Which of these data issues do you see as the most significant hurdle to taking full advantage of most AI tools?

Data Quality is one of the most critical aspects to consider for the AI journey. AI can generate incorrect results if there are quality issues with the data that is being used to the train the models.

While unorganised data and unstructured data are significant challenges, the most critical hurdle to fully leveraging AI tools lies in data quality issues. Poor data quality directly undermines the accuracy and reliability of AI models, leading to flawed insights and decision-making. High-quality data is essential for AI models to learn effectively and provide trustworthy predictions. Therefore, addressing data quality should be the top priority to ensure the success of AI initiatives, as it forms the foundation upon which all other data-related efforts depend.

Privacy and security drive the acceptance of many new technologies. While AI offers lots of possibilities, the non-corporate use of AI still needs to offer secure interaction with users and verification their data is not being secretly misused.