- Since it’s capable of analyzing large volumes of production data, AI can make smart predictions, automate routine decision-making, and create more optimized workflows.
- According to Keypoint Intelligence’s research, businesses are turning to AI to improve automation, data analysis, and optimization rather than attempting to achieve autonomous production.
- AI enhances robotics systems by making them more adaptive and responsive.
By Eve Padula
Introduction
Not so long ago, artificial intelligence (AI) was primarily viewed as a distant-future disruptor in the production printing industry. It existed in trade show demonstrations and early-stage trials, but it really wasn’t an integral part of real-world workflows. In the past few years, however, AI has improved by leaps and bounds. The technology is everywhere, and it has impacted virtually every vertical industry in existence. Now, AI is moving beyond the experimentation phase and is making its way into actual deployments. This is especially the case among larger, technology-forward print service providers (PSPs).
Despite its far-reaching impact, AI isn’t affecting our industry in quite the way that many expected. Instead of completely revolutionizing the print production process, AI is facilitating incremental improvements. Businesses are leveraging AI to optimize their workflows, make better decisions, and manage the complexity of modern print production.
Bridging the Workflow Gap
Interest in AI is certainly expanding, and this is largely because of ongoing structural changes that are occurring in the production printing landscape. Modern PSPs are facing increased pressure to get more done with fewer resources. Customers are demanding shorter print runs, increased job variability, faster turnaround times, and a greater degree of customization. Traditional workflow systems were designed to handle long runs and repeatability, so they aren’t well-suited for this new reality.
AI offers a solution because it helps print providers meet the evolving needs of today’s customers. Since it’s capable of analyzing large volumes of production data, AI can make smart predictions, automate routine decision-making, and create more optimized workflows. These capabilities are particularly valuable in hybrid print production environments where digital and analog processes are used together.
There’s no question that AI is making its presence known, but it is still in its early adoption phase. Modern implementations are occurring in workflow and production management rather than on the press itself. Some of the most common areas for AI deployment include scheduling optimization, automated estimating, and production planning. Organizations are primarily integrating AI into their existing workflows to reduce the need for technical expertise and lower the risk of implementation.
According to Keypoint Intelligence’s most recent Global Software Investment Outlook, AI is most commonly used for graphic design, marketing, and operational analytics. Only 12% of total respondents weren’t using AI at all.
Figure 1. Use of AI—Current
N = 181 Total Respondents
Source: Global Software Investment Outlook; Keypoint Intelligence 2025
Current use is about efficiency. Survey participants are turning to AI to improve workflow automation, data analysis, and optimization rather than attempting to achieve completely autonomous production. At least for now, AI is being used to enhance familiar systems instead of replacing existing processes.
Future implementation plans suggest that AI will be used more strategically to better support the decision-making process. As shown in the Figure below, the focus is expected to shift toward production automation and predictive service/maintenance. Marketing applications, which are already leading in terms of current use, will also remain important in the future.
Figure 2. Use of AI – Future
N = 181 Total Respondents
Source: Global Software Investment Outlook; Keypoint Intelligence 2025
Even the small share of businesses that haven’t yet implemented AI are actively exploring it. The conversation is shifting from “Should we use AI?” to “How and where can it be used deliver the most value?” Meanwhile, early adopters are expanding their investments and implementing AI across a broader range of functions. We’re seeing a transition from experimentation to strategic deployment and integration, and this indicates that AI is becoming a core consideration for the industry.
Transforming Data into Insight
AI makes it easier to unlock the value of data, and this is one of its biggest benefits to production printing. Printing environments have massive amounts of important information, but much of this data has historically been underutilized. By transforming raw data into actionable insight, AI can help identify trends, recommend improvements, and anticipate issues before they occur.
Predictive maintenance is just one example of how AI can improve workflow. Because it can analyze equipment performance and flag potential failures, downtime can be reduced and productivity can improve. Similarly, AI-driven quality control can uncover inconsistencies early on, minimizing waste and improving output consistency.
In addition, AI’s role in automation is evolving. AI-enabled systems can perform intelligent file preparation, workflow routing, and color management with minimal human intervention. These tools are good news for human workers because they alleviate the burden of repetitive, data-intensive processes. As a result, employees have more time to focus on higher-value activities.
AI in Robotics
While still in its early stages, we are seeing a growing interest in using robotics for tasks like material handling and finishing. According to our survey data, early robotics deployments are largely focused on moving media and substrates around the production floor or loading/unloading. Because these tasks are repetitive yet labor-intensive, they are prime candidates for the automation that robots can offer.
Figure 3. Functions of Robots
N = 149 Respondents that have deployed or are considering robotics
Source: Global Robotics Survey; Keypoint Intelligence 2026
AI enhances robotics systems by making them more adaptive and responsive. This might eventually pave the way for more collaborative environments where robots and human operators work side by side. This trend is closely related to one of the print industry’s most persistent challenges: labor shortages. As experienced workers retire and fewer new entrants join the field, PSPs are struggling to maintain staffing levels. AI-enabled automation and robotics offer a way to sustain productivity while reducing reliance on specialized labor.
The Bottom Line
The interest in AI is undoubtedly strong and growing, but adoption is far from uniform. Larger firms with more resources and technical expertise are leading the charge, while smaller PSPs are generally more cautious. Integration with legacy systems is often complicated, and many businesses lack the expertise to implement AI effectively. There are also concerns with return on investment and data readiness. Some organizations lack the high-quality, well-structured data that AI systems rely on. As a result, many PSPs recognize the potential of AI but are unsure how to get started.
At this stage, AI in production printing is more foundational than transformational. We’re not seeing fully autonomous print environments or radical changes to the production process. The focus is on smaller improvements like better scheduling, smarter planning, improved analytics, and more efficient automation. Rather than completely revolutionizing the production printing process, AI is steadily improving how our industry operates. The most successful PSPs will likely be those that align AI initiatives with business goals, integrate them into existing workflows, and learn to make better use of their data. Vendors can also play a role by embedding AI into familiar platforms and lowering the barriers to entry.
Eve Padula is a Senior Consultant for Keypoint Intelligence's Production Services with a focus on Business Development Strategies, Customer Communications, and Wide Format. She is responsible for creating, analyzing, and formatting many types of content, including forecasts, blogs, industry analyses, and research/multi-client studies. She also manages editing and client distribution for many types of deliverables.
