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By Megan Carnegie
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AI is simultaneously overhyped and underestimated—often by the same people, in the same breath. The hype tends to cluster around what models say, generate and simulate. But the bigger story is where AI is heading next: into robotics, advanced manufacturing and the physical systems that make, move, and assemble things in the real world.
That is where the hard questions arise: How does AI work alongside robotics? What happens when systems built to optimize performance are pushed into environments where precision, safety and accountability are paramount? And who is responsible when something goes wrong?
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This week, those questions will be taken up in Edinburgh, where Launchpad Build AI, an AI software company headquartered in El Segundo, California, with an R&D base in Edinburgh, is hosting "World of Tomorrow," a tightly curated gathering of senior leaders from industry, government, defense and investment.
From the abstract to the physical
Already, the tectonic plates are shifting, moving physical AI from the abstract and into deployment. Faster inference is making models cheaper to run and easier to embed into real-world systems, while companies like NVIDIA, TSMC and Nebius are helping build the infrastructure needed to run robotics at industrial scale. At the same time, manufacturers and robotics firms are pushing AI into warehouses, assembly lines and other environments where machines must see, decide and act in real time.
Economic pressure is certainly driving that change: in the U.S., the workforce still has 1.7 million fewer people than it did in February 2020, according to the U.S. Chamber of Commerce, even as manufacturers continue to report hiring strain. In the U.K., the case for reindustrialization has sharpened too, with Capgemini estimating that British firms are set to invest $650 billion in it by 2028, while supply chains remain fragile and vulnerable to shocks. In Lloyds Bank’s Business Barometer survey, 37 percent of U.K. firms had experienced supply chain disruption due to a more volatile trading environment.
For governments in the U.S. and Europe, the issue is no longer just productivity. Manufacturing capacity is increasingly tied to resilience, industrial sovereignty and national security, especially as competition over chips and critical infrastructure intensifies. “There’s a disconnect in that we all want reindustrialization,” Jon Quick, CEO of Launchpad Build AI told Newsweek. “But the crossover in conversation around AI and manufacturing is hard to decipher—there’s no pragmatic middle ground of where to go and what to do.”
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The companies that can harness the right tools to keep factories running, reduce dependence on scarce labor and make manufacturing more resilient stand to gain a huge and lucrative early-adopter advantage.
The new AI power map
In manufacturing, logistics and defense, systems have to deal with messy inputs, changing conditions and legacy machinery that was never designed to talk to software. That tension is already visible in industries like automotive production, warehouse automation and industrial inspection, where companies are trying to combine AI vision systems, robotics and older production lines without interrupting output.
A chatbot can make things up; a robot arm cannot.
If an AI system misreads a part, stops a production line or makes the wrong call in a live environment, the question becomes who is responsible— the model maker, the hardware supplier, the systems integrator or the company using it. In software, failure is inconvenient; on a factory floor, it can stop production, damage equipment or put people at risk.
That is what makes the World of Tomorrow worth paying attention to. The roughly 50-person guest list includes chip, compute and simulation companies such as Nvidia, TSMC and Nebius; industrial, defense and technology leaders from Lockheed Martin UK, BAE Systems Air, Leonardo, Ericsson Ventures and Booz Allen Hamilton; investors and advisers including J.P. Morgan, Lavrock Ventures, Squadra Ventures, Bain and Orrick; and Scottish government and economic-development figures. It also brings in the investors, advisers and operators who will shape how this market is funded, governed and understood. It’s set to be a view right across the stack.
Topics on the table include what AI can and cannot do on the factory floor, how liability and IP might shift as systems make consequential decisions and what it will take to turn technical promise into operational advantage. The next phase of AI—perhaps unlike the one that preceded it—won’t be won by the loudest claims, but by the companies that can make the technology effective in the physical world.
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