Enterprises of all stripes have started to invest heavily in AI to help them understand their customers more deeply and to gain the advantages of superior customer experience (CX). Yet as leaders strive to form a more complete picture of customer preferences and behaviours, they continue to rely on ageing survey-based measurement systems that for decades have formed the backbone of CX efforts.
In the age of VUCA world & Industry 4.0 revolution, AI continues to dominate the business landscape. Whilst the naysayers have advocated the doomsday for humanity by predicting the advent of singularity, AI for good & all have several applications to usher a new change in how we make decisions at enterprise and personal fronts.
Featured Article: Author: Dr. Anish Agarwal, Global Head of Analytics, Dr. Reddy’s Laboratories The Metaverse is one of the most significant rising technologies right now. Some will say you have to travel in time to know about it. But the metaverse has given a huge platform to people to hypothetically get into the imaginary world. […]
Featured Article: Author: Jayachandran Ramachandran, Senior Vice President – Artificial Intelligence Labs Course5 Intelligence There are multiple inflection points in the history of the computation industry since the invention of computers in 1945. Some of the seminal moments are the advent of mainframe technology, personal computing, graphical user interface, Internet, mobile tech, cloud tech, artificial […]
Featured Article: Author: Tarana Chauhan, Procurement Analyst, AB InBev Dependency on Commodities and Associated Risks: Companies with Agricultural commodities as their core raw material face several risks in supply security. Agricultural commodities not only suffer from the risks associated with market dynamics like all other commodities but are also impacted by environmental factors making them […]
Featured Article: Author: Abhishek Sengupta, Walmart Global Tech India Introduction: A necessary but often tedious task data scientists must perform as part of any project is quality assurance (QA) of their modules so as to prevent any unforeseen incidents during deployment. While Quality Assurance and Excellence is quite prevalent in Data Engineering, QE in Data […]