Generative AI hype has finally reached the intelligence investigations and analytics industry, which means just about every platform is exploring new AI features. And some of the early headline results have been hard to ignore. When news broke that Australia’s Soze tool could analyze video, financial records, social media, emails, and documents at the same time, and review materials from 27 complex cases in about 30 hours (work that was estimated to take 81 years for a human), it became clear that there was a basis to the hype.
It’s an exciting change, and in many ways long overdue, but it’s important to recognize that adding AI to an OSINT workflow doesn’t automatically make that workflow better. Some areas do benefit from agentic automation, while others still rely heavily on human judgment, data-handling rules, and privacy constraints.
You can cram AI into almost any workflow if you try hard enough, but it rarely delivers value unless a few deeper, less obvious conditions are actually present. Before anything else, there’s the basic question: does AI belong here at all? If it’s added just to follow a trend or check a box, it won’t impress anyone, and it may raise real risks around data handling or trust.
The places where AI truly matters in OSINT are the parts that quietly drain time through repetitive, mechanical tasks or demand a level of scale and consistency humans can’t maintain. That’s where automation earns its keep, and where AI agents start to feel less like a marketing slogan and more like a meaningful advantage.
An analyst might need to track a person of interest across dozens of platforms. That can include Telegram channels, old Twitter accounts, regional news sites, breach forums, public records, business registries, and the comments section of obscure blogs. Humans simply cannot refresh all of those sources continuously. AI is useful here because it can pull everything into a single place, summarize the newest information, identify what changed since last night, and highlight anything that might matter.
International investigations usually span several languages. One post might be in Farsi, the next in Turkish, the next in Russian slang. Investigators also encounter screenshots of conversations, voice messages, phone videos, photographed documents, and PDFs. AI can translate, transcribe, extract entities, clean up text from an image, and match names across languages without slowing down. This is the kind of grunt work that takes analysts hours.
A common OSINT task is figuring out whether multiple online identities belong to the same person. Analysts look at usernames, email reuse, timestamps, posting style, shared IP information, old forum handles, and tiny clues like the same profile picture used ten years apart. AI can process these hints at scale and surface likely matches so the investigator can confirm them. This is a major boost because humans often miss weak signals scattered across hundreds of posts.
During a fast-moving event, information floods in from every direction. Analysts may try to watch eight different live sources at once. AI can watch all of them, filter out noise, and alert the analyst when something meaningfully changes such as a new claim, a location update, or a previously unseen video.
Anyone who has done OSINT knows what a disaster raw collection can be. Duplicates pile up. URLs break. Screenshots are mislabeled. Spreadsheets are filled with half-complete fields. AI can clean all of this automatically so the investigator is not wasting half their day reorganizing their own notes. Something as simple as “group all these documents by entity and date” saves enormous time.
There are tasks that no analyst enjoys. Pulling the same company filing from five different jurisdictions. Extracting email addresses from a hundred leaked spreadsheets. Checking whether a person’s username appears in a thousand forum pages. AI can handle these repetitive chores and free the human to focus on reasoning, interpretation, and context.
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