If I can get the information faster and more efficiently with AI, is that really a bad thing?
In national security, cyber defense, and intelligence work, speed and accuracy aren’t luxuries, they’re requirements. The faster an analyst can detect, assess, and act on information, the more resilient our posture becomes. So, it’s worth asking: if tools like AI can help us get to those insights faster, does it matter how we got there?
This isn’t just a classroom debate anymore. It’s a matter of operational advantage that I’m afraid adversarial states may be addressing quicker.
Intelligence Work is Changing
In the traditional model, analysts were trained to research exhaustively and reason independently. Today, the volume of data is overwhelming, the velocity of conflict is increasing, and the information space is more contested than ever. Memorizing doctrine or manually parsing SIGINT is outdated.
AI changes the workflow. It doesn’t remove critical thinking; it simply relocates it. Instead of spending hours searching for the right piece of intel or policy precedent, analysts can use AI to surface patterns, contextualize alerts, and propose early assessments. That frees up cognitive space to focus on what it means and what to do next.
Another key shift in modern intelligence work is the sheer volume of internally generated reporting, ranging from post-incident summaries and investigative writeups to tactical threat advisories. Over time, these internal repositories have grown so vast that referencing older yet still-relevant documents in future reporting becomes a major challenge. Analysts often know the insight exists somewhere in the backlog, but tracking it down quickly, especially under time pressure, is inefficient or even unfeasible.
This is where private, domain-specific AI models trained exclusively on an organization’s own corpus can change the game. By indexing historical reports and enabling semantic search across them, these models can retrieve and summarize relevant findings in seconds. For example, if a threat actor resurfaces after a long dormancy, the AI can instantly surface prior incidents, TTPs, and internal commentary, giving analysts a head start and ensuring continuity across time. Rather than reinventing the wheel, intelligence teams can build on their own institutional knowledge more effectively. While some organizations may already employ this functionality, I believe most companies and agencies have yet to adopt it at scale; at least for now.
The Real Threat Isn’t AI, It’s Passive Use
Threat actors are already using AI to generate disinformation, automate phishing, and map attack surfaces. If defenders don’t leverage the same tools, they fall behind.
The real concern isn’t that AI makes us weaker thinkers. It’s that some people will use it to skip thinking entirely. I wouldn’t say that’s the AI’s fault, it’s the user’s intent. A disengaged mind won’t be saved or spoiled by technology. A sharp one, however, can be enhanced.
Stategic Implications
In a contested world both geopolitically and informationally, the competitive edge doesn’t go to the one who remembers the most. It goes to the one who can interrogate input, synthesize perspectives, and act decisively. AI, used correctly, accelerates the process.
National security professionals, educators, and leadership teams should embrace AI not as a crutch, but as a force multiplier. Train people not just to consume answers but to pressure-test them. To ask better questions. To turn good input into greater output.
Final Thought
Whether you’re an analyst, policymaker, or digital defender, the real skill today isn’t thinking in isolate, it’s knowing how to think with assistance. The people who learn that now will be the ones driving strategy tomorrow.
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