中文Barely a day passes without a story about artificial intelligence, ranging from fears over lost jobs and energy consumption to rogue models attacking companies. Yet hidden among the noise are huge advances in translation and medical research, all powered by AI, and it is clear the technology is here to stay. The wide-format print sector is no exception, and AI is now being applied in practical, revenue-protecting ways rather than as a marketing slogan.
To appreciate the potential, it helps to define AI. The term covers several layers built on machine learning models that are trained to recognise elements. These systems are not truly intelligent; they use computational power to crunch data sets, spot patterns, and produce output from assumptions based on those patterns. At its simplest, that could mean spotting print artefacts or reading X-rays; more sophisticated large language models recognise speech patterns to formulate replies, powering chatbots, predictive text and translation.
Generative AI is already reshaping design software, with users typing prompts to generate drawings, helping designers iterate concepts quickly and letting customers assemble artwork without a professional. This has driven a rise in files sent to print service providers that still need correction and preparation, creating a new bottleneck that equipment vendors are rushing to solve with AI.
HP, for example, introduced an AI variant of its Latex R530 entry-level hybrid printer. The hardware is unchanged, but the new variant ships with an AI version of the HP Internal Print Server behind a new Automatic Print Mode Selection feature, where on-board software chooses optimal settings balancing quality and throughput without human input. HP also added AI capabilities to its PrintOS Production Hub, including AI Order Intake, which turns a customer email or file into an order automatically, and AI Upscale, which improves low-resolution files in one click by generating the pixels needed to enlarge them.
Several OEMs use AI for predictive maintenance, learning from the operating status of hundreds or thousands of connected devices to predict failures. Ken Hanulec, EFI’s vice president for worldwide marketing, says AI increasingly informs decision-making in print production. EFI’s InSpec software uses the cloud to record printed images and analyse them through AI for quality control and verification, scanning output continuously to identify defects, support real-time correction, and reduce waste. Its Insight platform records machine actions to measure performance and predict failures, now extending beyond the Nozomi platform to hybrid printers and industrial textile and sign applications.
Durst has developed Kyveris, a production management system said to use AI heavily, demonstrated at Fespa Global Print Expo in Barcelona. CEO Christoph Gamper said AI has moved out of the browser and into the print shop, adding that “the next 20 years belong to industrial intelligence.” Kyveris integrates job queuing and RIP software with a robotic automation layer including autonomous mobile robots for loading, unloading and moving pallets, plus a digital twin concept to predict and verify product behaviour.
In conclusion, AI is being used across wide-format printing at many levels, helping eliminate daily problems from poor customer files to machine breakdowns, and taking out cost should lead to better outcomes for most print shops.
Source: FESPA (www.fespa.com)
The practical payoff is significant. By catching poor customer files before print, automating order entry, upscaling low-resolution artwork and predicting machine failures before they happen, AI removes some of the most persistent cost drivers in wide-format production. For print service providers operating on thin margins, those savings translate directly into competitiveness. There are, of course, workforce questions: as with every automation wave, some routine tasks shift, but vendors argue AI augments skilled operators rather than replacing them, freeing people for higher-value work. The direction of travel is clear: AI has moved out of the browser and into the print shop, and over the next decade industrial intelligence is poised to become as foundational to production as the press itself.
Specific product examples show how concrete the shift has become. HP’s on-press AI that selects print modes and ingests orders from emails removes two of the most error-prone manual steps in a print shop. EFI’s cloud quality scanning turns every printed sheet into a data point for defect detection and traceability, while its analytics platform forecasts failures before they strand a job. Durst’s Kyveris goes further, weaving job management, RIP and autonomous mobile robots into a single intelligent workflow and even modelling equipment digitally to predict behaviour. None of this replaces skilled operators; rather, it removes drudgery and catches mistakes earlier, protecting margin in a sector where small inefficiencies compound. Data governance and trust remain considerations, since cloud-connected machines stream operational information off-site, and vendors must reassure customers that proprietary job data stays secure. Looking ahead, the companies that combine reliable hardware with pragmatic, well-integrated AI stand to widen their lead as industrial intelligence becomes table stakes rather than a differentiator.
