A factory with workers operating machinery and a conveyor belt system in operation.

Unlocking the true potential of industrial AI

As industrial AI reshapes factories and supply chains, the provider ecosystem is rapidly expanding. Companies seek AI to boost efficiency and speed innovation, while startups can create value and disrupt sectors from pharma manufacturing to logistics and aerospace.

Funding in Europe mirrors this trend: in the first quarter of 2025 alone, AI companies in Europe raised approximately €3bn in VC funding, representing a 55% increase on the same period in 2024. The reason for this momentum is simple: in sectors where businesses are delivering under extreme time and budget constraints, executives are hungry for applications that reimagine workflows and facilitate significant improvement to the bottom line.

New generative [AI] approaches can offer totally new solutions with digital simulations and next-level efficiencies that were previously unachievable.

Catherine Crump, Managing director, WIRED Consulting

“Not only are these delivering a step change in efficiency, but some are also unlocking entirely new processes and ways of working,” says Catherine Crump, managing director of WIRED Consulting, one of several experts in the growing AI ecosystem quoted in this article.

Impact where it matters most

Design is one area where AI can accelerate production phases and introduce new efficiencies.

As AI tools allow engineers to analyze large volumes of structured and unstructured data, they provide new perspectives on alternative materials and performance through simulation and help to resolve long-standing supply chain bottlenecks.

I see a world where supply chains will be dramatically reformatted and existing methods will be greatly disrupted.

Jon Nieman, VP Investments, G42

It is the fusion and cross-pollination of AI technologies that enables the major breakthroughs, says Jon Nieman, vice president investments at G42, an Abu-Dhabi-based AI development company focusing on solutions in healthcare, aviation and other industrial sectors.

As well as unlocking major profitability gains, AI developers have the potential to make a positive impact on a much larger scale. For Meike Neitz, founder of startup consultancy embassidy, AI’s potential role in mitigating climate change is one of its most exciting features. It can for example reduce material waste through innovation in the design phase, as up to 80% of an industrial product’s environmental footprint is already determined by its design.

The AI-driven redesign of industrial robot grippers in combination with additive manufacturing can lead to an 82% reduction of carbon emissions per robot.

“The industrial domain is still one of the world’s largest sources of greenhouse gas emissions,” says Neitz.

AI-powered solutions can play a huge role in energy efficiency, driving electrification, minimizing material waste and optimizing processes.

Meike Neitz, founder, Embassidy

Having a vision of what AI can achieve in the real world – no matter how inspiring – will only get you so far, however. As the experts featured in this article explain, founders of AI companies need a clear understanding of domain know-how, how to scale and collaborate, and an obsession with the end user.

Leading the industrial AI transformation is not something one company can do alone. That’s why we are shaping a thriving industrial AI ecosystem, which demands strong collaborations between customers, industry leaders, startups, sellers, partners and developers.

Linda Krumbholz, Senior Vice President, Siemens Xcelerator Ecosystem & Marketplace

How not to get lost in the AI hype

Industrial robotic arm assembling electronic components on a circuit board against a blurred factory background

Industrial AI aids visual simulations that deliver real impact on the factory floor.

One of the challenges that industrial AI startups face is to define a clear path to return on investment (ROI) and use cases that resonate within industry contexts. If they can’t get this right, their application will likely get lost in the noise.

According to Crump, startups need to strive to address specific unmet needs in industry. Adopting this mindset gives them a competitive advantage. “There is so much AI hype out there right now, and a deluge of startups innovating with this technology,” she says. “Those that stand out can demonstrate where their unique AI-enabled solution is tackling a clear need and leading to better outcomes. Their products and services show a tangible, positive business impact and a clear ROI.”

How the startup makes an impact can differ significantly between industrial settings, such are the many potential applications of AI technology. Startups need to show a deep understanding of how their solution interacts with industrial hardware or team-up to get domain know-how and quality industrial data sets.

The focus should be on facts, using proprietary data and providing scalable, user-centric solutions, suggests Samuel Schuler, managing director of Reimann Investors Venture Management. “Prioritize building a deep understanding of the actual industrial workflows before customizing AI solutions,” he says.

Tailored, domain-specific insights often outperform generic AI strategies.

Samuel Schuler, Managing Director, Reimann Investors VC

Alexander Oelling, the chief digital officer at ISAR Aerospace – a launch service provider for small and medium-sized satellites – also underscores the importance of real-world domain expertise.

I always try to assess founders' domain expertise beyond technology credentials.

Alexander Oelling, Chief Digital Officer, ISAR Aerospace

Getting closer to the end user

To ensure their solution delivers the promised impact on industry – and that its adoption spreads among users – startups need to demonstrate a laser focus on delivery. In practice, this means becoming extremely curious about the end user and how they engage with AI tools.

“Obsess about the people on the ground that you’re building your solution for,” embassidy’s Neitz advises founders and leaders. “Build for them, rather than their bosses. Be in touch with them to get their feedback. Learn their pains, about their work realities, about their processes.”

A person is standing in front of a large screen displaying a graph with a blue line and a red line.

Developing user-centric AI is key to successful deployment.

Oelling also stresses the value of working closely with end-users, arguing that tangible, on-the-ground results are what cut through most when startups begin to establish themselves. “Industrial AI startups that secure early-pilot implementations, even if limited in scope or partially subsidized, establish credibility that theoretical ventures simply cannot match,” he argues.

Conversely, an insufficient grasp of the customer’s working reality can have a negative impact on sales, especially when targeting companies in utilities, oil and gas, aerospace and government, which have their own needs and preferences.

“I have seen it again and again,” says G42’s Nieman. “People fail to recognize that these types of customers do not want to dump their data into a data lake, they want two-year long pilots or vendor assessments, they tend to be fast-followers and they tend to pay less exciting multiples for startups."

Ultimately, this is about establishing credibility. The good news for startups that are successful in this endeavor is that they will find themselves in increasingly high demand.

As an investor, when trying to assess whether a startup will succeed, Nieman says he pays particular attention to its origin story. “I find the path is the best predictor of the future,” Nieman says. “Knowing the fabric of the inception of the company, the product, the technology and the team is more important than any one of those pieces in isolation. What helps a company stand out is understanding its roots – the skills, thinking and mindset of the founders, and the arc of commercialization of the product. All of this either verifies or unravels the story.”

The insights for this article were provided by the jury members of the Industrial AI Awards 2025 for startups at the AI with Purpose Summit.