By 2020, 50% of organizations will lack sufficient AI and data literacy skills to achieve business value. Data literacy is the ability to read, work with, analyze, and argue with data. Data literacy is the ability to derive meaningful information from data, just as literacy in general is the ability to derive information from the written word. As data and analytics become core to the enterprise, and data becomes an organizational asset, employees must have at least a basic ability to communicate and understand conversations about data. Just as it is a given that employees are now competent in word processing and spreadsheets, the ability to "speak data" will become an integral aspect of most day-to-day jobs. Gone will be the days when data scientists, analysts, and statisticians are the only ones "speaking data."

Given the pervasive nature of artificial intelligence (AI), the consequences of IT getting AI right or wrong are potentially profound. When used incorrectly, AI can unintentionally reinforce harmful biases, increase polarization and result in other damaging consequences. "With the excitement for and hype surrounding the possibilities of AI, it is easy to focus on the technology and coding disciplines -- what might considered the'artificial' aspects," says Alan D. Duncan, research vice president at Gartner. "However, what could be thought of as the'intelligent' aspects of a digitally connected world don't function -- don't exist -- without data. While conversant in the people, process and technology capabilities of business models, most executives and business and IT professionals do not'speak data' fluently," added Duncan.