The pioneers behind artificial intelligence and machine learning have successfully broadened their reach within the business world, and found an integrality across all key verticals. Better tooling and innovation in data labeling are two of the factors behind this rapid and unprecedented development – and, more importantly, the discipline's ability to find centrality to both everyday processes, and long-term development. From highly perceptive robotics to self-driving cars, we live in an age where almost anything feels possible, provided we have the patience and technology on our side. And, as these sophisticated outputs begin to cross the bounds between'idea' and'reality', developers and tech companies must continue to utilise the most refined and efficient data annotation processes. Since annotation is the key to accurate machine learning, the goal is to make this process more efficient.