By We can see lately that artificial intelligence is now revolutionizing how modern-day businesses do data-oriented decision-making to autonomous operations. AI covers it all, and now more and more enterprises rely on AI capabilities to make more precise decision-making in business. Ai has a huge influence on data-based decision making.
AI with big data has the capability to analyze huge volumes of data and provide crucial insights to the business owners and decision-makers by providing them an overview of the bigger picture and help them make more informed decisions. Now, AI is becoming more and more capable of making decisions autonomously on its own, thereby ensuring a higher return on investment. This article will explore some real-life examples of artificial intelligence being used in decision-making in top companies.
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Some real-time use cases of artificial intelligence in decision making
Health care industry – Infravision
Image recognition and image analysis are crucial parts of machine learning, and artificial intelligence can be effectively used for diagnostic purposes in the medical sector. In this area, artificial intelligence is now helping to save lives. Cancer is one of the leading causes of death all over the world now. Radiologists use CT scans and PET scans to diagnose cancer. To make this diagnosis, radiologists need to go through various CT scans and reports. This is a very tedious and time-consuming task.
China is such a country with a limited number of radiologists to review about 1.4 billion CT scans each year, so they are now leveraging AI to fill this gap.Information developed through this can be used to train AI applications with a sequence of algorithms that make them capable of reviewing CT scans and detect early signs of lung cancer.This will further make it easier for the radiologists to use various data points from the CT scans and mix them up with AI to diagnose cancer more efficiently and accurately. This makes CA treatment more advanced and focused.
Retail sector – Teva and Jika
Maker sights application uses a product decision engine that helps the retail industry and supports decision-makers in making informed decisions.This support is extended throughout the product creation to the go-to-market process.Various teams use AI to validate product attributes at assortments and collect inputs from the target customers to product hypotheses while providing a user-friendly mobile experience. Many retailers now use Artificial Intelligence-based decision making for all their products with AI Technology. In contrast, Makersights effectively address this with a proper framework for effective decision-making in each of their product creation. Makersights site also helps the clients figure out the strategic opportunities in the market and identify issues and complications at very early stages.
Manufacturing – Volvo
The automotive industry is largely making use of AI and IoT for the last few years. Vehicles have been generating a lot of data for which they are fitted with different sensors for security purposes. Autonomous vehicles have also started their journey in the last couple of years. Volvo now effectively uses AI and IoT to uphold and maintain the safety reputation of their brand. In a recent project, Volvo fitted their cars with sensors capable of detecting and analyzing the driving conditions and monitoring the vehicle’s performance in various conditions.
The data collected is getting uploaded to the cloud, and based on further evaluation of this data using Teradata with machine learning, they can provide an early warning system. For this, the Volvo Teradata system analyzes a million events per week to predict any possibilities of failure or breakdown in their cars. Providers like RemoteDBA.com will support handling the huge volume of data securely at the backend databases.
Energy sector – BP Plc
British Oil for BP Plc is a gas and energy brand that now operates in 72 countries across the globe. It is now largely leveraging the benefits of AI and big data in all its processes. Using big data technologies and artificial intelligence, BP processes the collected data to make business decisions like improving operational efficiencies and trying cost-cutting in the needed areas. For the same, BP has installed data collection and service in their oil Wells and gas resources, which will continuously gather data and monitor the same to understand the working conditions of the oil wells at various sites irrespective of the location. Analyzing all these data will also help BP to monitor their equipment and manpower for optimum utilization.
Financial services – Underwrite.ai
Financial services are another big area that is always at the risk of fraudulence in terms of loan applications and incurred losses in order to cut short the possibility of such troubles. AI can effectively assess the credit risks for smaller businesses and consumer loan applications by analyzing various data points from the credit bureau. Using artificial intelligence and machine learning possibilities, analyzing a huge volume of personal data is made possible. Doing this will allow the provider to analyze the credit risk of each consumer and business to make an informed decision in terms of loan approval. Artificial intelligence systemuses advanced algorithms to acquire the portfolio data and find out the patterns for good and bad loan applications.
By reviewing all these real-time applications of artificial intelligence, we can see that AI is now unquestionably the future of business decision making, which has widespread coverage across the industries. It is a radical change from choosing what you need based on the circumstances to understanding what best is for each customer. AI can make decisions based on the desired output and goals of businesses and ensure the highest output.
Similarly, for all types of businesses, AI can be well aligned to their exact wants and needs and help businesses grow in whichever direction they want. However, when you plan to adopt artificial intelligence technologies, it is essential to understand your exact needs and plan the tools and strategies to be used for a better return on investment from your AI applications. That will help you make a suitable decision for your decision making.
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