by Gary Mintchell | Jan 12, 2026 | Automation, Data Management, Generative AI, Manufacturing IT, Software, Technology
Siemens seems to have found a home at CES over the past few years. I don’t know what it costs to give a keynote, but it’s probably well worth it, since no other major automation supplier seems to attend. I did write about a robotic exhibitor in my last post. Oh, and I’m still not likely to travel to Las Vegas for the next CES. I’ll save a ton of money and grief by receiving the news at home.
Siemens has maintained strong collaboration with Microsoft for decades—see all the Copilot news below. Recently, NVIDIA has joined the collaboration dance. Also, see news below. I think Siemens thought they’d gain penetration into the North American market through Chrysler’s acquisition by a German company plus the plants constructed by VW and BMW. That market is not so hot—see the proportion of sales into automotive by competitor Rockwell Automation, for example. Check out the customers featured by Siemens at CES this year: PepsiCo, Commonwealth Fusion Systems, Meta Ray-Ban, and Haddy.
Perhaps the best acquisition, and most successful, that Siemens ever made was with UGS years ago. While rivals have struggled with software (and competitors have nibbled at some of the Siemens applications), Siemens continues to strengthen Xcelerator and Copilot technologies. And check out the launch of Digital Twin Composer. Digital Twin technology and application seems to be finally gaining traction.
In short, Siemens announcements:
- Siemens and NVIDIA expand their partnership to build the Industrial AI Operating System, reinventing the entire end-to-end industrial value chain through AI – from design and engineering to manufacturing, production, operations, and into supply chains.
- Siemens launches Digital Twin Composer software, available on Siemens Xcelerator Marketplace mid-2026, to power the industrial metaverse at scale
- PepsiCo using Siemens Digital Twin Composer to simulate upgrades to its facilities in the U.S. with plans to scale globally
- Siemens unveils nine industrial copilots to bring intelligence across the industrial value chain
- Siemens highlights new technologies for accelerating drug discovery, autonomous driving and shop floor efficiency
“Industrial AI is no longer a feature; it’s a force that will reshape the next century. Siemens is delivering AI-native capabilities, intelligence embedded end-to-end across design, engineering and operations, to help our customers anticipate issues, accelerate innovation and reduce cost,” said Roland Busch, President and CEO of Siemens AG.
“Just as electricity once revolutionized the world, industry is shifting toward elements where AI powers products, factories, buildings, grids and transportation. Industrial AI is no longer a feature; it’s a force that will reshape the next century. Siemens is delivering AI-native capabilities, intelligence embedded end-to-end across design, engineering and operations, to help our customers anticipate issues, accelerate innovation and reduce cost,” continued Busch. “From the most comprehensive digital twin and AI-powered hardware to copilots on the shop floor, we’re scaling intelligence across the physical world, so businesses realize speed, quality and efficiency all at once. This is how we scale a once-in-a-generation technology shift into measurable outcomes.”
Siemens and NVIDIA are expanding their partnership to build the Industrial AI Operating System – helping customers revolutionize how they design, engineer, and operate physical systems. They will work together to build AI-accelerated industrial solutions across the full lifecycle of products and production, enabling faster innovation, continuous optimization, and more resilient, sustainable manufacturing. The companies also aim to build the world’s first fully AI-driven, adaptive manufacturing sites globally, starting in 2026 with the Siemens Electronics Factory in Erlangen, Germany, as the first blueprint.
To support development, NVIDIA will provide AI infrastructure, simulation libraries, models, frameworks and blueprints, while Siemens will commit hundreds of industrial AI experts and leading hardware and software. The companies have identified impact areas to make this vision a reality: AI-native EDA, AI-native Simulation, AI-driven adaptive manufacturing and supply chain, and AI-factories.
Integration with Siemens software.
Siemens also announced that it will be integrating NVIDIA NIM and NVIDIA Nemotron open AI models into its electronic design automation (EDA) software offerings to advance generative and agentic workflows for semiconductor and PCB design. This will both maximize accuracy through domain specialization and significantly lower operational costs by enabling the most efficient model to handle and adapt to every specific need.
Product Launch
Siemens’ primary product launch at CES 2026 is the Digital Twin Composer, available on the Siemens Xcelerator Marketplace mid-2026. This new technology brings together Siemens’ comprehensive digital twin, simulations built using NVIDIA Omniverse libraries, and real-time, real-world engineering data.
With the Digital Twin Composer, companies can create a virtual 3D model of any product, process, or plant; put it in a 3D scene of their choosing; then move back and forth through time, precisely visualizing the effects of everything from weather changes to engineering changes. With Siemens’ software as the data backbone, the Digital Twin Composer builds Industrial Metaverse environments at scale, empowering organizations to apply industrial AI, simulation and real-time physical data to make decisions virtually, at speed and scale. Digital Twin Composer is part of Siemens Xcelerator, an industry proven portfolio of software used by companies worldwide to develop digital twins.
Customer application of digital twins
PepsiCo and Siemens are digitally transforming select U.S. manufacturing and warehouse facilities by converting them into high-fidelity 3D digital twins that simulate plant operations and the end-to-end supply chain to establish a performance baseline. Within weeks, teams optimized and validated new configurations to boost capacity and throughput, giving PepsiCo a unified, real-time view of operations with flexibility to integrate AI-driven capabilities over time.
Leveraging Siemens’ Digital Twin Composer, NVIDIA Omniverse libraries and computer vision, PepsiCo can now recreate every machine, conveyor, pallet route and operator path with physics-level accuracy, enabling AI agents to simulate, test, and refine system changes – identifying up to 90 percent of potential issues before any physical modifications occur. This approach has already delivered a 20 percent increase in throughput on initial deployment and is driving faster design cycles, nearly 100 percent design validation and 10 to 15 percent reductions in capital expenditure (Capex) by uncovering hidden capacity and validating investments in a virtual environment.
New Industrial Copilots Streamline Manufacturing Operations
Siemens also spotlighted its partnership with Microsoft highlighting co-building the industrial copilot.
Siemens also announced that it is expanding its set of AI-powered copilots across the industrial value chain. This will embed intelligence that extends from design and simulation to product lifecycle management, manufacturing, and operations.
Siemens will deploy nine new AI-powered copilots for its software offerings, this will include Teamcenter, Polarion, and Opcenter. These copilots, respectively, streamline product data navigation, reducing errors and accelerating time to market; automate compliance, helping to ensure faster regulatory approvals and lower risk; and transform manufacturing processes, driving cost savings and operational efficiency.
These copilots, along with the rest of Siemens’ expanding portfolio of industrial AI solutions, are available to companies of every size on the Siemens Xcelerator Marketplace.
AI-Driven Innovations in Life Sciences, Energy and Manufacturing
- Siemens acquired Dotmatics whose Luma platform enables scientists to unify billions of data points generated across instruments and labs, creating a coherent foundation for AI-driven exploration. Combined with Siemens Simcenter simulation and digital twins, teams can rapidly test molecules, identify promising candidates, and virtually scale production to help life-changing therapies reach patients up to 50% faster and at a lower cost.
- Bob Mumgaard, CEO and co-founder of Commonwealth Fusion Systems, described how the company uses Siemens’ technologies as it leads the path to commercial fusion. Commonwealth Fusion Systems uses design software and a strong data backbone to help it accelerate the development of fusion machines that promise clean, limitless energy for generations to come.
- In manufacturing, Siemens announced a collaboration to bring Industrial AI to Meta Ray-Ban AI Glasses. With hands-free, real-time audio guidance, safety insights, and feedback, shop floor workers will feel empowered to solve problems efficiently and confidently.
- Haddy is reshaping manufacturing through AI-powered 3D printing and localized micro factories that deliver sustainable, high-quality products faster and closer to customers. Facing challenges around supply chain disruption, sustainability, and production agility, Haddy partnered with Siemens to streamline design, optimize operations, and scale efficiently.
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by Gary Mintchell | Dec 23, 2025 | Business, Generative AI, News, Technology
I wonder how many technology firms with headquarters in the US consider themselves American and how many think (thought?) they are global.
Before MAGA, these were global companies by my observation. Suddenly it dawned on many that there is actually another country vs country competition striving for first place.
Now, everyone not technical, and some who are, is panicking about AI. There are many unknowns and much hype. The current administration sees the competition looking to put some financial and public muscle behind further developments in AI—especially using AI to benefit scientific research and manufacturing.
I am currently digesting the Genesis Mission under the Dept. of Energy announced last week. Today’s news concerns AI both for manufacturing and cybersecurity for critical infrastructure from the Dept of Commerce’s National Institute of Standards and Technology (NIST).
The U.S. Department of Commerce’s National Institute of Standards and Technology (NIST) has expanded its collaboration with the nonprofit MITRE Corporation as part of its efforts to ensure U.S. leadership in artificial intelligence (AI). Through this award, NIST is investing $20 million to establish two centers to advance the delivery of AI-based technology solutions to strengthen U.S. manufacturing and cybersecurity for critical infrastructure.
“This investment will help accelerate the application of AI in American manufacturing and help drive the American manufacturing renaissance,” said Deputy Secretary of Commerce Paul Dabbar. “We can harness AI to increase the competitiveness of our manufacturers and attract investment in America.”
The award is an important step in implementing NIST’s Strategy for American Technology Leadership in the 21st Century to accelerate the progress of critical and emerging technologies from development to adoption, in close partnership with U.S. industry.
“Our goal is to remove barriers to American AI innovation and accelerate the application of our AI technologies around the world,” said Acting Under Secretary of Commerce for Standards and Technology and Acting NIST Director Craig Burkhardt. “This new agreement with MITRE will focus on enhancing the ability of U.S. companies to make high-value products more efficiently, meet market demands domestically and internationally, and catalyze discovery and commercialization of new technologies and devices.”
The AI Economic Security Center for U.S. Manufacturing Productivity and the AI Economic Security Center to Secure U.S. Critical Infrastructure from Cyberthreats will drive the development and adoption of AI-driven tools, or “agents,” in these two national priority areas. The centers will develop the technology evaluations and advancements that are necessary to effectively protect U.S. dominance in AI innovation, address threats from adversaries’ use of AI, and reduce risks from reliance on insecure AI.
NIST will rely on existing resources to build on its expertise and carry forward recommendations in the White House’s July 2025 America’s AI Action Plan, including Pillar I: Accelerate AI Innovation and Pillar II: Build American AI Infrastructure.
These are important first steps in NIST’s programmatic plan to coordinate innovation-based research efforts for accelerating the development and deployment of critical technologies in areas of national priority. Building on its long history of public-private collaboration, NIST plans to use adaptive and flexible partnerships to develop, pilot and implement new advances to establish U.S. leadership and innovation in critical and emerging technologies such as AI, quantum information science and technology, and biotechnology.
The partnership will leverage MITRE’s long-standing mission to operate federally funded research and development centers. NIST expects the AI centers to enable breakthroughs in applied science and advanced technology and deliver disruptive innovative solutions to tackle the most pressing challenges facing the nation.
This agreement expands NIST’s portfolio of AI-focused programs and builds on the private-public partnerships leveraged by the Center for AI Standards and Innovation (CAISI), which leads evaluations of U.S. and adversary systems and contributes to NIST’s efforts to develop best practices. CAISI has established voluntary agreements with multiple developers of leading-edge or “frontier” AI models to enable collaborative research and voluntary testing of industry models for priority national security capabilities.
In the coming months, NIST plans to announce its award for the AI for Resilient Manufacturing Institute, through the Manufacturing USA program. With up to $70 million in investment over a five-year period from NIST and at least that much in nonfederal funding, the institute will bring together expertise in AI, manufacturing and supply chain networks to promote manufacturing resilience.
Combined, these efforts will enhance NIST’s core research, standards and technology mission to tackle barriers preventing U.S. innovation and leadership in AI.
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by Gary Mintchell | Dec 2, 2025 | Data Management, Enterprise IT, Generative AI, Internet of Things, Operations Management
User studies remain one of the primary ways software companies can gain insight and achieve some public recognition. Most of the studies emanate from cybersecurity protection developers. This one comes from a software company with which I’ve had little contact. There was a woman I knew from one company who came to SAS for a while. We had occasional conversations before she left that company.
SAS develops software applications. I’ve never had a handle on its business. It now bills itself as a global leader in data and AI. This study was conducted by the research firm IDC. And we have the acronym AIoT—or the convergence of AI and IoT. Somehow I feel that concatenating acronyms is the beginning of the end times 😉
Key findings from the IDC InfoBrief, How AIoT Is Reshaping Industrial Efficiency, Security, and Decision-Making, sponsored by SAS, include:
This one should surprise no one. Everyone discusses predictive maintenance.
Predictive maintenance dominates current AIoT use. Nearly 71% of organizations use AIoT for predictive maintenance, the most widely adopted use for manufacturing/industrial and energy companies surveyed. IT automation (53%) and supply and logistics (47%) were the next most cited uses for AIoT.
Executives continue to dream of significant cost reductions from AI.
AIoT drives tangible business value. 54% of respondents anticipate major cost savings, 52% predict smarter and faster innovation and 49% expect streamlined operations from their investment in AIoT. Additionally, 63% believe AIoT will boost productivity and competitiveness.
Managers continue to see AI as an aid to overcome the current skills gap of employees.
Skills gap emerges as the top challenge. The skills gap is the biggest barrier to AIoT success, outpacing legacy system integration and data quality issues as the most significant roadblock. Other challenges include high implementation costs, business process misalignment and cultural resistance. Addressing these issues is essential to unlocking AIoT’s full potential.
Some actually use the technology!
Heavy AIoT users see greater value. Organizations using AIoT heavily are twice as likely to report benefits that significantly exceed expectations as those that only use the technology sparingly. Strikingly, less than 3% say the value of AIoT “did not meet expectations.”
The IDC research is based on a global survey of more than 300 industrial executives in the manufacturing and energy industries.
And from the company:
SAS IoT solutions combine AI, machine learning and edge-to-cloud integration, enabling analysis of high-volume, high-velocity data. And joining AI with these IoT solutions extends the value of existing infrastructure investments and digitally transforms the workforce by shifting from manual oversight to intelligent orchestration.
Other organizations benefiting from SAS IoT and streaming analytics for improved asset reliability, enhanced product quality and increased efficiency across connected systems include:
- Georgia-Pacific
- Jakarta Smart City
- Lloyd’s List
- Lockheed Martin
- Town of Cary (North Carolina)
- Volvo Trucks and Mack Trucks
- wienerberger
by Gary Mintchell | Nov 20, 2025 | Generative AI, Operator Interface, Process Control
Every day brings more press releases about AI in something. Every one consistently uses the term AI completely undefined. I asked Honeywell if they could explain anything further about their AI. I waited a week. No reply.
Suffice it to say that some sort of AI “transforms” the experience for operators. So, forgetting the AI part, I continue to applaud refining ways to communicate the status of operations to operators (and others).
Honeywell announced a collaboration with TotalEnergies for the ongoing pilot of its AI-assisted Experion Operations Assistant at TotalEnergies’ Port Arthur Refinery in Texas. The initiative aims to support and empower operators to make timely and informed decisions while also providing the opportunity to enhance operational autonomy.
Built on Honeywell’s flagship distributed control system, Experion Operations Assistant is an advanced AI-powered solution designed to transform the way operators monitor plant operations from the control room. By merging operational analytics with real real-time predictive insights, the solution facilitates a more efficient workflow within critical refinery operations. With the integration of this new solution, operators in the control room can forecast potential maintenance events before they happen and minimize risks associated with unsafe operations and production losses.
TotalEnergies has already implemented an initial pilot of Experion Operations Assistant at the Port Arthur site’s Delayed Coking Unit (DCU). Preliminary results show the AI-assisted solution has successfully forecasted five potential events, helping to minimize downtime and reduce emissions from flaring. The predictions were made an average of 12 minutes in advance of an alarm incident, enabling operators to quickly implement corrective actions before an event.
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by Gary Mintchell | Nov 3, 2025 | Commentary, Generative AI, News
The IEEE released “The Impact of Technology in 2026 and Beyond: an IEEE Global Study” surveyed 400 CIOs, CTOs, IT directors, and other technology leaders in Brazil, China, Japan, India, the U.K. and U.S. at organizations with more than 1,000 employees across multiple industry sectors including banking and financial services, consumer goods, education, electronics, engineering, energy, government, healthcare, insurance, retail, and telecommunications. The survey was conducted September 11-17, 2025.
I find surveys interesting for an understanding of current sentiment among people who may be involved in the area but seldom have time to think through the questions. As a former product development professional, I’d never use these for developing new products. You need to be a little ahead of this curve.
Still, consider these as opinions coming from a background of much media hype about AI and Agents.
In general, the survey found these opinions:
- Widespread Use of Agentic AI as a ‘Smart Assistant’ for Everyday Tasks Such as Personal Shopper, Scheduler, Data Privacy Manager and Health Monitor Expected; Agentic AI Growth Will Also Spur a Data Analyst Hiring Boom
- Annual trends study forecasts robotics, extended reality, autonomous vehicles, quantum computing and renewable energy as technology areas AI will influence the most in 2026
Be wary of adjectives and adverbs injected into survey releases. Phrases such as “lightning speed” should be sent through the BS filter of your mind. Developments have seemed fast over the past few years. They also seem to have stalled.
Agentic AI is like a smart assistant that, when given a task, can work independently, but still needs its work double-checked. Its adoption is on the rise, and a strong majority of technologists globally (96%) agree that agentic AI innovation, exploration and adoption will continue at lightning speed in 2026, as both established enterprises and start-ups deepen investments and commitments to the technology.
Following are a lot of percentages. I’d advise skimming rather than getting lost in the minutiae.
The rise of agentic AI won’t be confined to business. Survey respondents see it reaching mass or near-mass adoption by consumers in 2026 for the following uses:
- (52%) Personal assistant | scheduler | family calendar manager
- (45%) Data privacy manager
- (41%) Health monitor
- (41%) Errand and chore automator (e.g. grocery orders)
- (36%) News and information curator
In addition, 91% agree the use of agentic AI to analyze greater amounts of data will grow in 2026, spurring a data analyst hiring boom to analyze the accuracy of results, transparency and vulnerabilities.
An interesting list of anticipated top skills for employees follows. Looks as if they have little to do specifically with AI (save one).
According to the survey, the top skills technologists will seek in candidates they plan to hire for AI-related roles in 2026 are:
- (44%) AI ethical practices skills (+9% from prior year)
- (38%) Data analysis skills (+4% from prior year)
- (34%) Machine learning skills (+6% from prior year)
- (32%) Data modeling skills, including processing (no change from prior year)
- (32%) Software development skills (-8% from prior year)
An interesting list of applications. Why was extended reality cited? That seems a long way off, if ever happening. Autonomous vehicles do keep improving.
A majority (77%) of technologists agree the novelty of humanoid robots can inject fun into the workplace but over time will become like commonplace co-workers with circuits. Robotics is also a top area of technology over half (52%) of technologists think will be influenced by AI in 2026. Other areas influenced by AI in 2026 will include extended reality (XR), including augmented, virtual and mixed reality (36%); and autonomous vehicles (35%).
I don’t see manufacturing/industrial applications hitting the top list.
Meanwhile, the top industries expected to experience the greatest transformation from AI next year will be software (52%); banking and financial services (42%); healthcare (37%) and automotive and transportation (32%).
Will they use it?
- (39%) Using Regularly, But Selectively: Generative AI will continue to be a regular part of our work in selective areas, and adds value. (+20% from prior year)
- (35%) Rapidly Integrating, Expecting Bottom Line Results: AI will continue to be integrated throughout all our operations. We’ve already seen measurable bottom line results and expect these to grow.
The top uses for AI applications technology leaders expect in 2026 includes:
- (47%) Real-time cybersecurity vulnerability identification and attack prevention (-1% from prior year)
- (39%) Aiding and/or accelerating software development (+4% from prior year)
- (35%) Increasing supply chain and warehouse automation efficiencies (+2% from prior year)
- (32%) Automating customer service (+4% from prior year)
- (29%) Powering educational activities such as customizing learning, intelligent tutoring systems, university chatbots (-10% from prior year)
- (23%) Accelerating disease mapping and drug discovery (-3% from prior year)
- (22%) Automating and/or stabilizing utility power sources (-3% from prior year)
Will you be using AI—really?
More than half of those surveyed (51%) cited 26-50% of jobs across the global economy will be augmented by AI software in 2026, while less than one-third (30%) cited 51-75% of jobs, (16%) cited 1-25% of jobs, and only (4%) cited 76-100% of jobs.
I’m thinking we may be reaching peak capital investment—mostly for economic reason, not technical. But many people ride the wave.
Close to half of technologists (49%) think it will take 5-7 years to build out the global data center infrastructure required to meet growing AI development and demand. One-third think it will happen sooner, in 3-4 years, while 10% think it will not happen for 8-10 years or more.
by Gary Mintchell | Oct 22, 2025 | Generative AI
Only a month ago I wrote about how every news release included “AI” no matter how mundane or useful it was. Suddenly the new phrase is “Agentic AI”. Agents are pieces of code that build on data generated by Large Language Models (LLMs) which are the current iteration of AI. Agents consider the data and context in order to make decisions.
These can be useful. However, we do know that the data generated from LLMs are not always useful or accurate or repeatable. The technology is good, but it also needs much growth to become a reliable tool in the worker’s kit.
This news comes from the ServiceMax division of PTC. Looks like the first usable implementations will help service workers. Since I’m writing this in the customer area of the car dealer’s service center, this is top of mind today.
In brief:
- Agentic AI advancements in ServiceMax AI accelerate work order execution and enable improvements in first-time fix rates
- Agentic AI advancements in Servigistics expand AI-driven intelligence for service parts planning
From the news:
PTC announced the availability of new service lifecycle management (SLM) AI offerings in its ServiceMax field service management solution and Servigistics service supply chain optimization solution. Agentic AI advancements in ServiceMax AI strengthen multi-agent action to support field service management outcomes, including faster work order execution and smarter parts queries. Servigistics AI advancements deliver additional agentic intelligence to the service supply chain, enabling autonomous orchestration of [service] planning and execution.
The latest ServiceMax AI enhancements build on the unique ability to take advantage of AI directly from the current processes already managed by ServiceMax. This latest release enhances AI Actions with orchestrated multi-agent execution, AI-driven process automation through Service Flow Manager, and a new Knowledge API that connects to documents across enterprise systems.
Servigistics is also introducing a new AI Assistant, which supports planners by improving forecast accuracy and accelerating planning cycles, and will be generally available in October 2025.
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