AI and machine learning offer tremendous promise for humanity in terms of helping us make sense of Big Data. But, while the processing power of these tools is integral for understanding trends and predicting threats, it's not sufficient on its own. Thoughtful design of threat intelligence--design that accounts for the ultimate needs of its consumers--is essential too. There are three areas where thoughtful design of AI for cybersecurity increases overall utility for its end users. To set the process of machine learning in motion, data scientists rely on robust data sets they can use to train models that deduce patterns. If your data is siloed, it relies on a single community of endpoints or is made up only of data gathered from sensors like honeypots and crawlers.