For decades, manufacturers have measured risk through familiar lenses: downtime, worker safety, supply chain resilience and product quality. Cybersecurity, while increasingly discussed, has often remained a secondary concern—particularly in mid-sized industrial environments.
That balance is shifting rapidly. As we move toward 2026, artificial intelligence is no longer just a productivity enabler; it is becoming a force multiplier for cyber adversaries. Attacks are accelerating in speed and sophistication, while industrial environments remain deeply exposed due to legacy systems, converged IT/OT networks and chronic underinvestment in security.
At RELIANOID, our Research & Development teams are closely analyzing this evolution. Our work in Artificial Intelligence focuses on applying machine learning, behavioral analysis and automated response to strengthen performance, availability and modern cyber defense across hybrid and industrial infrastructures.
1. From Assisted Attacks to Fully AI-Orchestrated Campaigns
AI is already embedded in the early stages of many attacks. Automated tools can analyze public data, map organizational structures and generate highly convincing phishing content in minutes. What is emerging next is a fully coordinated, end-to-end attack model driven by AI agents.
In this model, autonomous components handle each phase of the intrusion lifecycle: reconnaissance, initial access, lateral movement, exploitation and extortion. Decisions are made at machine speed and can be replicated at scale across multiple organizations simultaneously.
For manufacturers, the threat extends beyond corporate IT. Production environments rely on connected PLCs, SCADA systems and industrial sensors—many designed without cybersecurity in mind. Once attackers bridge IT and OT, the impact can include halted production, equipment damage or compromised safety systems.
This reality changes a core assumption: response windows measured in days are no longer realistic.
2. Midmarket Manufacturers as Preferred Targets
AI alters the economics of cybercrime. When reconnaissance, social engineering and credential harvesting are automated, attackers are no longer limited to large enterprises. Mid-sized manufacturers, often operating with limited security resources, become attractive and scalable targets.
Common weaknesses include limited monitoring, minimal incident response capability and an overreliance on generalist IT staff to manage both office systems and plant-floor infrastructure.
Financially motivated attacks such as business email compromise and payment fraud are growing rapidly. AI makes it easier to impersonate executives and time fraudulent requests precisely, resulting in attacks that can succeed within hours.
3. Industrial Infrastructure and the Regulatory Horizon
Alongside criminal activity, nation-state interest in industrial and critical infrastructure continues to rise. Manufacturing plays a central role in sectors such as food, healthcare, energy and transportation, placing it within the scope of national resilience.
Despite this importance, manufacturing remains relatively underregulated from a cybersecurity standpoint. Many OT environments rely on aging technology that cannot be easily patched or monitored, creating attractive conditions for sophisticated adversaries.
If current trends continue, stronger OT security requirements, mandatory incident reporting and higher resilience expectations are likely to follow.
4. Cybersecurity Leadership Still Lags Behind
Cyber risk is gaining executive attention, but in many industrial organizations it still lacks sufficient authority. Security leadership is often positioned too low in the organization, limiting its ability to influence strategic risk decisions.
At the same time, many manufacturers recognize that they cannot build all security capabilities internally. This is driving increased adoption of managed security services and virtual CISO models.
What Should Manufacturers Prioritize Now?
While organizations cannot control how attackers use AI, they can control how well they prepare. Three priorities stand out.
- Fight AI with AI. Machine-speed attacks require machine-speed detection and response. This principle guides RELIANOID’s AI-driven R&D initiatives.
- Take OT security seriously. Segmentation, visibility and incident response planning must include industrial and safety-critical systems.
- Elevate cyber risk to leadership. Cybersecurity must be treated as a core business and resilience function.
Closing the Gap
The coming years will determine whether cybersecurity remains a chronic vulnerability or becomes a competitive advantage for manufacturers. AI will favor organizations that invest early in visibility, automation and architectural resilience.
At RELIANOID, we believe that intelligent traffic management, security-aware application delivery and AI-enhanced analytics will be central to this transformation—helping industrial organizations prepare not just for 2026, but for the decade ahead.
The window for proactive action is still open—but it is narrowing fast. Let us help you.
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