When AI Guesses and Security Pays: Choosing the Right Model for the Right Security Decision | A Brand Story Highlight Conversation with Michael Roytman, CTO of Empirical Security

In this Brand Highlight, we talk with Michael Roytman, CTO of Empirical Security, about a problem many security teams quietly struggle with: using general purpose AI tools for decisions that demand precision, forecasting, and accountability.

Michael explains why large language models are often misapplied in security programs. LLMs excel at summarization, classification, and pattern extraction, but they are not designed to predict future outcomes like exploitation likelihood or operational risk. Treating them as universal problem solvers creates confidence gaps, not clarity.

At Empirical, the focus is on preventative security through purpose built modeling. That means probabilistic forecasting, enterprise specific risk models, and continuous retraining using real telemetry from security operations. Instead of relying on a single model or generic scoring system, Empirical applies ensembles of models tuned to specific tasks, from vulnerability exploitation probability to identifying malicious code patterns.

Michael also highlights why retraining matters as much as training. Threat conditions, environments, and attacker behavior change constantly. Models that are not continuously updated lose relevance quickly. Building that feedback loop across hundreds of customers is as much an engineering and operations challenge as it is a data science one.

The conversation reinforces a simple but often ignored idea: better security outcomes come from using the right tools for the right questions, not from chasing whatever AI technique happens to be popular. This episode offers a grounded perspective for leaders trying to separate signal from noise in AI driven security decision making.

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GUEST

Michael Roytman, CTO of Empirical Security | On LinkedIn: https://www.linkedin.com/in/michael-roytman/

RESOURCES

Learn more about Empirical Security: https://www.empiricalsecurity.com/

LinkedIn Post: https://www.linkedin.com/posts/bellis_a-lot-of-people-are-talking-about-generative-activity-7394418706388402178-uZjB/

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Keywords: sean martin, michael roytman, ed beis, empirical security, cybersecurity, ai, machinelearning, vulnerability, risk, forecasting, brand story, brand marketing, marketing podcast, brand story podcast, brand spotlight

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