Business managers, and users take real-time data from internal transactional business systems for granted. They increasingly demand continuous intelligence based on real-time context data, from external sources such as social media, weather or other market data. Internal customer interactions such as click-stream data, or contact center logs, and sensors such as location, or machine data. Virtually, all digital business transformation strategies use continuous intelligence based on real-time context data to enhance one or more of their business processes. A small but growing number of early adopter companies have implemented real-time, custom-built infrastructures that provide continuous intelligence which spans multiple applications, across multiple business functions. However, most mainstream companies still lack the skills needed to achieve broad-scale, custom continuous intelligence. As more companies undertake digital transformation, they're finding the need to substantially upgrade the level of real-time data, and analytics in their systems. Descriptive, and predictive analytics as we've discussed based solely on the data in their transactional systems, even if it's real-time data is not sufficient. Their new business processes, have to provide continuous intelligence that leverages prescriptive analytics, often using machine learning or optimization techniques, and rule processing systems, for human decision support or in some situations, full decision automation. Higher-quality decisions are made by tapping a much broader set of real-time, and historical, internal, and external or exogenous data sources. Therefore we expect that over the next few years, more than half of major, new business systems will incorporate continuous intelligence to improve, and automate decisions. Unfortunately, the more powerful, and complicated forms of continuous intelligence can't be obtained off the shelf because they involve exchanging real-time data among multiple, independently designed, independently owned systems, in different business units. The hardware, and software technology to enable this, is already available but putting the pieces together, is still beyond the capabilities of many mainstream companies. Lineage companies have already done it, and first followers are starting now, but wider adoption of such solutions will be gradual.