Why 96% of Enterprises Face AI Training Data Issues - Dataconomy

A recent survey of over 225 enterprise Data Scientists, AI technologists and business stakeholders involved in active AI and machine learning (ML) projects, suggests that for most organizations, it's still early days for AI technology. The AI market is projected to become a $190 billion industry by 2025 ( according to Markets and Markets), and global spending on cognitive and AI systems is expected to reach $35.8 billion in 2029, an increase of 44.0% over the amount spent in 2018 (according to IDC). This research suggests AI is advanced and on the move, already being undertaken by large enterprises and ready to make an impact on how we live and work. But it is still early days for AI when it comes to the implementation of AI in organisations and there are reasons for that. An AI system requires meticulous training before it can perform its intended function. When that function involves something as complex as making human-like judgments about images or videos – "seeing," in other words – the system must be exposed to enormous volumes of accurately labeled and annotated training data.