Decision Analytics or AI

Many engineering students interested in building intelligent applications are confused with two related yet altogether different disciplines. Both Decision Analytics & AI have common roots in Big data & Data science. Only difference being one is closely associated with automation whereas the other is closely associated with productivity.

Application of productivity tool in decision-making allows us to make quick & error free judgement whereas automation completely removes human involvement. Both Weather prediction and driverless car involve artificial intelligence but one is automation other is productivity. Both have benefited by availability of massive computational power, richness of data Science library in Python or R as well as the massive and often real-time digital data sets available for classification & pattern recognition.

Both AI & developing intelligent productivity tools for business decision-making is going to be the next wave in IT domain and will drive innovation and jobs for the next decade. While AI might flood manufacturing, decision analytics applications will flood managerial functions.

Decision Analytics applications are wide and far-reaching for two reasons. One, every type of business function be it Finance, Marketing, Human resources, Supply chain & logistics – all need applications of intelligent productivity tools.  Two, the managerial resources are increasingly expensive and productivity tools offer attractive cost-benefit proposition which all businesses invariably like.

Therefore, if you are an engineer inclined towards business and not towards technology, then go for Decision Analytics. If you are an engineer inclined towards technology and R&D, then go for AI or Robotics.