中文Every printer knows the feeling. A complex enquiry lands in the inbox at 4pm — a weird mix of substrates, finishes and deadlines — and someone senior has to produce a binding quote by morning. For decades, that meant manually checking machine run times, material costs, setup, post-press and outsourced services, then making a judgement call. Often, if we are honest, it meant a guess.
Artificial intelligence is now rewriting that ritual, and the printing and signage industry should pay attention. As FESPA contributor Sonja Angerer reports, AI-powered cost estimation is moving from buzzword to shipped product — and it is changing who wins work.
The core idea is straightforward. Traditional costing systems run on fixed rules. Modern AI solutions analyse large volumes of historical production data, spot patterns, and derive optimal pricing recommendations. The goal is not only to calculate faster, but to make better business decisions. Unlike older tools, AI can evaluate different production methods at once — is this job most profitable on a digital press, offset, or some combination? — while factoring in delivery dates, material availability and machine utilisation.
The speed is the headline. Instead of spending minutes or hours on a quote, AI can generate one in seconds. Rogler Software, one of the established providers, offers a cost-calculation solution built on AI and a knowledge database that automatically determines the optimal production path. GelatoConnect’s Estimator goes further, using generative AI to understand customer enquiries in natural language and produce a calculation within about 15 seconds. Other names — Fiery, CTM, printIQ, Ordant — are weaving AI and automation into their MIS and workflow tools.
The business case is more than speed. Until now, complex quotes were handled by experienced staff or management, often “on a gut feeling” because checking every parameter was so time-consuming. AI automates that analysis, freeing skilled people and making processes more stable — no more delays when someone is on holiday. It also reduces error rates: incorrect material assumptions, overlooked steps and wrong surcharges are among the most common causes of margin leakage. And because the system can update its cost bases automatically when material prices shift, printers stop bidding with stale numbers.
There is a tantalising possibility on the horizon: dynamic pricing. Just as ride-hailing apps surge with demand, AI pricing could lower a quote when the shop is quiet and add a surcharge ahead of a big trade show. That is not yet mainstream, but the technology is close.
Larger print and signage firms are also building their own in-house AI agents — digital cost estimators that plug into ERP systems, material databases and pricing rules. The upside is flexibility and the comfort that proprietary know-how stays in-house. The risk is real too: large language models carry token costs that can spike with thousands of monthly calculations, and generative AI can misinterpret incomplete data. Many shops are settling on a hybrid model, where AI drafts the price and an experienced human signs off — especially for complex signage projects.
The honest limitation is that AI cannot fix bad data. Clean master data remains the foundation; pricing strategy is still a human business decision about target margins and market position.
But the direction is clear. As Angerer concludes, the question is no longer whether AI will change print costing, but how thoroughly companies weave it into their workflows. In a market where the first solid proposal often wins the job, those 15 seconds could be the most valuable quarter-minute in the shop.
Source: FESPA — “AI-Powered Cost Estimation: How to Make Digital Printing and Signage More Profitable” (20 August 2026)
