Over the past few years, the adoption of Artificial Intelligence into institutional investors' investment processes has proved to be successful in increasing investment results and operational efficiency. The remarkable application of such technology in this field has then grabbed substantial attention, particularly from large financial institutions, to the point that Forrester – the world's leading strategic consultancy firm – estimates that by 2025 an estimated $64 billions will be spent by large organizations to buy AI softwares and platforms.

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However, there’s no such thing as two financial institutions sharing a similar investment process. Thousands of nuances make decision-making and portfolio construction processes unique for each firm and so require AI adoption journey to be carefully crafted to achieve a specific set of investment objectives, risk budgets and constraints. That is why seamlessly integrating Artificial Technology in the investment process – both at a product or process level – requires agreeing on some ground truths and standard best practices.