INSIGHT ENGINES MARKET ANALYSIS

Reluctance to adopt new technologies is indeed restraining the growth of the global insight engines market. Many organizations are hesitant to embrace new technologies like artificial intelligence and machine learning based insight engines due to the perception of risk involved with deployment of such advanced technologies. There is a lack of understanding among decision makers about real capabilities and business benefits of insight engines. Many feel that critical business decisions should only be made by humans and not machines.

This reluctance stems from fear of job losses if insights are generated automatically through machines. Many organizations are also concerned about data privacy and security challenges with deploying insight engines. Managing huge volumes of internal and external data and ensuring privacy and access control is a complex task. There are genuine fears that customer and employee data could be compromised if deployed without proper controls and governance. Transitioning to insight engines also requires cultural change within organizations. Not all employees may be receptive to machines playing an active role in decision making process. Letting go of manual processes built over years requires mindset shift.

Market Opportunities: Scope for insight engines in emerging applications

Insight engines have immense potential in emerging application areas with the rapid digitization across industries globally. As more organizations adopt digital practices and gather huge troves of structured and unstructured data from various sources, insight engines can analyze these diverse datasets and extract meaningful insights in real-time. This ability to glean intelligence from complex data landscapes automatically through machine learning and natural language processing is opening up new use cases for insight engines. Forward-thinking companies have already started deploying insight engines to power personalized recommendations, predictive maintenance, anomaly detection, sentiment analysis, document classification and summarization, among other strategic decision-making functions.

As insight engines learn from massive amounts of data constantly, their analytical capabilities will continue to improve and augment at an exponential pace. This will see insight engines moving beyond basic queries and reporting into more human-like conversational capabilities over time. Their scope will extend from desk research and analytics to transforming entire business processes with optimized outcomes. As insights need to be delivered just-in-time across organization silos, insight engines are being integrated with other applications via APIs and embedded analytics. This is allowing both internal users and customers to access tailor-made intelligence ubiquitously on any device or channel of their choice.