The cost of creating an AI proof of concept

Today, we are witnessing AI-powered software that senses, reasons, acts, and adapts to new information. It starts by ‘learning’ from large sets of diverse data training models to recognise patterns and insights. Once the model has been trained, it can then apply what it has learned to new or unseen data, such as converting spoken words into text and sound, spotting anomalies in images, or detecting unusual patterns.

Although AI algorithms have been around for quite some time, recent advancements in AI technology have snowballed within various industries. This rapid growth is mainly due to significant drops in processing and data storage costs. At the same time, improvements in AI algorithm design, particularly in neural networks, have led to more accurate model training.

Such developments accelerate AI adoption, opening up many opportunities for organisations to make more informed decisions and improve processes, resulting in tangible business outcomes.