact with skin, to optimize formulations for improved efficacy.

Virtual twins combine generative AI, 3D modeling and simulations that will guide Groupe Rocher’s scientific teams in its formulation experiments, and will help bring innovations to market faster by reducing development time by 20 percent.

This collaboration aims to strengthen Groupe Rocher’s research and development with virtual twins — advanced science-based technologies already proven in all industries.

Today it takes an average of about 30 laboratory tests to find the right formulation. Groupe Rocher aims to accelerate this pace through its collaboration with Dassault Systèmes, while achieving greater efficiency gains. This new technological approach combines generative artificial intelligence, chemical modeling and simulation with expertise in plant-based active ingredients, providing teams with a predictive framework that complements their expertise and saves them valuable time, thereby optimizing the efficiency of their work and enhancing their performance.

02/05/2026

AI Sweden published a report based on many interviews. It writes:

”Relatively seen, the investments in transformation and change made by the interviewed companies are significant — for some, the largest of their kind in decades. All invest in capabilities, not least in human capital, such as building central teams of dedicated competences, level the knowledge among all leaders, and educate and enable employees to work effectively with AI in their daily tasks. Where relevant, this is complemented by investments in new ways of working — for example cross-functional teams and faster decision-making processes — as well as in new platforms, data foundations, and scalable compute.

The interviews also show the importance of investing in both good and challenging times, the reshaping needs to happen regardless.”

It writes also: Individuals actively reshape their organizations through data and AI.

29/04/2026

TCS och Google Cloud fördjupar samarbete för att accelerera AI för företag

Tata Consultancy Services (TCS) låter meddela att man fördjupar av sitt strategiska partnerskap med Google Cloud. Det syftar till att hjälpa företag att anamma autonoma driftsmodeller med AI i grunden, genom att stödja implementering och hantering av agentiska och autonoma AI-system. Detta möjliggör snabbare beslutsfattande över komplexa affärs- och IT-funktioner, utan att öka operationell risk eller komplexitet.

Dessa AI-agenter kommer också att bidra till att upprätthålla stark styrning, säkerhet och förtroende i reglerade och verksamhetskritiska miljöer. För att omsätta detta i praktiken lanserar TCS fyra erbjudanden som ska hjälpa företag att gå från AI-piloter till operationell autonomi inom sektorer där skala, tillförlitlighet och förtroende är avgörande.

Dessa inkluderar:
Agentic AI Data Accelerator – hjälper till att minska dataövergångscykler med upp till 40 %, samtidigt som den skapar en molnbaserad grund för AI i stor skala.

TCS Physical AI Blueprint – använder vision AI och agentisk orkestrering för att möjliggöra säkrare, semi-autonoma industriella miljöer.

TCS Smart Factory Blueprint – ett erbjudande med samma tekniska grund som ovan för smarta fabrikslösningar.

TCS AI SOC (security operations center) som drivs av Google SecOps – möjliggör snabbare, mer effektiv incidenthantering och åtgärd, vilket hjälper organisationer att bygga upp sin cyberförsvarskapacitet.

Kevin Ichhpurani, President - Global Partner Ecosystem, Google Cloud, säger: "Utökningen av vårt strategiska partnerskap med TCS är ett bevis på vårt gemensamma engagemang för att driva verklig företagsomvandling. Genom att kombinera Google Clouds AI-infrastruktur med TCS djupa branschexpertis och deras över 3 000 specialiserade agenter, ger vi kunderna möjlighet att gå bortom pilotprojekt till helt autonoma driftsmodeller med AI i grunden."

28/04/2026

IBM today (April 28) announced the global availability of IBM Bob, an AI-first development partner built for enterprise teams. Bob doesn’t just help developers write code fast. It works across the full software development lifecycle (SDLC), from planning and coding to testing, deployment, and modernization, with the governance and security controls enterprises need.
AI is changing how software gets built. But for most enterprises, that speed is running headfirst into decades of accumulated complexity: legacy systems, hybrid environments, compliance requirements, and the very real cost of getting it wrong. Fast AI without the right guardrails is not progress. It is just faster risk.
IBM Bob is designed to close that gap. It’s built on a structured framework that embeds Bob into every role across the development process – including persona-based modes, enforced standards, reusable playbooks, tool calling, and human-in-the-loop governance – so teams can move fast while staying in control.
Key capabilities include: AI-first SDLC orchestration: It is estimated that a significant portion of development effort is fragmented across tools, roles, and lifecycle stages—slowing delivery and introducing risk. Bob embeds agentic AI across the entire SDLC—from discovery and planning through design, coding, testing, deployment, and operations—coordinating specialized role-based agents, reusable skills, and governed workflows. Intelligent modernization: It is estimated that 60–80 percent of development budgets go toward modernization efforts that can take weeks or months. Bob coordinates specialized agents across code, tests, documentation, and pipelines to execute complete modernization tasks. For example, Bob helped cloud solutions and consulting services company Blue Pearl conduct a typical 30-day Java upgrade in just 3 days, saving over 160 engineering hours. Security controls built in from day one: AI isn’t just accelerating software development; it’s transforming the security landscape and introducing new risks. Bob includes prompt normalization, sensitive data scanning, real-time policy enforcement, and AI red-teaming directly within the development workflow, not as an afterthought. Auditability: AI-generated code can reach production without sufficient review, creating compliance blind spots. Bob’s CLI (BobShell) creates self-documenting agentic processes in real time, so every action is traceable from start to finish. Multi-model orchestration: Bob dynamically routes tasks to a suitable model based on accuracy, performance, and cost, drawing on a mix of frontier models including Anthropic Claude, Mistral open source models, and IBM Granite, alongside specialized fine-tuned models for code reasoning, security, and next-edit prediction. Simpler completions go to lighter models. Complex tasks go to more capable ones. The goal: better outcomes and lower spend. Transparency and developer control: Bob’s approval model lets developers configure checkpoints that match their workflow, from manual approvals to auto-approve by task type, keeping humans in the loop.

“Every business is racing to modernize. But speed without control and transparency is a liability. IBM Bob is how enterprises can move at AI speed without sacrificing the governance and security needs their businesses require. Bob was engineered by developers inside IBM for the millions like them worldwide, and it’s the foundation on which enterprises will become truly AI-first.” — Dinesh Nirmal, Senior Vice President, IBM Software.

Stop managing models. Start managing outcomes.
Enterprises don't have a model problem. They have an outcome consistency problem. As AI adoption matures, the challenge isn't which model to use, it's how to consistently get the best result across a rapidly evolving landscape without making model selection an ongoing engineering distraction.
Bob handles this automatically. It draws on a mix of frontier LLMs, open source models, IBM Granite SLMs, and specialized fine-tuned models to route each task to a suitable model based on accuracy, latency, and cost across the full SDLC, from planning and coding to testing and validation. With pass-through pricing and usage visibility, organizations can align AI spend to real outcomes rather than experimentation.

“Developers need a system that understands the full context of their work and can act on it. That's what we built with Bob. It's an agentic platform that embeds an AI partner into every role across the SDLC, from the architect sketching a design to the security engineer reviewing code before it ships. We built Bob around a simple belief: model capability alone isn't enough. How you deploy it, how you structure context, and how you keep humans in the loop is what determines whether AI actually delivers. With Bob, we’re helping developers to automate the mundane, and augment the complicated.” — Neel Sundaresan, General Manager, Automation & AI, IBM Software.

28/04/2026

The rise of the chief AI officer, and why “owning” AI is overrated

Written by writer Aili McConnon:

If you’ve been scanning corporate org charts lately, you may have spotted a title that barely existed a few years ago and now seems to be everywhere: chief AI officer. Meta has one. HSBC has one. Novo Nordisk has one. And they’re in good company.

According to a sneak preview of data that IBM’s Institute for Business Value (IBV) will share next week at Think 2026, 76 percent of companies surveyed now have a chief AI officer—up from just 11 percent in 2023. And nearly 70 percent of CEOs believe the role will be in place by 2030.

What’s fueling the demand? In short, ex*****on. “Chief AI officers used to be more figureheads—AI evangelists promoting the technology,” said Jacob Dencik, Research Director at IBV. “Now they’re driving real transformation, helping organizations move from pilots to production.” Translation: fewer slide decks, more results.

Schneider Electric offers a telling early example. The company created its CAIO role back in 2021—long before generative AI became a boardroom obsession—and focused squarely on operational impact. As Philippe Rambach, the company’s Chief AI Officer puts it, AI should “start with a business need, not the technology.” Simple idea. Surprisingly rare in practice.

Still, not every company necessarily needs a standalone CAIO, CIO Strategic Advisor Tim Crawford told IBM Think. He compares this moment to the rise of chief digital officers a decade ago—some wins, plenty of confusion. His point: don’t fix AI fragmentation by adding another title. In some organizations, AI leadership can sit with the CIO or even the CEO—so long as accountability and coordination are clear.

That distinction—between coordination and control—is becoming the real story. Many AI leaders don’t actually “own” AI at all. They orchestrate it across teams, platforms and processes. At IBM, there’s no formal chief AI officer, yet many point to Joanne Wright, SVP of Transformation and Operations, as the functional equivalent. Her remit sits at the intersection of every operational domain at IBM, from procurement to data and analytics to CIO and more. As Wright put it in an interview with IBM Think, “I don’t ‘own’ AI. Each leader is accountable for adoption on their own teams, and my role is to accelerate that and remove friction.”

That accountability mindset matters. According to new research, companies that embed continuous visibility and governance into agentic systems from the start—rather than relying on policy documents and crossed fingers—achieve 20 percent higher ROI, alongside stronger gains in productivity and revenue.

The takeaway? As AI spreads everywhere, AI leadership isn’t about grabbing the baton. It’s about conducting the orchestra—and making sure everyone stays in tune.

28/04/2026

Siemens recently announced, effective August 1st, that Mesut Eken will take over as Chief Financial Officer (CFO) of Siemens USA. In this role, Eken will serve as the financial leader for Siemens' largest market globally, driving financial strategy, capital stewardship, and operational performance across the company's extensive U.S. footprint.

Eken is an experienced finance executive whose Siemens career spans nearly three decades of leadership within Siemens and the industrial sector. He joins the U.S. leadership team from his role as CFO of the Motion Control Business Unit within Siemens Digital Industries, where he oversaw financial operations. Before that, he spent several years within Siemens Corporate Finance Headquarters in Munich, leading both Shareholder Controlling and Internal Financial Disclosure — roles that gave him a holistic view of the company's financial positioning at the highest level.