Bridging the Divide: Navigating IT/OT Convergence in Modern Manufacturing

Reducing Risks in IT/OT Converged Manufacturing Environments

The push toward connectivity also expands the cybersecurity risk surface. Legacy OT systems, built without modern security requirements in mind, introduce exploitable vulnerabilities once connected to broader networks.

“They often have security holes that result in ransomware being inserted into the network,” Hojlo says. 

He notes another area of exposure is external ecosystem collaboration, whether that means suppliers working with OEMs or multiple participants working together for a joint venture.

“Different systems in different IT architectures certainly can expand the attack surface,” he says.

The consequences are significant. In manufacturing, downtime is expensive, making ransomware a particularly disruptive threat. Simultaneously, increased collaboration across supply chains and partner ecosystems has introduced additional exposure as data moves across different systems and architectures.

Mitigating that risk requires a layered approach. Security controls must extend from enterprise systems to the factory floor, incorporating threat detection, identity management and access controls across all locations and endpoints.

Hojlo cautions that without that consistency, gaps in coverage can undermine broader security strategies.

DIVE DEEPER: Find out how to manage the convergence of IT and operational technology securely.

Aligning IT and OT Teams for Digital Transformation in Manufacturing

While technical challenges are substantial, cultural differences between IT and OT teams are another equally significant barrier. IT organizations are typically structured around rapid change and centralized governance, while OT teams prioritize stability and deterministic performance to avoid disruptions in production.

“It is true that IT teams move more quickly to change than OT,” Hojlo says. 

Historically, both domains have moved cautiously in adopting cloud and advanced analytics, but that is changing. Over the past five years, manufacturers have accelerated digital initiatives, often running multiple transformation efforts simultaneously, including cloud migration and AI deployment.

“IT/OT convergence has become so fundamental to working effectively as an AI-fueled digital organization, teams recognize the need to converge technically and organizationally,” Hojlo explains.

To bridge the gap, many organizations are establishing centralized digital transformation teams, often led by a CIO or chief digital officer. These groups are tasked with aligning priorities across IT and OT while introducing new capabilities such as AI, which can unify and analyze data across the enterprise.

Hojlo explains that successful convergence requires a clear strategy for modernizing infrastructure without disrupting production — a process started by cleansing and unifying data not only with individual domains but as a connected digital thread across the organization.

“Moving to a hybrid cloud platform approach with this digital thread as the foundation is the next step, on top of which can be deployed SaaS applications that support every aspect of the manufacturing process chain,” he explains.

This layered approach allows manufacturers to introduce new capabilities — such as machine learning, generative AI and agent-based systems — without requiring a complete overhaul of existing infrastructure.

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Strengthening Data Governance in IT/OT Convergence Strategies

Governance frameworks play a central role in making this approach viable. As systems become more interconnected, organizations need clear policies governing data access, security and compliance.

“They are fundamental to proactive, predictive cybersecurity,” Hojlo says. 

Effective governance creates a trusted environment for data sharing, both within the organization and across external partners. It also supports more efficient collaboration, enabling faster engineering changes, improved product quality and reduced time to market.

The value of IT/OT convergence ultimately depends on the ability to translate integrated data into actionable insights. Without that capability, connectivity alone offers limited benefit.

Hojlo says organizations that can align systems, teams and governance around a shared data foundation will be better positioned to manage complexity, reduce risk and unlock the full value of digital transformation.

“With a unified data platform and a workflow powered by ML, as well as a set of GenAI and agentic tools in place, organizations learn more rapidly, ultimately making better decisions,” he notes.