Dr. Velkoski serves as Director, Data Science at the National Association of REALTORS and Adjunct Professor at DePaul University. It has been nearly eight years since data scientist was declared the sexiest job of the 21st century. As senior professionals demonstrating the talent and creativity necessary to transform raw data into deep, intuitive knowledge, data scientists were poised to revolutionize decision-making and strengthen organizational performance. According to PwC's 22nd Annual Global CEO Survey, organizations continue to struggle to extract actionable intelligence from data. Those that participated in the survey highlighted a lack of analytical talent, data silos and poor data reliability as the main causes for the absence of progress.

The amount of data available to organizations every day continues to proliferate at a staggering volume. But technologies such as analytics and artificial intelligence (AI) have the potential to help businesses make better use of these massive volumes of data. In an age of collaboration between humans and machines--what we call the "Age of With"1--organizations can gain advantage by designing systems in which humans and machines work together to improve the speed and quality of decision-making. But not every organization is optimizing the opportunities available in the Age of With. Some do little or nothing with data to aid their decision-making. Others carry out analytics projects in pockets of the business.

The mining industry continues to face volatile commodity prices, safety and environmental concerns, and decreasing productivity savings amongst others. Artificial intelligence (AI) related technologies have the potential to bring tangible benefits for mining organizations like enhanced operational efficiency and improved safety and health conditions. What are the key challenges that arise when deploying AI within the mining industry and how can mining companies prepare to adopt AI? Read the report to understand how mining companies are already using AI‑related technologies. There are also many useful lessons for other asset intensive organisations.