Today’s businesses rely heavily on data. They employ data analytics methods to improve their products and services. However, this was not the scenario a few years back. Although data was important back then, the prominence of data has grown ever since intelligent and connected technologies like AI and IoT have come into the spotlight.
AI and IoT go hand in hand to create technological wonders. AI is the big brain whereas IoT is the nervous system. Together they make applications perform different operations. These operations may be complex or simple but their execution is surely fast.
The definition of AI is machine intelligence. In layman terms Artificial Intelligence enables the machines to think, analyze and process information in a similar fashion to that of humans. Although AI has not been fully developed yet. Still, AI has found its applications in a number of fields where the results are nothing short of a breakthrough.
IoT, on the other hand, is the network of interconnected devices exchanging information among themselves without the need of human interaction. This network of connected devices acts as the neural ends of the IT infra. The devices may be considered as body parts or organs of this Information Technology body.
Measuring industrial growth through AI
In today’s times, AI has helped enterprises to increase their operational speed and efficiency while simultaneously decreasing production costs. This has made the technology a reliable and highly functional advancement in whatever field it is applied. The key aspect of Artificial Intelligence is its efficiency to break down huge data sets into small informational bits. AI learns and analyzes through these data sets.
AI is also helpful in tracking and analyzing fraudulent activities beforehand. Thus it can be used for risk prevention.
AI is used to read and convert big data sets into a meaningful and structured form. Thus major industry sectors are leveraging AI in their process to yield multi-fold benefits.
How AI has changed the world?
AI has become the hottest topic in the technical field. This all started with the commencement of this decade. Although AI was around since the 80s, the post-2010 period witnessed AI getting hugely implemented and experimented with. This opened new opportunities for businesses around the world. As a result, the industries today became more data-driven than they used to be.
Also, another impact of AI has been on the authenticity of the information. With AI being implemented in most fields today, the chances of having fake or unusable data are very low.
AI, when integrated with IoT, is a fully functioning unit of its own. With high intelligence and a network of interconnected devices at its helm, the probabilities are mind-boggling.
AI has found its breakthrough applications in industries like logistics, healthcare, insurance, manufacturing, etc. Let us take a look at the changes and advancements AI has created in some of these fields.
AI in the insurance sector
The insurance sector is the most profitable sector to implement AI in its processes. The potential savings by implementing AI is estimated to be $390 billion by 2030. A major chunk of these savings comes from the front offices. The AI-driven cost savings may go up to $168 billion.
The three main aspects through which these savings can be incurred are improving customer experience, personalizing policies, and managing the insurance claim process. The first can be implemented by using AI chatbots. For personalizing policies AI can be leveraged to study huge volumes of customer data and then based on that data AI can help in formulating more personalized policies for their customers. And finally, AI can handle the management of the claim process by streamlining it.
AI in the manufacturing sector
The manufacturing sector can make the most out of AI’s aspect of increasing productivity. AI can be used for 24*7 production, thus saving labor costs. To implement AI on such a huge scale in a coordinated manner, you need the machines to interact with each other in a structured manner. This is done with the help of IoT.
Also, human labor is prone to mistakes and a small error could end up in a fatal blow for the whole manufacturing process. So using AI and machine learning instead of human labor will eliminate that risk. Also, the added benefits of using AI in the manufacturing process include fast data-driven results, reduced operational costs, optimum output, and superior scalability.
AI in logistics
Companies throughout the world have started leveraging AI in logistics. The warehouses are becoming fully automated, robots are being used to pack and stock items and the delivery routes are being updated for the quickest delivery.
Also, AI is assisting in last-minute deliveries. The management of customer data, their choice of delivery location and the ETA for the location gathers a lot of data. This amount of data is difficult to process. To counter this problem, AI is used. Also, most of this data is dynamic, so AI is the best option to process it.
How AI can change the current scenario?
According to Gartner, at least 20% of individuals of developed nations will rely on AI to assist them with tasks by 2020. So we all have witnessed what AI and IoT are capable of. The challenge lies in further exploration of their implications. Gartner also predicted that by 2022 40% of government workers would rely on AI support to make decisions and drive processes. The organizations will modify their structures to integrate AI and IoT in their segment. This makes sense as AI and IoT together can bring revolutionizing changes.
Conclusion
All these sectors have been transformed in a crucial manner after the integration of AI and IoT. and all this has happened in the last decade itself.
Although AI has grown leaps and bounds, it is still far from reaching its full potential. That being said, AI and IoT are growing at light speed. Each new day programmers are finding innovative ways to implement AI. It would be interesting to see how AI could be implemented in sectors like energy, oil, gas, and cryptocurrencies. Also, a recent study has come up with the idea of using Twitter data to identify public epidemics by using AI. Such advancements make us believe that the applications of automation and analytics are endless.