In a recent RANE Insights webinar, analysts Kristin Ronzi, Caroline Hammer, Matthew Bey, and Sam Lichtenstein offered a candid look at what private-sector security and threat intelligence work actually looks like day to day, and how skills from government, military, or nonprofit service translate into it. Here are the key takeaways for anyone considering the jump.
The panelists' backgrounds were strikingly different: Kristin came from the nonprofit sector doing capacity-building work in North Africa and Southeast Asia; Caroline started in corporate security at Carnival Corporation assessing threats to cruise ship operations before moving into client-facing analysis and eventually business development; and Matthew arrived with a math and game theory background and now leads scenario-planning methodology. The common thread isn't a specific degree or career track, it's the ability to apply core analytical skills (research, writing, critical thinking) to new subject matter quickly.
Clients ask about far more than the obvious headline issues. Examples raised included assessing gum arabic supply risk out of Sudan for a beverage client and analyzing Sierra Leone's mineral sands industry (a key input for white paint pigment) for another. The lesson: almost any topic has someone, somewhere, willing to pay for expert analysis on it, and analysts need the flexibility to build credible knowledge on unfamiliar subjects on demand, often by digging into local-language media, academic journals, investor relations materials, and direct conversations with subject-matter experts.
When facing an unfamiliar request, the panelists don't just start writing, they use techniques like"starbursting" (systematically listing who/what/where/when/why questions before researching) to scope the problem and target their research efficiently. This kind of structured process, common in intelligence tradecraft, is one of the more transferable skills service members and analysts bring with them.
Corporate interest in geopolitical risk has grown substantially, accelerating with events like the 2013-14 and continuing today. Many large organizations now have dedicated strategy or risk teams incorporating geopolitical analysis directly into decisions that reach the C-suite, not just security or supply-chain functions. Private intelligence firms like RANE tend to focus on strategic analysis (the "why it matters" and long-term outlook) rather than tactical, real-time monitoring, which many companies still handle in-house through their own security operations centers.
Even analysts not directly covering a conflict need to track its downstream effects. The Iran conflict, for instance, has shaped Latin America-focused work — not just through obvious channels like fuel and fertilizer costs, but through subtler links like how the conflict has diverted US policy attention and resources away from planned Western Hemisphere security operations (Cuba, cartels, organized crime),delaying timelines clients were tracking.
For multi-year forecasts, the approach involves identifying five or six key underlying assumptions (e.g., the future political stability of Iran, or leadership succession in Turkey or the UAE), rigorously analyzing each one individually, and then combining them into a broader strategic model, often using scenario planning and stability analysis to stress-test how the picture changes if those assumptions shift.
Organizations rarely ask outside firms to handle live crisis response or real-time monitoring; that function usually lives in-house. What they do seek out: help understanding second- and third-order business implications of geopolitical events, investment risk assessments, scenario planning, and sometimes simply a way to connect siloed teams within their own company who don't otherwise talk to each other about shared risks.
The panel converged on a few traits: intellectual curiosity (a drive to keep asking questions and closing knowledge gaps), strong critical thinking and argument construction, being an "information sponge" who can hold a working understanding of many topics even without deep expertise in all of them, and genuine teamwork, since the best analysis usually draws on multiple analysts' regional and topical expertise.
The panelists were direct: AI isn't replacing analysts, but it is reshaping workflows. Common uses include brainstorming (asking AI to list possible impacts to catch angles an analyst might miss, while treating the output critically), research support (using AI to locate sources rather than trusting its summaries outright), editing and gap-checking drafts, and building data visualizations, statistical models, and semantic-tagging tools for large data sets. Clients themselves are often skeptical of generative AI-written analysis, which several panelists said reinforces the value of human-driven critical thinking and verification.
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