Your Guide to Understanding IT Trends in Manufacturing

In an environment of inflationary pressure, labor constraints, and fragile supply chains, modern manufacturing technologies have become core to maintaining operational resilience. Artificial intelligence (AI) and cloud technology are among the leading technologies redefining how manufacturers adapt to disruption and deliver long-term value.

This guide examines the top IT trends in manufacturing to help leaders identify which capabilities align with their most pressing business challenges.

IT Trends Reshaping Manufacturing Strategy​

1. Stronger Cybersecurity on the Shop Floor​

Recent attacks on major manufacturers underscore the growing operational risks tied to cybersecurity.

For example, in 2024, Volkswagen faced a temporary halt in production due to a third-party breach. The breach originated from a compromised third-party service provider, underscoring the cybersecurity risks inherent in complex supplier networks. 

To mitigate these risks, manufacturers are adopting layered cybersecurity strategies, including:

• Smart access controls tied to user roles
• Continuous industrial network monitoring
• Zero Trust architectures that verify all activity

Manufacturing companies are also ensuring that frontline employees are a core layer of defense. Targeted cybersecurity training programs are reducing the risk of phishing, ransomware, and social engineering attacks that bypass technical safeguards.

2. Growing Focus on Edge Tech, Wearables, and Private 5G

Industrial workers need tools to match their on-the-go reality.

Manufacturers are implementing wearables—smart glasses that enable hands-free access to shop-floor data, repair instructions, and more. These edge devices increasingly sit on private 5G networks for low-latency connectivity on the plant floor.

At the same time, vendors are increasingly investing in industrial edge-AI platforms designed to support machine vision, anomaly detection, and real-time safety monitoring. These platforms process data locally to detect defects, flag equipment hazards, and identify unsafe worker behavior.

By blurring the lines between worker and data, edge technology is paving the way for a smarter, more agile manufacturing future.

3. The Transition to Cloud ERP and Hybrid Models​

Cloud adoption is accelerating in manufacturing, especially where scalability, interoperability, and cost management are strategic priorities. 

For example, cloud ERP and cloud-delivered MES (Manufacturing Execution Systems) are becoming central to connecting operations across plants, suppliers, and distribution channels.

Manufacturers are also using the cloud to support functions like CRM, procurement, and finance. These applications benefit from improved accessibility, automated updates, and the ability to scale during periods of growth or consolidation.

Many organizations are moving toward hybrid or multi-cloud strategies—deploying cloud solutions where they drive the most value, while retaining certain systems on-premise for control, latency, or regulatory reasons.

4. Advancement of Digital Twins and Simulation Capabilities​

Digital twins—virtual replicas of physical systems—are enabling manufacturers to:

• Shorten product development cycles
• Optimize production lines through real-time simulation
• Enable remote diagnostics and performance monitoring

Digital twins are increasingly tied to product lifecycle management (PLM) and live operational data.

For example, Siemens’ integration of NVIDIA’s Omniverse visualization tools demonstrates how digital twins are evolving into real-time, collaborative environments.

5. Expanding Adoption of the Industrial Internet of Things (IIoT)​

IIoT connects sensors, machines, and enterprise systems to generate actionable data in real time. Manufacturers are using IIoT to enable:

• Predictive maintenance
• Environmental compliance tracking
• Real-time production optimization

As IIoT adoption expands, manufacturers are placing greater emphasis on seamless data flow between production systems and enterprise platforms. This connectivity is becoming critical for meeting emerging compliance and sustainability mandates.

6. Increasing Importance of AI-Enabled ERP Systems

AI is a foundational layer for many of the top manufacturing ERP systems. Manufacturers are leveraging AI for:

• Demand forecasting
• Schedule optimization
• Process automation
• Financial analysis

Generative AI is also playing a growing role in summarizing ERP data, assisting customer service, and guiding decision support. 

For example, popular ERP systems now embed AI agents to generate contextual recommendations and predictive alerts directly within workflows.

Looking ahead, organizations should expect AI to power self-correcting supply chains and real-time decision frameworks. However, our AI readiness consulting team has been emphasizing that success depends on data readiness, governance, and strategic alignment across the business.

7. Increasing Focus on Sustainability and Circular Manufacturing

Digital platforms now play a central role in connecting data across the product lifecycle. This includes integrating material traceability, supplier transparency, and lifecycle analytics to support both compliance and sustainability goals. 

By aggregating information from ERP, PLM, and supply chain systems, manufacturers can gain a unified view of sourcing practices, carbon footprint, and end-of-life impact.

Increasingly, manufacturing companies are embedding sustainability into IT strategy through:

• Green IT architectures that reduce energy consumption across data centers and industrial systems
• Circular-economy models that prioritize reuse, recycling, and resource optimization
• Digital product passports that track materials from raw state to disposal for transparency and traceability
• Data systems designed for ESG and carbon reporting, enabling compliance with regulations like CSRD and future-proofing environmental disclosures

Learn More About Manufacturing IT Trends​

Digital trends offer exciting possibilities, but their impact depends on your organization’s readiness across people, processes, and data. 

AI adoption will stall without a governance framework. Similarly, digital twins require high-integrity data and systems integration.

Panorama’s independent consultants help manufacturers assess organizational readiness before they invest in digital transformation. Schedule a free consultation to learn about our technology assessment services and AI enablement services.