AI projects require a different approach than traditional IT projects in order to succeed. This article covers the 5 main differences between AI and traditional IT projects that would help you adopt the right approach towards clients. First and foremost, specification is completely reversed. What this means is that instead of defining rules, you give the result as an input that will train the AI. This, in turn, means that you have to know the data you are working with. AI projects need to be conducted predictively, with a project design that supports predictive project development.
The whole journey is conceptual, and the end-result has an enormous effect on change management. Cognitive AI solutions can have a major impact on the business environment and for that reason they need to be thoroughly planned. The excitement with each AI project is that the final result is not always known in advance, which is both challenging and rewarding in the end. Read the full article for more detailed elaboration of the differences between AI and other IT projects.
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