Kristen Smith 
A strong data strategy is essential for government agencies aiming to harness artificial intelligence for cyber defense, said Matthew McFadden, vice president of cyber at General Dynamics Information Technology, in an opinion piece Government Executive published Thursday. He noted that the effectiveness of AI tools depends not only on their algorithms but on the quality and accessibility of the data that powers them.
“As adversaries scale their tactics, we have to level up too,” McFadden said. “AI is going to help us, but only if we have the right foundation in place.”
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Why Data Quality Determines AI Effectiveness
AI-enabled cybersecurity depends on reliable, well-governed telemetry data that can inform tools used for behavioral analytics, network monitoring and automated threat response. McFadden said agencies often possess enormous amounts of information but lack the structure needed to make it actionable.
“If you don’t have access to the data, how can you act on it?” he said, pointing out that fragmented systems and isolated cloud environments limit how AI can analyze and respond to threats in real time.
How Agencies Can Turn Data Into Actionable Intelligence
McFadden said federal cybersecurity teams must focus on making data usable, not just collecting it. That means establishing clear governance policies, improving data quality and breaking down silos that prevent information sharing.
“We can leverage data to prioritize risk, we can leverage it to look for outliers that could be an adversary,” McFadden said. “And in the event of a breach, we can leverage it to automate our response and remediate high-risk systems.”
Three Steps to Build AI-Ready Data
McFadden outlined three key steps for agencies to prepare data for effective AI integration:
- Assess the data landscape. Agencies should catalog their existing data, evaluate its value and remove irrelevant or redundant information that adds cost and slows analysis.
- Optimize and right-size data. “Just because you’re ingesting that data doesn’t mean it’s all usable,” McFadden said. Agencies should focus on centralizing only high-value data to improve efficiency and accuracy.
- Automate with purpose. Once data is organized and validated, automation can reduce manual workloads and speed threat response. “Without automation, the cybersecurity workforce is stuck in a reactive cycle,” McFadden warned.
Building Toward Responsible AI
McFadden urged agencies to apply AI responsibly, using it as a force multiplier to enhance, not replace, human expertise. “The reward outweighs the risk,” he said, noting that with the right data and framework, AI can help them correlate faster, reduce risk and strengthen defenses.
