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AI-Powered Cost Estimation: How to Make Digital Printing and Signage More Profitable
Will humans and intelligent machines work together in the future to create proposals for large-format printing projects? It sounds like a distant dream, but the products are already on the market.
Cost estimation has always been one of the most challenging tasks for printing and sign-making companies. Material costs, machine run times, setup costs, post-press processing, and outsourced services must be factored in quickly to arrive at a competitive price.
At the same time, customers today expect quick quotes. Often, even for complex inquiries, a binding quote is expected within hours. In an industry increasingly characterized by small production runs, customized products, and intense competitive pressure, pricing becomes a decisive factor.
Artificial intelligence (AI) is currently bringing about fundamental changes in this field. While traditional costing systems are based on fixed rules, modern AI solutions can analyze large volumes of historical production data. This makes it possible to identify patterns and derive optimal pricing recommendations. The goal, therefore, is not only to calculate costs more quickly and accurately, but also to make better business decisions.
What AI-powered Cost Estimation Means in Practice
Software providers define AI-powered cost estimation as the use of machine learning methods, knowledge databases, and intelligent algorithms to automate cost estimation processes. The systems access production data, material prices, machine data, and other operational information. Based on this data, they calculate the most economically viable production strategy.
Unlike traditional cost-calculation tools, modern systems can evaluate different production methods simultaneously. This makes it possible, for example, to determine whether a job can be produced most profitably on a digital press, using offset printing, or through a combination of different methods.
At the same time, factors such as delivery dates, material availability, and machine utilization are taken into account. In this context, Rogler Software refers to a cost-calculation solution based on artificial intelligence and a knowledge database that can automatically determine optimal production paths.
What advantages does AI offer for cost calculation in digital printing?
The greatest strength of AI lies in its ability to analyze large amounts of data in a very short time. Until now, complex calculations were usually handled by experienced employees or by management itself. This involved manually checking numerous parameters. Because this is extremely time-consuming, decisions are often made “on a gut feeling.” An intelligent system, on the other hand, automatically analyzes all relevant factors.
This significantly reduces the time required to process quotes. Instead of spending several minutes or even hours on a quote, quotes can be generated in just a few seconds. This reduces the workload on highly qualified employees while also making business processes more stable. Previously, periods of sick leave or vacation could lead to significant delays in submitting quotes.
With the help of AI, even less-skilled workers are able to initiate complex calculations. In many cases, this actually reduces the error rate. Incorrect material assumptions, overlooked steps, or incorrect surcharges are among the most common causes of margin losses in printing companies.
In addition, AI systems enable dynamic price adjustments. If material costs or purchasing terms change, the calculation bases can be updated automatically. This reduces the risk of bidding on jobs with outdated cost estimates and giving away profit margins.
AI-powered pricing would even make it possible to adjust prices based on demand. Similar to taxi alternatives like Uber, the same print service could be offered at a lower price when demand is low. If demand rises—for example, due to an imminent major trade show—a surcharge would be conceivable. Currently, however, such pricing models are not yet widespread in the printing industry.
However, even today, the following holds true: In the project business for digital printing and advertising technology, the provider who is the first to submit a solid proposal often wins the contract.
What AI-powered pricing solutions for print are available on the market?
Rogler Software is one of the established providers. The company combines cost estimation, production planning, and workflow automation in a single, integrated, AI-powered software environment.
Graphic Communications offers a range of software products for automating cost estimation. The company increasingly describes its strategy as AI-powered automation of quoting, production, and reporting processes. It also offers iQuote , a solution specifically designed for cost estimation.
In addition, other providers such as Fiery , CTM , printIQ , and Ordant are increasingly integrating AI and automation features into their MIS and workflow solutions. The trend is clearly moving toward intelligent, largely automated pricing. However, artificial intelligence operates in the background. Data is entered as usual via the keyboard into data fields.
The GelatoConnect Estimator offers a relatively new approach. The solution uses generative AI to understand customer inquiries in natural language and automatically derive production parameters and price suggestions from them. According to the provider, initial calculations can be generated within 15 seconds.
Custom AI Agents as an Alternative to Standard Software
In addition to commercial industry solutions, larger printing and advertising technology companies, in particular, are increasingly turning to AI agents they have developed in-house. These agents access ERP systems, material databases, production metrics, and pricing rules via interfaces. The agent acts as a digital cost estimator and generates price proposals based on available company data.
The biggest advantage lies in the high level of flexibility. In-house AI agents can be tailored precisely to a company’s machinery, production processes, and individual margin targets. This approach offers considerable freedom, particularly in the sign and display industry, where custom-made products and project-based services are common. In addition, the company’s proprietary know-how remains entirely in-house and can be systematically further developed.
Many companies start with small pilot projects and expand functionality step by step. Compared to implementing and deploying a comprehensive MIS, this approach often seems more appealing. During the demo phase, AI services are often free or very inexpensive to use.
However, there are also risks. One important factor is the ongoing cost of AI models. If large language models are used intensively, the so-called token costs can rise unexpectedly sharply. This can result in a significant cost burden, particularly when thousands of automated calculations are performed each month. This is especially true when, for example, customers can perform AI calculations on their own via a web portal.
Added to this is the risk of inaccurate results. Generative AI systems can misinterpret information or incorrectly weight incomplete data. In-house software developers often lack experience as well. However, even minor errors in material costs, setup time, or outsourced services can significantly skew the cost estimate for a job.
Many companies are therefore turning to hybrid models in which AI generates a price proposal that is then reviewed by experienced employees. Especially for complex signage projects, human expertise remains an important component of quality assurance for the time being.
Limitations of AI-Based Cost Estimation
Despite all the progress that has been made, AI cannot replace clean master data. The quality of a cost estimate continues to depend on the quality of the underlying data. Incomplete machine hours, outdated material prices, or incorrect work plans inevitably lead to inaccurate results.
Furthermore, pricing strategy remains a business decision. AI can calculate costs, optimize production processes, and analyze sales opportunities. However, management must still determine the target margin and the market position a company aims to achieve.
Will AI-powered cost estimation become the standard?
AI-powered cost estimation is becoming one of the most important tools for increasing profitability in digital printing and the signage industry. Faster quoting processes, more accurate cost calculations, and better margin control promise significant competitive advantages.
Both new and established providers are increasingly turning to AI for enterprise software—both in the front end and behind the scenes of their software solutions. At the same time, innovative printing companies are developing their own AI agents that offer maximum flexibility.
The key question, therefore, is no longer whether AI will change the way costs are calculated, but rather how thoroughly printing and advertising technology companies will integrate these capabilities into their business processes.
Source
- FESPA (2026-08-20) - Original article: AI-Powered Cost Estimation: How to Make Digital Printing and Signage More Profitable
