Spend some time talking to risk management professionals from a broad swath of vertical industries and you’ll find they all have specialized views of the global risk landscape as unique and varied as the organizations they defend. No two enterprise risk profiles, no two GSOC missions, are exactly alike.
Still, there’s a common thread connecting them all. Trust.
Over the past four months, I’ve met with more than 70 of our customers to hear how their analysts work and what they need to protect their organizations in a world of constantly evolving threats. Without fail, every conversation comes around to the non-negotiable requirement that risk intel be more than just fast. Real, actionable intelligence must be impeccably documented, verified, and, above all, trustworthy.
Trust as the core currency of risk intel isn’t new, of course. Ours is a discipline rooted in reputation and credibility. Always has been. However, the current glut of instantly available AI-generated information of questionable provenance has ratcheted the trust premium to an all-time high. What’s touted as AI-enhanced enablers for security teams often turn out to be time-wasters for analysts stuck trying to disentangle facts from speculation and hallucination. More time spent chasing sources, less time making decisions.
Look, AI is unquestionably a force multiplier for risk teams. Its rapid ubiquity in risk tools came about precisely because it makes data easier to get and more abundant than ever. But there’s a catch. AI without the hard work of added credibility and reliability doesn’t amplify much except noise. For risk management pros in the business of anticipating threats and making quick, accurate decisions to avoid disruption, credibility in AI-augmented systems is the bright line that separates confidence from confusion.
The chief operating officer of a multinational conglomerate put it to me this way:
“A lot of so-called intelligence right now is just circular operational info with obscure sources… or no sources at all. It’s non-processed information. When you can’t find the original source, it’s impossible for us to use the data for any sort of credible analysis.”
At Seerist, we maximize the speed and scaling benefits of AI-enhanced intelligence without sacrificing that credibility. Our approach starts with discipline. It’s 15-plus years of diligent curating, controlling, categorizing, validation and verification of the input sources and data stores that underpin our platform. Seerist delivers rigorously sourced findings with linked citations to guide analysts through trustworthy sources as they drill deeper into topics of interest. This discipline is what turns raw signals into intelligence teams can trust and act on when deadlines are tight, and the margin for error is razor thin.
We also do it by enriching verified geographic and situational data with actionable human intelligence both from our team of analysts and through our partnership with the global intelligence experts at Control Risks. Our AI is engineered to support this human expertise; it doesn’t try to replace it. And this human-AI nexus is part of a dynamic process. What’s true today might be false tomorrow. As global tensions evolve, the models and the analysis need to change with them in order to provide the best available snapshot of the truth at any given moment.
Finally, we enhance data credibility through restraint. Among Seerist’s most important AI design choices: if the system lacks solid, defensible information, it will not fabricate an answer. Transparency and traceability are especially important now as we introduce our new AI-powered natural-language query features, which allow any user to simply ask a question and get narrative results based on Controls Risks expert analysis. Off-the-shelf generative-AI tools like ChatGPT, Gemini and Claude are infamous for filling in knowledge gaps with fluff and fiction. Seerist never does. It can’t. By design.
In our business, we see AI hallucinations as much more than a technical flaw. They’re a credibility killer and a dangerous source of risk all their own. Sometimes, the most trustworthy response to an intelligence problem needs to be, “we don’t know yet.”
“The main reason we’ve kept the [Seerist] partnership over the years is precisely the trust we have in the quality of the sources which is obviously highly important for us,” one enterprise security director told me recently.
“There are many suppliers in the market. The quality and integrity of the data is what really separates Seerist from competitors.”
Encouraging words that speak not only to what we’re doing today, but what we’re building for the future. We know every vendor in our industry has AI in some fashion. But few have built a corpus of data that’s credibly vetted and transparently sourced.
Looking ahead, AI enhancements will surely get even further embedded in risk tools and workflows. Security teams will have access to more information than they can realistically process. The real challenge going forward will be confidence. Confidence that what’s being surfaced is credible, accurate, complete, and rooted in verifiable sources. Without that, even the most sophisticated AI tools risk becoming more complicator than collaborator.
