2026年机器愿景:业界领袖AI贸易变化和未来一体化

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The imaging and machine vision sector stands at a turning point. As Imaging and Machine Vision Europe reported recently, the European machine vision industry is predicted to return to growth in 2026 , after three consecutive years of contraction. But as we head into this week’s VISION 2026 exhibition (come see us at Hall 8, Booth D90), it is apparent that technological evolution, changing global trade dynamics, macroeconomic headwinds and transformative potential of artificial intelligence (AI) are all still reshaping how industrial inspection and vision systems are engineered, deployed and scaled. To capture a snapshot of where the machine vision sector stands – and where it is heading over the next half-decade – we gathered perspectives from some of the key executives, optics experts and automation leaders within our IMVE Visionaries community. These industry leaders offer a candid look into their main operational challenges, the reality of AI on the factory floor and the core competencies that will define the next generation of vision integrators. While long-term demand for automated quality inspection remains strong, vision companies are navigating intricate operational hurdles. These range from traditional commercial pressures, such as customer acquisition and client education, to broader geopolitical and macroeconomic shifts affecting key industrial hubs. For Christian Pennycate, Managing Director at Soldel, the fundamental challenge is centered on commercial pipeline execution. It is “always the same story”, he says. “The sales funnel. Finding customers that feel pain and have a desire to address it.” For developers offering advanced AI solutions, operational friction often arises from rapidly expanding technical capacity while simultaneously educating potential clients on technological capabilities. Douglas Brion, CEO at Matta, says his company's main challenge involves “scaling fast enough and educating customers on the capabilities of state-of-the-art AI vision”. Talent acquisition, too, remains a growth constraint across hardware and software design teams. Gaspar van Elmbt, CEO at VA Imaging, says expanding operational capability hinges directly on workforce recruitment, on “finding the right employees to grow”. Beyond commercial pipeline management and recruitment, global industrial trade patterns are still exerting pressure on specific regional markets, most notably across European manufacturing strongholds. Mariano Perálvarez, Optics Master at IDNEO Technologies, explains how shifting global market shares in automotive manufacturing are causing ripple effects across European suppliers and driving strategic diversification: “Our firm primarily focuses on the automotive sector. Currently, China is absorbing a significant market share, which is causing a noticeable slowdown (or 'freezing effect') here in the European market. This is pushing us to diversify into other high-growth sectors, like aerospace.” Operational success is also deeply influenced by how early machine vision engineering is incorporated into wider industrial machine design workflows. Raffaella Riccato, Machine Vision Specialist and CEO at Hypersphere Consulting, identifies a widespread architectural misstep in industrial automation projects where vision technologies are brought in too late in the process: “Machine vision is part of the automation; this shouldn't be an afterthought after the machine is designed, but a parallel project in conjunction with the machine builder.” Finally, identifying qualified deployment partners remains a challenge. Ravishankar Rajagopalan, CEO at Augurai, says one of the chief operational roadblocks facing his organisation is “finding reliable system integrators for automation and robotics”. AI and deep learning have dominated technical discussions, marketing campaigns and industry headlines across the machine vision landscape. From automated defect classification to complex surface inspection and anomaly