When we integrate Intelligent Automation, we leverage the power of Machine Learning and Artificial Intelligence, but much of the automation implemented may not use either technology. Intelligent Automation is often built on programmatic rules written to guide work through the process steps needed to create the products you sell. These solutions bring efficiency and consistency to workflow and may be all you need. However, if you are looking at adding an array of new products connecting to other processes in internal or customer organizations, consider the options AI implementations can bring to the table and the power of Integrated Platforms.

A robust AI implementation goes beyond a library of executable rules. With the rise of Generative Pretrained Transformers—GPT—the options to embed more intelligent AI into digital front ends (DFEs), digital presses, hybrid presses, finishing equipment, dashboards and software tools are vast. GPT-based solutions, whether they leverage a Large Language Model (LLM) or a Multi-modal Model, can perform tasks, interpret data and learn faster than most people. Hardware vendors can pair GPT-based programming with color management and print quality tools, including input from vision systems (scanners and cameras) in real-time, to reduce or eliminate prepress work required to build profiles and minimize reliance on operators catching print quality changes during print runs. Leveraging AI, the press can identify issues, often take needed corrective actions and then inform the dashboard solution of the issues that occurred and actions taken.

Ask the vendors who supply your hardware and software about their AI roadmap. They may tell you they have already incorporated solutions into their machines and solutions. AI can bring superpowers to processes that free people to do more critical or complex work and for vendors, it can help speed the diagnosis of problems and the needed fixes.