The summer has officially begun in most parts of the world and we are almost halfway through the year. It’s time to take a pause and reflect on mid-year emerging trends and focus areas. In this edition of IoT Curator, we bring you three such reports/articles focusing on trends in 2018.

Gartner Magic Quadrant for Industrial IoT Platforms

The most awaited analyst report – Gartner Magic Quadrant for Industrial IoT Platforms is officially released. Gartner Magic Quadrant report is a culmination of research in a specific market, giving you a wide-angle view of the relative positions of the market’s competitors. By applying a graphical treatment and a uniform set of evaluation criteria, a Magic Quadrant helps you quickly ascertain how well technology providers are executing their stated visions and how well they are performing against Gartner’s market view. Companies and decision makers may use Gartner Magic Quadrant as a first step to understanding the technology providers they might consider for a specific investment opportunity. This is an inaugural report for Industrial IoT. It has recognized 11 companies in this report based on their ability to execute and completeness of their vision. This is a must read report if you are evaluating IoT Platforms or vendors to work with.

Trends in Digital Transformation for 2018

Yes, we are almost halfway through 2018 and certain trends are emerging prominently. Greg Gorbach of ARC Advisory identifies some of the key trends in digital transformation. Along with Advanced Analytics, Machine learning, Edge and Fog, Smart operations, Asset Performance Management as focus areas, the article shades light on Additive Manufacturing, Smart Environment, Product As a Service, and other trends as emerging areas.

AI, IoT, and Blockchain

Similar to trends in 2018, the primary focus areas emerging for the enterprise are AI, IoT, and Blockchain, according to the interesting study quoted in this Forbes article. It further highlights that IoT connected devices often generate large amounts of data necessary to train machine learning models.  Of the companies surveyed, more have IoT workflows already in production than AI. This is because a stable IoT and edge computing foundation are often prerequisites for enterprises to break ground on a machine learning model in the first place. This is a good read if you are thinking of AI investment in your enterprise. Please do share your feedback on the articles curated or if you have any interesting article to share with us.