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Examples of Artificial Intelligence in Decision Making

AI is analyzing mammoth amounts of data and providing critical insights to the business owners to provide them with a larger picture, with the help of which they can make informed decisions.


Artificial Intelligence in Decision Making
Published By - Kelsey Taylor

Artificial Intelligence is revolutionizing the way we conduct business. From data-based decision making to autonomous operations, we have it all. All this is filtering down to enterprises relying heavily on AI, and that brings us to decision making in businesses. AI has a massive influence in this regard with data-based decision making.

AI is analyzing mammoth amounts of data and providing critical insights to the business owners to provide them with a larger picture, with the help of which they can make informed decisions. But now AI has become capable of making decisions for businesses autonomously to achieve the highest ROI.

Top 5 Examples Where Artificial Intelligence Was Used For Decision Making

Infervision – Healthcare

Image recognition and analysis, an essential part of AI and machine learning, can be used for diagnostic purposes in healthcare, thereby saving lives. Cancer is becoming one of the leading causes of death in recent years. Radiologists use CT scans for the diagnosis of cancer. The radiologists have to go through numerous CT scans every day for the diagnosis. It sure is a time-consuming and tedious task.

China, which is lacking radiologists to review over 1.4 billion CT scans every year, is looking towards AI to fill this gap to some extent. With the ratio of doctors to scans being incorrectly balanced, overworking healthcare professionals might suffer from fatigue, which can in-turn cause errors.

Infervision has developed an AI and trained with suitable algorithms to review the CT scans and detect any early signs of lung cancer. It makes the job easier for radiologists because they can simply use the data from the AI and can diagnose for cancer more accurately and efficiently, treating it that much more effectively.

Teva and Hoka – Retail

MakerSights use product decision engine for retail and supports informed decision-making throughout the product creation and go-to-market process. Teams use it to validate assortments, product attributes quickly, and collect input from target customers for a product hypothesis while providing an excellent mobile user experience.

Teva and Hoka use MakerSights for AI-based decision making for their products. With AI-driven technology, MarkerSight enables Teva and Hoka with a proper decision framework for every product creation process step. It also helps them with figuring out strategic opportunities and determining issues and complications beforehand.

Volvo – Manufacturing

The automotive industry has been making good use of IoT and AI in recent years. Vehicles, in general, have been generating more and more data as they are fitted with an increasing number of sensors for security purposes. Also, autonomous vehicles generate even more data.

Volvo uses IoT and AI to uphold and maintain its safety reputation. In a project launched in 2015, Volvo fitted 1,000 cars with sensors to detect and analyze driving conditions and to monitor the vehicle’s performance in hazardous conditions.

The collected data is then uploaded to their cloud. Volvo works on this data with Teradata for carrying out machine-learning driven analysis across its collected data. Volvo’s early warning system analyzes over a million events per week to predict breakdown and failure in their cars.

BP plc – Energy

BP plc, the British oil and gas giant that operates in 72 countries worldwide and has been leading the industry, leverages the benefits of big data and AI in its processes.

BP has installed sensors in its gas and oil wells, which continuously collect data to monitor and understand the working conditions of the well at each site irrespective of the physical location. Analyzing this data helps BP monitor and optimize the performance of their equipment and keep a tab on their maintenance needs to enable smooth and unhindered functioning.

The sensors installed collects data about aspects such as chemicals, temperature, gas, humidity, vibration, and more from the oil and gas wells. With the help of big data technologies and AI, the collected data is then processed for making business decisions such as improving operational efficiencies and cost-saving.

Underwrite.ai – Financial Services

Financial services are always at a risk of accepting fraudulent loan applications and enduring losses. To cut back on such losses, Underwrite.ai accesses credit risk for small business and consumer loan applications by analyzing numerous data points from credit bureau data sources.

This allows them to access credit risk for individual consumers. Their system applies advanced artificial intelligence algorithms to acquire portfolio data to find patterns for good and bad loan applications.

Conclusion

AI is unquestionably the future of decision making for businesses and consumers alike. It has been a radical change from choosing what we need according to circumstances, and AI selects what is best for us.

Similarly, for businesses, all AI has to do is be aligned to where you want your business to grow and what you want to be done. AI will make decisions based on the desired output to bring you the highest ROI possible for your business.


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