Innovative companies are igniting strong growth in the global market for AI in manufacturing
By Mark Shortt
Whether they’re analyzing sensor data to predict potential equipment failures before they occur, or using AI-driven robots to perform complex, ergonomically challenging surface finishing tasks, manufacturers are increasingly adopting artificial intelligence (AI) technologies to achieve new levels of performance throughout their operations.
By implementing AI technologies, manufacturing companies are finding they can streamline production workflows, enhance real-time decision making, and improve predictive maintenance across diverse manufacturing operations. They can also optimize production scheduling and quality control.
As awareness of these benefits continues to rise, the global market for AI in manufacturing is poised to more than quadruple by 2030, going from $34 billion in 2025 to $155 billion by 2030, according to a new report by market research firm Research and Markets. In a recent release, the company highlighted some of the findings of its report on the market for artificial intelligence in manufacturing.
“As manufacturers strive for greater agility, cost efficiency, and quality assurance, AI solutions are becoming instrumental in unlocking new levels of operational intelligence and productivity,” the release stated. “Industries such as automotive, electronics, aerospace, and consumer goods are employing machine learning, computer vision, and natural language processing to optimize production scheduling, reduce downtime, and detect anomalies early in the process. The use of AI-enabled robots, digital twins, and intelligent quality control systems allows manufacturers to scale output with precision and adaptability.”
According to the report, AI is projected to play “a transformative role in shaping next-generation manufacturing paradigms.”
“As the demand for intelligent automation and continuous process innovation intensifies, the AI in manufacturing market is poised for sustained expansion across all regions and industry verticals,” the company said in the release.
Today, innovative companies are leveraging AI to address some of the toughest challenges that manufacturers face. That includes making relevant data, too often siloed in the past, more accessible to manufacturing teams.
“Manufacturing has long been seen as one of the best opportunities for AI, but the industry has been held back by challenging data environments in plants,” said Sight Machine CEO and Co-Founder Jon Sobel, in a company release. Sight Machine, with offices in San Francisco and Ann Arbor, Michigan, is the developer of a platform for data-driven manufacturing and industrial AI.
Sight Machine’s Manufacturing Data Platform is designed to create a common data foundation by capturing and structuring data from the entire factory to deliver a system-wide view of the manufacturing process. Its industrial AI agents are reported to combine “a process engineer’s deep understanding of manufacturing with a data scientist’s skill in working with data.”
“The power of these industrial AI agents comes from their seamless access to Sight Machine’s uniquely comprehensive real-time data foundation, which creates a true digital twin of production processes,” the release stated. “This provides the key to unlocking value from challenging production data, delivering in weeks what otherwise often takes years.”
In March, the company announced the integration of NVIDIA Omniverse libraries with Sight Machine’s Operator Agent, a combination that is said to provide real-time 3D visualization of production lines for improving line performance, rapid troubleshooting, root cause analysis, and simulation. The integrated offering is “rapidly being deployed by leading global manufacturers in industries as diverse as automotive and transportation, bottling, CPG, food production, and pulp and paper,” according to the release.
In September, Sight Machine announced the integration of its industrial AI platform with Microsoft Fabric and NVIDIA Omniverse libraries. This integration is described as providing “a complete industrial AI stack for connecting, structuring, analyzing, and visualizing production data, and for integrating the resulting insights with data from across the enterprise.”
Another company, Machina Labs, is working to build what it calls “the next generation of intelligent, adaptive, and software-driven factories” that offer on-demand production in ways that eliminate traditional tooling constraints. The company, founded in Los Angeles in 2019, has developed a new manufacturing model that integrates AI and robotics to customize production of automotive body panels.
According to a release from Machina Labs, its manufacturing methods for automotive body panels and accessories could enable automakers to bring customized vehicles to market at mass-production prices. The company’s manufacturing platform reportedly eliminates the need for dedicated tooling with each model variation.
“Traditional production tools are often massive, comparable in size to a small car and weighing over 20 tons,” said Ed Mehr, co-founder and CEO of Machina Labs, in the release. “With our solution, the need for dedicated tooling per model variation is eliminated. That means lower project capital, less storage both in-plant and for past models, which today can last up to 15 years, and faster production changeovers.”
In a recently announced pilot project with Toyota Motor North America, Machina’s RoboForming technology will be used to customize production body panels. The goal is to bring “automotive-grade quality and throughput to low-volume manufacturing,” the release said.
“AI-powered manufacturing is transforming how products are designed and produced at scale,” said George Kellerman, founding managing director at Woven Capital, in the release. “Customers increasingly demand more personalized products while engineers need faster, more cost-effective paths from concept to production without the constraints of traditional supply chains. We’re excited to team up with Machina Labs, supercharge their development roadmap in automotive, and support their journey in accelerating innovations that advance the future of manufacturing.”