Machine learning & optimization algorithms

Making machine processing more akin to human reasoning

Everyone is talking about Artificial Intelligence these days. Decision makers need to separate hype from reality, starting from its definition: a common mistake is to focus on automation advantages, failing to make clear the opportunities available to IT and business leaders. We can define AI as applying analytics and logic-based models, including Machine Learning, to interpret any kind of events, augmenting human decision making typically by learning from it.

If companies focus only on further automation via AI, they miss the hidden opportunities for greater business transformation and value differentiation. AI can classify information and make predictions faster and at higher volumes than humans. Typically, AI is used to “augment” existing applications and processes. For example, it might automate decisions or classify complex data. Both of these examples would traditionally require human intervention and, consequently, increased costs and risk of inaccuracy. However, AI enables enterprises to accelerate the whole process. Without replacing human capabilities, but augmenting them.