With a deep background in production management and a sharp focus on the intersection of manufacturing, electronics, and security, Kwame Zaire is a leading voice on the operational risks facing modern industry. As a thought leader in predictive maintenance and quality, he has a unique perspective on how digital transformation is creating new, often unseen, vulnerabilities on the factory floor. Today, we explore his insights on the rapidly evolving threat landscape, discussing how AI-driven attacks are changing the economics for cybercriminals, why small and midsize manufacturers are now in the crosshairs, and what practical steps leaders can take to treat digital risk with the same seriousness as physical safety.
Attackers are already using AI for reconnaissance that leads to fraud within hours. Looking ahead, how would a fully AI-orchestrated attack on a manufacturing plant differ, and what are the critical first steps to test a facility’s ability to contain a threat moving at machine speed?
The difference is staggering, and it’s all about speed and scale. What we’re seeing now is just the prelude. Think of the recent incident where attackers scraped an attendee list from a conference, identified a key executive, and siphoned millions from the company all before the end of the day. That was just the opening act. A fully AI-orchestrated attack won’t just be about reconnaissance for fraud; it will be an autonomous agent coordinating every step from initial access to lateral movement and final extortion, all happening at a pace no human team can possibly track. The AI won’t get tired, it won’t make mistakes, and it can scale across thousands of systems simultaneously. For a plant, this means a threat could pivot from the corporate IT network to the operational technology (OT) controlling the machinery in minutes, not days. The first step to prepare is to test your containment capabilities under this new assumption of speed. You have to run drills that simulate an attack moving at that velocity and see where your defenses break down. You must also meticulously map every potential pathway from IT into your OT environment and ensure those critical systems have the same, if not better, protective controls.
Small and midsize manufacturers are now seen as more profitable targets than large enterprises. What are the most common security gaps you see in these organizations, and can you provide a few examples of how AI-powered social engineering exploits these weaknesses in wire fraud schemes?
It’s a painful truth, but smaller manufacturers have become the low-hanging fruit, and AI has made harvesting that fruit incredibly efficient for attackers. The most common gap is a fundamental lack of resources and specialized expertise. These companies often don’t have enterprise-grade detection tools, they certainly don’t have 24/7 security monitoring, and responsibility for both IT and OT security might fall to a single IT generalist or even a facilities manager. This creates a perfect storm. We’re seeing an explosion in wire fraud because AI can now automate the entire social engineering process. It can scan social media to know when your CEO is on a flight, mimic their communication style perfectly in an email, and send a fraudulent payment request to the finance team that looks completely legitimate. The number of these cases we’ve handled this year alone, and the dollar amounts involved, have already surpassed all previous years combined. The attackers know these organizations have minimal security awareness training, making their employees far more susceptible to these highly convincing, AI-crafted scams.
With nation-state activity rising, federal OT security mandates seem likely. For a manufacturer just starting, what are the most practical first steps to treat OT cyber risk like a safety risk? Please walk us through how to inventory and segment these critical systems effectively.
This is a critical mindset shift. For decades, manufacturers have rightly treated physical safety as a non-negotiable priority. You would never operate a heavy press without proper guards and emergency stops. You need to apply that same rigorous, life-or-death thinking to your operational technology. The most practical first step is to start an inventory, just like you would for any critical physical asset. You need to know every single programmable logic controller, sensor, and control system on your floor, what it does, and how it’s connected to the network. Many of these devices are decades old and were never designed for a connected world, making them incredibly fragile. Once you have that inventory, the next step is segmentation. This means creating digital walls around your most critical systems, especially those tied to safety functions. The goal is to make it impossible for an attacker who breaches your corporate email to simply “walk over” to the network that controls your production line. Your incident response plans must also be updated to explicitly address OT disruption, not just data theft.
In many companies, cybersecurity leadership reports to a CIO focused on uptime, not risk reduction. How does this misalignment create tangible vulnerabilities, and what metrics can a security leader present to the board to reframe cybersecurity as a core business function, not just an IT cost?
This organizational structure is one of the most dangerous vulnerabilities I see, and it’s incredibly common in the midmarket. When the head of security reports to a CIO whose primary incentives are uptime and efficiency, risk management will always take a backseat. The CIO is measured on keeping systems running and projects on budget, not on preventing a low-probability, high-impact cyber event. This means crucial security investments get delayed, warnings about systemic risks are downplayed, and the board never gets a clear picture of the true threat landscape. To fix this, the security leader needs to speak the board’s language: the language of business risk. Instead of talking about firewalls and malware, present metrics that quantify potential financial losses from production downtime, the cost of a data breach in terms of regulatory fines and reputational damage, and the risk to supply chain commitments. Frame security not as an IT cost center, but as a function that protects revenue and enables the business to operate safely in a hostile digital world. The goal is to ensure someone with genuine cybersecurity strategy expertise has a direct, unfiltered line to the CEO and the board.
What is your forecast for the evolution of AI-driven cyberthreats beyond 2026?
Looking beyond 2026, I foresee a future where offensive and defensive AI are locked in a constant, high-speed arms race. The attacks will become even more sophisticated and autonomous. We’ll likely see AI-driven threats that can dynamically alter their tactics in real-time to bypass new defenses, making them incredibly difficult to stop once they are inside a network. They will be able to identify and exploit not just technical vulnerabilities but also complex business process flaws without any human intervention. For manufacturers, this means the line between cybersecurity and operational resilience will completely dissolve. Defending a plant will require an equally sophisticated, AI-powered defensive system that can detect, investigate, and neutralize these machine-speed attacks automatically. The human role will shift from hands-on response to strategic oversight—managing the defensive AI, setting its priorities, and ensuring it aligns with the core business functions of safety, quality, and production.
