Artificial intelligence (AI) increasing hype and gained visibility is a well-versed term in start-ups as well as big brands. But the fact that implementing these technologies require other elements of high-quality data inputs, applied engineering concepts and most important of all Information Architecture plays vital role on the basis of which Artificial intelligence systems can be built.
Some people claim that unstructured information architecture can also result in success when it comes to Artificial intelligence, ML which can understand, interpret algorithms but that’s not the case significant amount of manual hard work is required before these setups work their magic. Hence, to take advantage of Artificial intelligence tools you must prepare your organization to apply Information Architecture properly.
With IA providing the roadmap for execution process, methods to perform various activities like content curation. IA being applied to various unstructured data or partly structured data boost big data analytics. With unstructured data lagging hierarchies, missing tags and metadata results in time consumption and stimulus responses by Artificial intelligence system as it is expected that human functions should be reflected.
Content curation helps extract value from input data churning the complex data sets with continuous integration and classification. Improved IA helps curation process maximized efficiency, faster pattern identification and greater ROI/data item through reuse.
Due to the massive data collected from various sources creating a common view is very difficult task. Dividing the data into small chunks and then aligning them with a common data model will result into consistent structure.