Artificial Intelligence is coming, and like other technology trends, AI follows a hype curve. Where we are in the hype curve is debatable. Most experts and analysts suggest early on, in the growth phase. Regardless, interest in the technology and its potential is high. A recent study by consultants McKinsey found that 72% of businesses are investing in AI. A new AI is created or another type of job is at risk from the incoming AI revolution almost daily.
Aerospace is no exception. But asking ChatGPT to design you a plane isn’t going to work. Instead, AI companies are beginning to emerge, presenting bespoke Industrial AI solutions. These AIs are tailored to meet industry requirements in terms of accuracy, reliability, performance, security and capabilities.
AI TAKEOVER
Enterprise software company IFS (Industrial and Financial Systems) is expanding rapidly from its ERP roots and aims to become the leading global company for Industrial AI by the end of the decade, primarily financed by private equity investment. Over the last two years the company has been quietly acquiring smaller firms working on developing Industrial AI, such as asset management company Copperleaf and worker management company Poka. IFS is also a member of the All-Party Parliamentary Group in the UK on the application and impact of AI.
“IFS will be the undisputed world leader in Industrial AI by 2029,” proclaimed Mark Moffat, CEO of IFS at the company’s customer event in Birmingham UK in May.
Recent research commissioned by IFS, “Industrial AI: the new frontier for productivity, innovation and competition,” questioned 1,700 senior decision-makers across several industries. Half of the respondents were optimistic that with the right strategy for AI, value could be realized in the next two years, and a quarter believed in the next year.
Moffat believes Industrial AI represents as much an opportunity as a threat for aerospace businesses: “It can take process chains, assess where the blockages are, find the opportunities to save money and unlock value. But you have to lean into this to understand what AI can do for your business – in every part of your business.”
People are now familiar with natural language processing (NLP) AIs such as ChatGPT. These NLPs provide a front-end for users to interact with Industrial AI algorithms. Other types of AI can then be applied to industrial applications and data – generative, predictive, and agentic AI. It is mainly these three types of AI that currently form the basis of Industrial AI applications.
Once an Industrial AI application has been developed by IFS and a client, it is placed in a bank of applications alongside others, and can be accessed via IFS Cloud, the company’s core software platform. Unlike traditional siloed business systems, this “unified” cloud platform integrates multiple enterprise functions, such as ERP, EAM, FSM, and now Industrial AI, into a single accessible ecosystem.
There are already 200 Industrial AI applications, or “capabilities” as the company terms them in the IFS Cloud. These have been added since the launch of the IFS’ Industrial AI initiative last year. IFS Cloud is updated twice annually, in April and September, with new features and AI capabilities added each time.
VERTICAL MARKETS
Headquartered in Sweden, IFS works in a range of sectors, but its background is strongest in the oil and gas sector.
“We operate primarily in capital-heavy, asset and data-rich industries,” says Vijay Hadavale, director of aerospace and defense presales at IFS. “We have a business unit dedicated to aerospace and defense that serves both the commercial and defense sectors.”
IFS splits A&D into specific sub-verticals: airlines and operators, support providers, airport service organizations, A&D manufacturing, independent MRO facilities, defense contractors, and defense forces.
“Our value proposition centers around enabling control across the entire A&D value chain – build, operate, maintain and support,” Hadavale says. “Our architecture means customers can select and deploy the specific capabilities they need.”
The flexibility extends to different operational models, from project-based to discrete manufacturing, small component fabrication to major systems assembly. The platform also provides maintenance and engineering capabilities compliant with industry regulations such as Part M, CAMO, Part 145, Part 121, and ITAR requirements across air, land, sea, and space domains.
The solutions are designed to integrate with existing systems and meet the demands of airworthiness certification. “Our aviation capabilities cover all regulatory requirements – quality assurance, inspection protocols, certification processes, and airworthiness compliance,” Hadavale says. “We’ve embedded these essential functions within our software platform to comprehensively manage the maintenance lifecycle.”
AI can automate product workflows, including in testing departments
“Industrial AI goes beyond consumer chatbots to provide actionable insights” STEPHANIE POOR, MANAGING DIRECTOR OF UKI AND BENELUX, IFS
The integration of AI into established processes IFS already supplies represents a significant advance for industry, Hadavale claims. “AI is automating workflows and increasing productivity for technicians, engineers, and planners,” he says. “We’ve developed and released numerous use cases since last year, including maintenance scheduling optimization based on our Planning and Scheduling Optimization engine. These algorithms can be applied across manufacturing scheduling, maintenance and testing operations.”
Industrial AI agents are already being used in planning logistics and for optimizing manufacturing
This approach transforms testing from an isolated activity into a fully integrated component within workflows, allowing companies to manage test equipment, control plans, test parameters, and compliance documentation through a single platform, Hadavale explains.
SECURITY COMPLIANCE
Aerospace and defense companies face security challenges when adopting new technologies, including cloud-based AI solutions. According to Hadavale, these concerns have slowed adoption, despite the sector’s traditionally innovative nature.
“In the last decade, consumer industries have surpassed aerospace and defense in certain areas of digital transformation,” Hadavale explains. “A&D is highly protected and secure by necessity. Hesitancy toward cloud adoption stems from regulatory requirements, compliance mandates, and legitimate concerns about cybersecurity.
“In response we’re focusing on compliance, certifications, and regulations. In the US we’re working toward CMMC and FedRAMP certifications, while also addressing jurisdiction-specific requirements worldwide We already maintain ISO 27001, SOC 1, SOC 2, and GDPR compliance, with dedicated European services for data residency requirements.”
The extensive documentation requirements for aerospace testing and certification present significant opportunities for AI-driven efficiency gains. “AI brings automation to this ecosystem that increases productivity across the workflow,” Hadavale says.
AI IN TIME
With the increasingly perilous state of geopolitics, aerospace and defense firms are under pressure to scale up rapidly. Interest is growing in AI tools that can deliver the operational capacity improvements needed, while meeting compliance requirements. “Many defense contractors want to update and upgrade their technology to increase throughput. They are dealing with significant backlogs,” Hadavale says.
“They want to increase throughput – do more with the same workforce and facilities,” Hadavale emphasizes. These organizations can use AI to improve productivity by automating processes and making operations faster, more accurate, and more agile, while maintaining customer satisfaction through service level agreements.
Away from scheduling, Hadavale believes one of the most promising AI applications for aerospace is knowledge transfer. This is particularly critical for an industry facing talent challenges.
“The aging workforce and talent acquisition difficulties represent major challenges for the aerospace sector,” Hadavale says.
“With AI and co-pilot technologies, legacy knowledge becomes immediately accessible through context-aware conversational interfaces.”
This capability could dramatically transform the onboarding process for new technical personnel. “You can bring new talent up to speed much faster,” says Hadavale. “These systems can effectively capture and transfer the specialized knowledge of experienced engineers.”
The knowledge transfer mechanism will extend beyond simple documentation, into applications that use augmented reality, remote assistance, and contextualized information delivery systems to preserve critical expertise even when veteran staff depart. The approach could help aerospace companies ensure technical continuity even when specialized expertise leaves the organization.
“The systems capture the knowledge of engineers” VIJAY HADAVALE, DIRECTOR OF AEROSPACE AND DEFENSE PRESALES, IFS
HALLUCINATIONS
However, the specter rising above AI, especially for industrial applications, is hallucinations, where AIs invents false data. Industry requires analyses and assessments that must be precise. The risks and consequences of failure are higher in mission-critical sectors where lives are at stake, such as aerospace.
Moffat agrees on this critical nature: “We know you can’t get this stuff wrong,” he says. “Planes can fall out of the sky. It’s mission-critical, which is one of the reasons why we are focusing on Industrial AI as different from the generic, large language models.”
Moffat believes a careful approach is needed when deploying Industrial AI in aerospace. And while agentic AIs could be applied within aerospace workflows, he does not see them as making decisions that affect operations for a long time. For example, if an AI summarizes a critical report, he is clear on the limitations. “I think in mission-critical, high-stakes operations, it will be a while before we get a genuine, automated agent. You will still need to put a physical signature on documents,” he says.
While the need for human verification in critical systems isn’t changing anytime soon, the capability of Industrial AI is growing rapidly. Like many sectors and jobs, those who turn their backs to this new technology could risk being left behind.
AI can enable insights into test and inspection data that lead to process efficiency improvements
WHAT IS INDUSTRIAL AI?
Industrial AI is artificial intelligence built specifically for industrial applications.
Unlike general AI, which focuses on mimicking human intelligence, industrial AI is tailored for automating and optimizing complex industrial processes. It leverages data from sensors, machines, and networks to improve decision-making, enhance productivity, and drive innovation.
Stephanie Poor, managing director of UKI and Benelux, IFS says, “Industrial AI goes beyond consumer chatbots. It provides actionable insights and harnesses data effectively to boost productivity.”
IFS is not the only industrial software company adding AI functionality to its products. Companies from design software firms like Dassault and Autodesk, to manufacturing suppliers like Rockwell and Siemens have AI-powered enhancements in their products. But so far, the only company to try and redefine its entire product portfolio using AI is IFS.
DIFFERENT TYPES OF AI
There are many different types of AI, with new types being developed at pace. For business and industry on a general level AI can be split into three different categories – predictive, generative and agentic.
Predictive AI uses historical data to forecast future events or trends to help with decision-making and strategic planning. An example could be forecasting customer demand or predicting product failure.
Generative AI creates new content, such as text, images, videos, code or designs. It can be used to replicate human creativity and innovation. Examples include generating marketing copy, creating new engineering designs or composing music.
Agentic AI are autonomous systems that can analyze, plan and act independently. The AI agents can be used to make decisions, execute tasks, and adapt to changing situations. Example include software co-pilots, robotic assistants, self-driving cars, or autonomous logistics systems.
Palantir, a leading artificial intelligence (AI) software company, is emerging as a major U.S. stock favored by Koreans. [Photo source = Yonhap News]
Palantir, a leading artificial intelligence (AI) software company, is emerging as a major U.S. stock favored by Koreans.
According to the Korea Securities Depository on the 13th, the value of Palantir shares (storage) held by domestic investors reached $5.85 billion (8.1329 trillion won) as of the 10th, making it the third-largest foreign stock after Tesla and Nvidia.
At the beginning of this year, Palantir ranked eighth in storage, but it jumped five spots in just nine months. Storage increased by about 2.5 times from $2.3 billion.
Palantir is a company that sells advanced AI services to the military, government, companies, and intelligence agencies. The main goal is to help AI analyze vast and diverse data within the organization to find specific patterns and predict the future to make wise decisions.
In Korea, companies such as HD Hyundai Infracore and Samyang Foods use Palantir systems.
Palantir signed a contract with the U.S. Army last month worth up to $10 billion (W13.8 trillion) over the next decade, making it one of the largest Pentagon software contracts in U.S. history.
Palantir’s stock price more than doubled from 75.63 dollars (105,000 won) at the end of last year to 164 dollars (227,000 won) as of the 12th.
In the second quarter of this year, it exceeded $1 billion in sales for the first time ever and posted a net profit of $0.16 per share.
Big tech is expected to spend nearly $500 billion on artificial intelligence infrastructure next year.
Over the past few years, many corporate budgets have been reoriented toward artificial intelligence (AI) investments. Nowhere is this shift more evident than among the cloud hyperscalers — Microsoft, Alphabet, and Amazon — as well as other tech titans like Meta Platforms and Oracle.
At the center of this unprecedented wave of AI infrastructure spending stands one clear beneficiary: Nvidia(NVDA 0.43%). Whether directly or indirectly, the graphics processing unit (GPU) powerhouse is capturing a significant chunk of the money being spent on AI infrastructure.
Let’s explore how big tech is reshaping the AI landscape — and why these secular tailwinds point to further significant upside for Nvidia.
AI infrastructure spending has accelerated since the launch of ChatGPT
The launch of ChatGPT in November 2022 ignited an unprecedented AI arms race among the world’s largest companies. What’s important to recognize is that their capital expenditures in this battle are not plateauing — they’re accelerating.
Data from Goldman Sachs underscores just how dramatic these dynamics have become. In 2021, Alphabet, Meta, Amazon, and Microsoft collectively had capex of about $100 billion. By next year, Wall Street expects that figure to approach nearly $500 billion.
What does this mean for Nvidia?
Training and deploying large language models (LLMs) and building generative AI applications demands extraordinary amounts of computing power. GPUs are parallel processors, which makes them some of the best chips available to provide the type of computing power AI workloads require. Today, Nvidia commands a more than 90% share of the GPU market, giving it a dominant position within the AI supply chain.
A significant portion of the AI capex surge is flowing directly into GPUs and the supporting data center equipment necessary to maximize their performance.
This dynamic places Nvidia in a uniquely enviable position as the backbone of modern AI development — and it’s poised to capture incremental budget allocations as hyperscalers and other data center operators race to secure its next-generation chips the moment they become available.
Image source: Getty Images.
Is Nvidia stock a buy?
The magnitude of hyperscaler infrastructure investment reflects more than the world’s apparently insatiable appetite for AI computing power. It underscores a deeper reality: AI is becoming the central growth engine for these companies, and securing access to the most advanced chips has shifted from being a matter of technological advantage to being a matter of competitive survival.
The accelerating pace of this spending suggests that corporations are still in the early stages of implementing their AI playbooks. Far from being a speculative bubble, this wave of infrastructure investment is the result of deliberate, long-term strategic planning by some of the world’s most influential companies as they pivot away from their traditional priorities and take on sophisticated projects in robotics, autonomous systems, cybersecurity, and more.
For Nvidia, this dynamic should translate into sustained pricing power for its wares, durable recurring demand, and a multiyear runway for rapid growth. Its GPUs and CUDA software platform have become the gold standard for enterprise AI tech stacks.
Taken together, these tailwinds suggest that Nvidia could experience meaningful valuation expansion from here. As the infrastructure chapter of the AI narrative continues to unfold, Nvidia appears well positioned to remain as a core enabler of big tech’s transformation.
For these reasons, I see Nvidia stock as a no-brainer investment, and view it as one of the most compelling buy-and-hold opportunities in the market.
Adam Spatacco has positions in Alphabet, Amazon, Meta Platforms, Microsoft, and Nvidia. The Motley Fool has positions in and recommends Alphabet, Amazon, Goldman Sachs Group, Meta Platforms, Microsoft, Nvidia, and Oracle. The Motley Fool recommends Nebius Group and recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy.
north of Fargo, readers have asked several questions about the facility.
The Forum spoke this week with Applied Digital Chairman and CEO Wes Cummins about the 280-megawatt facility planned for east of Interstate 29 between Harwood, North Dakota, and Fargo. The 160-acre center will sit on 925 acres near the Fargo Park District’s North Softball Complex.
The Harwood City Council voted unanimously on Wednesday, Sept. 10, to rezone the land for the center from agricultural to light industrial. With the vote also came final approval of the building permit for the center, meaning Applied Digital can break ground on the facility this month.
“We’re grateful for the City of Harwood’s support and look forward to continuing a strong partnership with the community as this project moves ahead,” Cummins said after the vote.
Applied Digital CEO and Chairman Wes Cummins talks about his company and its plans for Harwood, North Dakota, during a meeting on Tuesday, Sept. 2, 2025, at the Harwood Community Center.
Alyssa Goelzer / The Forum
Applied Digital plans to start construction this month and open partially by the end of 2026. The facility should be fully operational by early 2027, the company said.
The project should create 700 construction jobs while the facility is built, Applied Digital said. The center will need more than 200 full-time employees to operate, the company said. The facility is expected to generate tax revenue and economic growth for the area, but those estimates have not been disclosed.
Here are some questions readers had about the facility.
What will the AI data center be used for?
Applied Digital said it develops facilities that provide “high-performance data centers and colocations solutions for artificial intelligence, cloud, networking, and blockchain industries.” AI is used to run applications that make computers functional, Cummins said.
“ChatGPT runs in a facility like this,” he said. “There’s just enormous amounts of servers that can run GPUs (graphic processing units) inside of the facility and can either be doing training, which is making the product, or inference, which is what happens when people use the product.”
Applied Digital’s $3 billion data center will be constructed just southeast of the town of Harwood, North Dakota.
Map by The Forum
Applied Digital hasn’t announced what tenants would use Polaris Forge 2, the name for the Harwood facility. At a Harwood City Council meeting, Cummins said the company markets to companies in the U.S. like Google, Meta, Amazon and Microsoft.
“The demand for AI capacity continues to accelerate, and North Dakota continues to be one of the most strategic locations in the country to meet that need,” he said. “We have strong interest from multiple parties and are in advanced negotiations with a U.S. based investment-grade hyperscaler for this campus, making it both timely and prudent to proceed with groundbreaking and site development.”
AI data centers need significant amounts of electricity to operate, Cummins said. Other centers have traditionally been built near heavily populated areas, but that isn’t necessary, he said.
North Dakota produces enough energy to export it out of state, Cummins said. The Fargo area also has the electrical grid in place to connect to that energy, he said.
“A lot of North Dakotans, especially the leaders of North Dakota, want to better utilize the energy produced by North Dakota for economic benefit inside of the state versus exporting it to neighboring states or to Canada,” he said.
North Dakota’s cold climate much of the year also will keep the center cooler than in states like Texas, meaning the facility will use significantly less power than in warmer states, Cummins said.
“We get much more efficiency out of the facility,” he said. “Those aspects make North Dakota, in my opinion, an ideal place for this type of AI infrastructure.”
The Harwood, North Dakota, elevator on Thursday, Aug. 28, 2025, looms behind the land designated for the construction of Applied Digital’s 280-megawatt data center.
David Samson / The Forum
How much water will the center use?
Cummins acknowledged other AI data centers around the world use millions of gallons of water a day. Applied Digital designed a closed-loop system so the North Dakota centers use as little water as possible, Cummins said.
He compared the cooling system to a car radiator. The centers will use glycol liquid to run through the facilities and servers, Cummins said. After cooling the equipment, the liquid goes through chillers, much like a heat pump outside of a house. Once cooled, the liquid will recirculate on a continuous loop, he said.
People who operate the facility will use water for bathroom breaks and drinking, much like a person in a house or a car, he said.
“The data center, even with the immense size, we expect it to use the same amount of water as roughly a single household,” he said. “The reason is the people inside.”
Duncan Alexander and dog Valka protest a proposed AI data center before a Planning and Zoning meeting on Tuesday, Sept. 2, 2025, in Harwood, North Dakota.
Alyssa Goelzer / The Forum
Will the AI center increase electricity rates?
Applied Digital claims that electricity rates will not go up for local residents because of the data center.
“Data centers pay a large share of fixed utility costs, which helps spread expenses across more users,” the company said.
Applied Digital’s center in Ellendale, North Dakota, much like the one to be built in Harwood, uses power produced in the state, Cummins said. The Ellendale center, which runs on about 200 megawatts a year, saved ratepayers $5.3 million in 2023 and $5.7 million last year, he said.
“Utilizing the infrastructure more efficiently can actually drive rates down,” Cummins said, adding he expects rate savings for Harwood as well.
How much noise will the center make?
Applied Digital’s concrete walls should content the noise from computers, Cummins said. What residents will hear is fan noise from heat pumps used to cool the facility, he said.
“It will sound like the one that runs outside of your house,” he said in describing that the facility will create minimal noise.
The loudest noise will be construction of the facility, Cummins said.
The facility only will cover 160 acres, but Applied Digital is buying 925 acres of land, with the rest of the space serving as a sound buffer, he said. People who live nearby may hear some sound, he acknowledged.
“If you’re a half mile or more from the facility, you will very unlikely hear anything,” he said.
About 300 people showed up to a town hall meeting on Monday, Aug. 25, 2025, at the Harwood Community Center to listen and to discuss a new AI data center that is planned to be built in Harwood, North Dakota.
Chris Flynn / The Forum
Has Applied Digital conducted an environmental study?
The facility won’t create emissions or other hazards that would require an environmental impact study, Cummins said.
Why move so fast to approve the facility?
Some have criticized Applied Digital and the Harwood City Council for pushing the approval process so quickly. Applied Digital announced the project in mid-August, and the city approved it in less than a month.
Cummins acknowledged that concern but noted the industry is moving fast. The U.S. is competing with China to create artificial intelligence, an industry that is not going away, Cummins said.
“I do believe we are in a race in the world for super intelligence,” he said. “It’s a race amongst companies in the U.S., but it’s also a race against other countries. … I do think it’s very important the U.S. win this AI race to super intelligence and then to artificial general intelligence.”
Applied Digital said it wanted to finish foundation and grading work on the project before winter sets in, meaning it needed an expedited approval timeline.
People in Harwood have shown overwhelming support, Cummins said, adding that protesters mostly came from other cities.
“I can’t think of a project that would spend this amount of money and have this kind of economic benefit for a community and a county and a state and have this low of a negative impact,” he said. “I think these types of projects are fantastic for these types of communities.”
