Predictive analytics, real-time monitoring, smart systems and enhanced safety are changing the industrial environment, improving sustainability, costs and waste management. Companies are benefiting from the ability to track assets in real-time, implement precision farming and livestock monitoring, and create more connected ecosystems that shave time and worry off the management of industrial environments.
For sectors such as mining, these changes are transforming safety and sustainability. “If a mine can detect early signs of machine stress or gas leaks, it can prevent downtime, protect workers and reduce environmental harm,” says Nithen Naidoo, CEO and founder of Snode Technologies. “Predictive analytics has become as important as the drill or the conveyor belt.”
At one of Snode’s mining clients, integrated data systems now combine operational metrics with security telemetry to predict failures before they happen. The same models that identify anomalies in network traffic can also forecast when a crusher blade is at risk of failure, an event that can cost millions in lost production every minute.
It's progress. Brilliant, essential progress that has the potential to add upwards of $4.4 trillion to the global economy and boost upwards of $103 billion in economic value across keys sectors in Africa.[1] This is the finding from McKinsey when analysing just how AI tools alone can double the potential of automation, predictive maintenance and yield optimisation. The African Development Bank and G20 work on AI‑driven productivity suggests that effective deployment of AI and Industry 4.0 technologies could significantly raise Africa’s labour productivity and industrial GDP, framing industrial AI as a “transformative catalyst” for manufacturing, energy and mining.[2]
However, all these benefits must be built on one core and critical foundation – cyber security. As Naidoo explains: “Digital transformation is now inseparable from security. If industrial systems are to operate sustainably, then cyber security needs to sit at the heart. Without it, the convergence of technology and industry will introduce risks that can undo the very efficiencies that organisations are trying to achieve.”
Many legacy operational technology (OT) systems have not been built with cyber security in mind and these tools and systems are incapable of providing the levels of protection that companies need as they move deeper into the digital era. They were not designed to manage bespoke protocols or embedded devices, or to ensure the absolute and rigorous security required in industrial environments that have open architectures and diverse vendors, sensors and systems.
“Snode’s platform integrates security analytics across IT, OT and IOT layers to give operators a unified view of risk,” says Naidoo. “By analysing patterns across connected systems, we help our clients identify vulnerabilities and uncover opportunities for optimisation.”
Naidoo points to projects where the same models used for cyber risk are being applied to agriculture, where AI-driven disease detection helps farmers intervene early and protect yields. In industrial settings, the same principles support energy efficiency and worker safety.
“Security is what allows digital systems to land safely,” he concludes. “It’s what ensures that predictive technologies actually protect companies rather than creating new risks. If companies adopt next-generation technologies with cyber security as the foundation, then they are building both securely and sustainably. And this is the smart way to ensure ongoing agility and resilience.”
[2] https://aisma-alliance.org/wp-content/uploads/2025/05/Classeur1_compressed.pdf
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