Five AI mistakes and how to avoid them in your organisation

You need to collect the right data, find the right tools for your organisation, and team members need to be trained on how to build and optimise the AI models. However, even if you have found the right AI for your business and it's been onboarded well, there's still the risk that you will not be getting what you want or need from it. If an AI mistake is made, it has varying levels of severity. For example, AI that predicts real estate prices (similar to Zillow's recent issues) but isn't set up properly can result in over or under-evaluations. AI that is used to predict cryptocurrency trading trends, but doesn't get retrained on new data could lead to missed opportunities. However, for a business that is looking to adopt AI to improve processes and make them more efficient, even the smallest mistake can result in lost productivity, money, or reputation.