Today’s manufacturing landscape is constantly being reshaped by tariffs, supply chain disruptions, cybersecurity threats and persistent labor and skills shortages. A recent Supply Chain Planning Benchmark Report found that 63% of small and mid-sized manufacturers experienced direct operational impacts from tariffs in 2025. With these pressures expected to persist, manufacturers are increasingly turning to AI to strengthen resilience and improve decision-making.

That shift is already underway. Deloitte’s State of AI in the Enterprise report found that 34% of organizations are using AI to deeply transform their business, with another 30% redesigning key processes around AI. In manufacturing, this evolution increasingly includes the use of AI agents to support product development, optimize production and balance competing operational priorities.

While much of the conversation centers on analytics, models and outcomes, far less attention is paid to how data actually moves between systems, partners and environments. Manufacturing depends on constant, secure file exchange across Computer-Aided Design (CAD), supplier orders, inspection reports and customer documentation. These exchanges span internal platforms such as Enterprise Resource Planning (ERP) and Manufacturing Execution Systems (MES), as well as a broad network of external partners.

Each point of transfer introduces potential exposure. When data movement lacks visibility, control and governance, risk does not remain isolated—it propagates across every downstream system that relies on that information. As data flows through a patchwork of processes built up over time, consistent security becomes essential to closing gaps before they become liabilities.

Legacy transfer methods create security gaps

Despite rising investment in AI and automation, many manufacturers continue to rely on fragmented approaches to file transfer. Ad hoc collaboration via email, file transfer protocol (FTP) servers, shared drives and legacy tools all remain common. Unfortunately, these methods were not designed for the scale, sensitivity or regulatory expectations that define modern manufacturing environments.

Email often lacks consistent encryption and access controls, while legacy FTP systems and shared cloud storage tools typically fall short on visibility and governance. As usage expands across larger teams and external partners, these shortcomings compound. Over time, they fuel shadow IT workflows, as employees create informal workarounds to meet operational demands, often prioritizing speed over security. This makes it difficult for organizations to answer basic questions, such as who accessed a file, when it was modified or which version informed a critical decision.

How security risk can scale

As manufacturers grow and modernize, deeper system integration and automation naturally follow. File transfers increase in both volume and speed, with data moving continuously across applications and partners. While this evolution enables efficiency, it also reduces opportunities for hands-on oversight. A single weak point in a transfer workflow can expose multiple systems.

It's no surprise that file-transfer infrastructure has become an increasingly attractive target for threat actors, with manufacturing remaining a high-value target. The IBM X-Force Threat Intelligence Report found that for a fourth straight year, manufacturing has been the most-attacked industry by cybercriminals. According to the same report, “Manufacturing organizations continued to experience significant impacts from attacks, including extortion (29%) and data theft (24%), targeting financial assets and intellectual property.”

File transfer systems are particularly sensitive points of exposure because they sit at the intersection of internal operations and external collaboration, often handling high-value data. As automation and agentic AI use cases expand, strong governance becomes even more critical. With fewer opportunities for manual intervention, misrouted, improperly accessed or inappropriately altered data can move rapidly through downstream systems before issues are detected.

Importance of governed data movement

To combat these challenges, manufacturers must treat data movement as a core control layer within their architecture, which starts with centralizing how file transfers are managed and governed across the organization. Standardization is a great start, as it allows teams to have visibility into the flow of information while also making security simpler to enforce. Then encryption, access controls based on role and audit trails can all become part of a more cohesive strategy. The end goal for manufacturers is the ability to identify anomalies and respond before issues ever escalate, rather than reacting after incidents occur and are in motion.

Enabling confidence through technology

Secure, governed data movement plays a direct role in enabling AI at scale. Trust in the integrity and protection of data allows analytics and decision systems to operate on accurate, reliable inputs. It reduces the risk of sensitive data exposure and minimizes the chance of decisions driven by incomplete or compromised information.

In an ecosystem defined by complex supplier and partner networks, governed file transfer allows manufacturers to share data confidently and operationalize AI without introducing unnecessary risk.

John Picinich is the Director of Product Management at Progress Software. He leads product strategy and vision for Progress’s file transfer portfolio, spanning both existing and emerging solutions