#USA #Vienna #AI Automation #Manufacturing Trends #Redwood Software

Overview

In the ever-evolving landscape of manufacturing, the adoption of Artificial Intelligence (AI) and automation is a critical focus for many organizations aiming to enhance efficiency and streamline operations. A recent study conducted by Redwood Software has shed light on the state of AI and automation within the industry, revealing both the potential and the challenges manufacturers face as they navigate this technological transition.

Key Findings

The report titled "Manufacturing AI and Automation Outlook 2026" highlights the following significant trends in the industry:

• - Exploration and Preparedness: An impressive 98% of manufacturers are actively exploring or considering the application of AI-driven automation in their processes. However, only 20% of these manufacturers feel adequately prepared to implement AI solutions at scale. This indicates a significant gap between ambition and readiness.

• - Automation Levels: The survey, which included responses from 300 manufacturing professionals, found that seven out of ten manufacturers have automated only 50% or less of their core operations. This limited automation hampers overall operational efficiency, contributing to an incomplete integration of AI capabilities.

• - Downtime Reduction: Despite the challenges, 60% of manufacturers reported achieving a reduction in unplanned downtime by at least 26% through automation efforts. This is a substantial achievement, suggesting that while many are still in the early stages of automation, there are already benefits being realized.

• - Data Transfer Automation: Surprisingly, 78% of respondents indicated they have automated less than half of their critical data transfers. This limitation restricts real-time decision-making and presents a hurdle in the pathway toward achieving full operational automation.

• - Exception Handling: Only 40% have automated exception handling processes, which are regarded as one of the most disruptive elements of production workflows. The lack of automation in this area signifies a bottleneck that needs addressing for smoother operational flows.

Identifying the Automation Gap

The research has unearthed a growing automation gap in manufacturing, effectively showcasing how many organizations remain trapped in mid-stage automation maturity. While the enthusiasm for AI is evident, manufacturers are struggling to realize potential efficiency gains due to fragmented workflows and the failure to coordinate actions across systems effectively.

Kevin Greene, CEO of Redwood Software, observed, “Manufacturers aren’t failing at automation—they’re hitting the limits of siloed execution.” At many companies, automation tools are in place, but their effectiveness is diminished by manual data transfers and disjointed systems that hinder the seamless execution of workflows. As a result, operations suffer from inefficiencies due to slow handoffs and poor data quality.

Looking Forward

For manufacturers to move forward into the realm of AI-driven operations, they must address these silos and work toward orchestrating a streamlined approach to automation. Those that succeed in integrating workflows, optimizing data flows, and enhancing exception handling across multiple systems will be better positioned to escape the mid-maturity trap and fully leverage AI capabilities.

Research insights indicate that Redwood Software’s clients are 2.7 times more likely to achieve higher stages of automation maturity, positioning them favorably in the competitive landscape.

Conclusion

The "Manufacturing AI and Automation Outlook 2026" report serves as a crucial benchmark for understanding the current gaps in automation and AI readiness among manufacturers. Companies are urged to rethink their automation strategies, focusing on connecting disparate systems into a cohesive operation. By doing so, they can lay the groundwork for scalable AI applications that drive efficiency and resilience in the manufacturing sector.

For those looking to delve deeper into these findings, accessing the full report will provide comprehensive insights into automation maturity, operational bottlenecks, and the necessary steps to prepare for the next wave of technological advancement in manufacturing.