by Jared Williams

BLUF: Artificial intelligence is quickly changing cyber operations and defense, making them more scalable, efficient, and proactive. I believe AI acts as a force multiplier by accelerating detection, automating defenses through pattern recognition, and enabling predictive analytics. This shift is needed because cyber threats are becoming more complex, but it also raises long-term concerns, including overreliance, ethical issues, and imperfect predictions. Even with these challenges, using AI in cybersecurity is not optional, but inevitable.

Artificial intelligence is changing how cyber operations work by making human operators more effective. In traditional cybersecurity, analysts review logs, investigate alerts, and respond to incidents by hand. But as networks get bigger and threats become more advanced, this approach no longer works well and cannot keep up with the threats to remain a proactive process. This is where AI solves the problem by automating repetitive, time-sensitive tasks. Machine learning models can quickly analyze large volumes of data and spot patterns that people might miss. For example, AI-powered intrusion detection systems can detect signs of advanced threats and respond immediately. The implementation of AI filters in email has already detected and prevented malicious intent by analyzing language patterns and metadata to identify suspicious content.

As someone working in data systems and preparing for a role in cyber warfare, I see this as a clear advantage. AI lets smaller teams defend larger, more complex systems, multiplying their impact without requiring more people. Russell and Norvig (2021) note that intelligent systems can learn from data and improve over time, and can make fast changes, like in cyberspace. Both help build the systems and the operators needed to gather the best patterns and become better together. By personally training their systems, they can create a unique type of security tailored to the position or areas they need to protect. This can also be used to assist other departments within the DOD when working within the DOD, ensuring an automated process for connecting and detaching systems that become compromised. The ability to collaborate within our fighting forces and in business will help build a better security structure and practices that are important to the overall infrastructure. This brings me to my next point: cyber threats are becoming more complex, which is why more people and organizations are turning to AI.

Today’s cyber threats are not just more common; they are also more advanced. Nation-states, cybercriminals, and hacktivist groups use automation, zero-day exploits, and clever ways to avoid detection. Traditional rule-based systems struggle to keep up with these new tactics. AI gives us an important advantage by allowing for predictive and adaptive defenses. Instead of only looking for known threats, AI can spot new ones by watching for unusual behavior. This is especially important for stopping modern attacks like ransomware and supply chain hacks. The ENISA (2023) threat landscape report shows how rapidly cyber threats evolve and underscores the need for improved detection methods. This supports the idea that AI is not just a nice addition but is actually needed to keep cybersecurity strong.

Now, let’s look at the philosophical side by considering “The Short Arm of Predictive Knowledge.” AI systems depend heavily on prediction. They look at past data to guess future threats. This is powerful, but it has limits. Predictions are only as good as the data and models behind them. One major concern is the risk of false positives and false negatives. An AI system might incorrectly identify normal behavior as malicious or fail to detect a sophisticated attack. In a military or critical infrastructure context, these errors could have significant consequences.

Buchanan and Miller (2017) point out that while machine learning is powerful, policymakers and practitioners need to understand its limits. Relying too much on AI could make people complacent and reduce human oversight in favor of automated decisions.

In my view, this is especially important in cyber warfare. AI can help with decision-making, but it should not take the place of human judgment. It is important to keep a balance between automation and human control, with a human in the loop and a structured plan. In the next section, we will examine the ethical and strategic issues associated with using AI in cyber operations. Using AI in cybersecurity brings up important ethical questions. For example, should AI systems be allowed to respond to cyber threats on their own? What if an automated response makes a conflict between countries worse? These questions show why we need clear policies and rules. Building responsible cyber-infrastructure means establishing guidelines for AI use and ensuring it adheres to legal and ethical standards.

There is also the problem of attackers using AI, being the opposition to our force multiplication. As defenders improve, attackers use AI to refine their tactics in less time with less compute actually needed and this is a problem that will not stop as code is being written and changed and open-sourced models continue to improve without the implementation of the same boundaries and safeguards if you can properly prompt engineer the correct reasoning. This creates an arms race, with both sides always trying to stay ahead. This reinforces my position that AI is not just a tool but a strategic necessity. Failing to adopt AI in cyber defense would place organizations and nations at a significant disadvantage. Artificial intelligence is changing cyber operations and defense by acting as a force multiplier for those trained in any job field, both cyber and non-cyber. It improves detection, automates responses, and allows predictive analysis, making it a key part of modern cybersecurity.

However, this change brings challenges. We need to consider the limits of prediction, ethical concerns, and the risks of overreliance on automation. I believe AI is needed for strong cyber defense, but it should be used carefully and backed by good rules and human oversight. Some people may say that AI is too risky or that old methods are enough. While these concerns are real, the evidence shows that today’s cyber threats are too big and complex for traditional solutions. My understanding is that AI should be a tool, like Microsoft Word, that provides the ease of a linear platform for typing and reflects how typing has replaced the form of writing. This ideology did not replace the implementation of the ideas of the individual author of each work, but made the work uniform and presentable to all, and created a consistent data source that could be evaluated through a file type. The same way that AI will prompt answers, but the questions asked are far more intricate and specialized, and still have to be verified by other sources on their validity through continued data and research.  AI offers the advanced tools we need, and will only be as good as the operator using it.

In the end, I believe AI is both an opportunity and a responsibility. As someone planning to work in cyber warfare, I see how important it is to use AI effectively while also knowing its limits. The goal is not to replace people, but to help them, so cybersecurity stays flexible, strong, and ethical.

References

Buchanan, B., & Miller, T. (2017). Machine learning for policymakers: What it is and why it matters. Belfer Center for Science and International Affairs.

ENISA. (2023). Threat landscape report. European Union Agency for Cybersecurity.

Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson.