AI keywording has revolutionised the way archives and image libraries manage content. Modern systems can scan thousands of files per hour, identifying objects, colours, and even activities. It’s fast, consistent and cheap — but not infallible. Machines can recognise what’s in an image, but they don’t understand why it’s there or what makes it relevant to a buyer.
Keywording isn’t about labelling everything you see; it’s about selecting what matters. A photo might contain “grass, person, tree, car, sky,” but only a human understands that the meaningful terms could be “family picnic, summer, outdoor leisure.” The AI sees data; the human recognises intent.
At Picsell Media, we don’t see humans and AI as competitors — we see them as partners. Our AI Mechanic tool handles the heavy lifting, generating a broad set of accurate but basic tags. Then our AI Professional editors refine that list, deleting unnecessary terms, adding context and hierarchy, and ensuring that the final keywords reflect commercial search intent.
For example, an AI might tag “people, phones, room, meeting,” whereas a human keyworder adds “business meeting, teamwork, corporate communication.” The difference is subtle but critical: those final keywords are what clients actually search for.
Automation alone tends to produce cluttered metadata — hundreds of technically correct but commercially useless tags. Human oversight removes that noise and adds value. The result is a clean, focused keyword set that strengthens search accuracy and improves discoverability.
The perfect balance is automation for speed and humans for meaning. AI delivers efficiency, while professionals supply judgement and language awareness. A hybrid workflow reduces costs, maintains consistency, and guarantees your images can actually be found.
In short: AI keywording without human quality control is like auto-translation without a proofreader — fast, but risky. The smartest image libraries let the machines do the grunt work and the humans make it great.