3 Major Sectors That are Increasing Their Use of AI

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AI and machine learning are definitely the future of the global economy. Increasingly, significant businesses and sectors are in the process of actualizing complex machine learning and artificial intelligence systems for a range of applications, not least because of the multitude of easily understandable and adaptable programming languages able to facilitate intelligent systems. 

AI has been available since the 1950s. However, improvements to systems over the decades and educated programmers that can increase and understand functionality have facilitated an expansive global shift towards rapid AI implementation. As a result, AI spending is projected to reach almost $80 billion by 2022.

Logistics and Transport

Machine learning and AI have been used in the transportation and logistics industry to analyze supply and demand chains and now even route planning. As we’ve seen with services such as Last mile delivery software, advancements in real-time technologies operating on a multidisciplinary and interoperational technology system streamlines operations. Improvements to existing applications alongside new applications are now possible.

Some features are potentially beneficial to significant chains and leading independent insurance brokers alike as AI and ML integrate to predict vehicle maintenance issues, avoid congested areas and effectively navigate automated driverless vehicles. For example, artificial neurons can manage and operate vehicles better and at a level far quicker than a human brain. 

Healthcare Services

Currently, 90% of US hospitals use AI as a part of their crucial infrastructure. The automation features of AI systems such as SAGE allows hospitals to streamline vital operations and improve broken healthcare processes. However, AI and ML in hospitals are currently operating on a quasi-trial basis, yet the benefits are becoming apparent.

The practical applications of AI in the medical field have been widely known and implemented for years. Fundamental medical AI systems help physicians record notes, analyze data, and enter data into record systems. Advanced systems utilize data sets to diagnose, treat and predict results in a medical setting.

e-Commerce and Retail

One of the more practical applications of AI is in the retail industry. Big data drives AI systems in e-commerce, currently accounting for 35% of online sales. Retailers like Amazon utilize AI for customer recommendations based on previously analyzed data. Upselling and cross-selling are also made possible by implementing intrinsic AI systems that are part of the infrastructure as a whole.

AI in commerce doesn’t only relate to sales. Chatbots and AI-driven interfaces are becoming increasingly popular. Customers can raise queries using ChatBot systems, but bots are also becoming more popular as a promotional method. Bots can recommend purchases via an online store interface, and it is predicted that by the end of 2021, 80% of all human interactions at an online store will be managed by AI systems.

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The vast implementation of AI systems has increased spending to $80 billion per year, while improvements to systems, ease-of-use, and educated programmers have facilitated the shift towards major AI infrastructure. As a result, various industries such as transport and logistics, medicine, and retail benefit from these systems.

The prediction models of AI and ML efficiently integrate into transport, where data can be used to analyze insurance-focused aspects such as vehicle maintenance, diver automation, and collision reduction.

Process automation AI is helping doctors and hospitals all over the world streamline their operations, with 90% of hospitals in the US adopting automated systems for data analysis and patient access where data is analyzed for predicting and diagnosing illnesses.

It is now estimated that 80% of online retail interactions are handled by ChatBots. AI systems in retail are at such an advanced level that they can operate a storefront, and data analysis allows suggestions to be made to previous customers in addition to upselling and cross-selling.