Mitigating risks and cybersecurity when implementing AI

In the age of digital transformation, businesses are adopting AI in manufacturing processes to streamline operations and improve decision-making. Particularly in the realm of manufacturing and supply chain management. This piece dives into the dual role AI plays in risk assessment and cyber security within these sectors.

Gain insight into various AI technologies used for automatic risk evaluation. Including; expert systems, machine learning, and multi-agent systems, and the types of risks these tools can help mitigate. However, alongside the tremendous potential AI holds, we also explore its inherent flaws. Detailing how AI can become exploitable, especially in cyber security.

AI and Risk management

How is AI changing risk management?

Supply chain managers must assess risks across the entire network. Including planning, supply, processing, demand, and environmental risks. With each risk measured by its likely severity and frequency. Allowing managers to rank risks for mitigation.

Manual risk assessments can be slow, and the results can vary according to who makes the assessment. Different artificial intelligence technologies can assist managers with the automatic evaluation of these risks. Each supports more reliable and consistent decision-making.

Expert systems can ask pertinent questions and provide a rule-based assessment of the risk's severity and frequency. While these systems are effective in a small business, they can be more difficult to maintain in larger supply chains.

Machine learning based systems are more effective in more complex networks. These algorithms can find hidden risk factors if they have access to enough data. They can quickly isolate the most important risks that require attention.

Multi-agent systems are the most complex and expensive systems to commission. They can, however, assess correlated and conflicting risks. While quickly taking into account the whole impact along the entire supply chain when risk frequency or severity changes.

Examples of risks that AI technologies can instantly assess include: supplier liquidity, product quality, and weather events. As well as cyber security threats, price fluctuations, and insurance risks.

AI and Cyber security

It would be great to say that AI can improve supply chain information security. Unfortunately, while it may have some advantages, the downsides will quickly surpass the benefits. More intelligent tools to detect malware, phishing, and other threats can improve the abilities of organisations to counter conventional threats.

Yet, there is nothing to stop malicious actors from using AI to interrogate hardware and software. Doing this to find risks, develop more effective malware, and deceive employees on a scale not previously possible.

AI applications themselves can introduce new vulnerabilities because it is possible to manipulate how they operate. Applications can "learn" in a wide variety of ways, but they can also be "taught". However, they can also have what we call "common sense," a capability that is still in its infancy.

Imagine the consequences of teaching an inventory management application that seven comes after four. Consider the reputational damage from a customer service chatbot trained to use offensive language or symbols.

What are the benefits of Artificial Intelligence?

What about data protection? An advantage of artificial intelligence is that it does not tire like a human operator. You can ask a chatbot endless questions - but this is also a vulnerability.

If you keep probing a chatbot with questions, you might figure out how the algorithm functions. From this, you may be able to reconstruct the data set used to train it. This data may include personal or confidential information.

A supplier negotiating with a chatbot might learn to manipulate it to reveal its negotiating position. It is possible to develop solutions to these problems, but AI is likely to help malicious actors stay one step ahead.

AI can be powerful tool for risk management, increasing cyber security protocols in manufacturing and supply chain operations. However, it also introduces new vulnerabilities. Leveraging AI technologies for automatic risk evaluation can aid in more consistent decision-making. However, we must also be vigilant of the new threat landscape these technologies can engender.

It is crucial that organisations be proactive in addressing these vulnerabilities to fully harness AI's potential without compromise. With balanced deployment and diligent oversight, AI can indeed be a game-changer in the industry.

For a deeper understanding and to explore further applications of AI in supply chain management, click here to read our guide.