Media has created a buzz around Internet of Things and Artificial Intelligence as being applied only to niche products. The truth is that the business world has begun implementing these technologies throughout the entire enterprise schemes to improve their productivity.
Key sectors such as fleet management in transportation, inventory and warehouse management in retail as well as cybersecurity in banks are some of the areas where the Internet of Things and AI merge together.
IoT refers to the millions of physical units that are connected to the internet, sharing and collecting data. It adds a level of digital intelligence to devices allowing them to communicate without human intervention.
On the other hand, Artificial Intelligence refers to the concept of machines being able to perform tasks in a smart way. Devices engineered to act intelligently can be categorized into two major groups including applied - which involves systems designed to trade stocks or handle a vehicle - and general - which involves machine learning subsets, being able to fulfill any task. The latter is still in its very early stages.
How Can Businesses Integrate These Technologies?
To survive today’s competitive business scene, enterprises must focus on analytics to improve productivity and efficiency. Businesses which make decisions based on metrics are far more successful in gaining value from the internet connected environment than those still using traditional methods. Focusing on the IoT involves transformation, special collection and study of data and clear interpretation of various sourced information.
Transformation should take place throughout the entire organization, including technology, personnel, and operations. Great volumes of data should be sourced and studied by specialists for the best results. Using a team of data scientists, analysts and business executives is the safest strategy. The key is to combine internet connected analytics with other data provided by enterprises (CRM, sales), public data (weather, public Census) and third-party data (demographics).
The Importance of Data Science and Machine Learning
The huge volumes of data analytics provided by the Internet of Things require teams of data scientists and analysts to carry out joint study. Through machine learning (ML), patterns can be identified and used to predict human behavior, events and processes. ML reveals the information required by data scientists to understand what is happening and accurately make predictions.
To survive in the competitive business world, enterprises must encourage and develop data science abilities to design better processes and improve overall ROI. By integrating technology throughout all business-related processes, companies will return a higher value to their shareholders and improve their market position worldwide.
Wrapping It Up
In the business world, these technologies ensure that data-driven strategies are successful. Viewed as liberating forces, they offer enterprises the freedom of handling tasks that only humans can perform. At the end of the day, companies which act on data insights become the innovators and industry leaders.
Maybe you'll find this ebook interesting: