The term AI Lifecycle is primarily found in the fields of Artificial Intelligence, Automation, and Digital Transformation. It describes the entire lifecycle of an AI solution – from the initial idea to daily deployment and regular improvement.
The AI Lifecycle begins with problem definition: a company recognises there's a problem that can be better solved with Artificial Intelligence, for example, predicting product demand. Subsequently, data is collected and prepared, as no AI can function without quality data. In the next step, a suitable AI model is developed, which is intended to fulfil the desired tasks.
After development, the model is tested to ensure it functions reliably. If everything is in order, the AI is integrated into business processes and begins to take on real tasks – for example, creating forecasts for the warehouse. But the AI lifecycle doesn't end there: the AI continues to be monitored and regularly optimised so that it can adapt to new conditions.
The AI Lifecycle ensures that solutions with artificial intelligence remain sustainable, secure and effective.
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