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Data is the foundation of every business, allowing us to make improved decision-making to know more about the customers. However, the volume of data in our hands poses a challenge for human brains to process effectively. That is where Artificial Intelligence (AI) Decision Making comes into play.
In this blog, we’ll learn how companies can use Artificial Intelligence in Decision Making to generate quicker, more precise, and consistent decisions in their workspace. Unlike humans, AI can process large amounts of data without mistakes. It allows your team to focus more time on other tasks. It also provides an upper hand in the business field.
Table of Contents
1) What is Artificial Intelligence?
2) Types of Artificial Intelligence
3) What is Artificial Intelligence Decision Making?
4) How does AI influence Decision Making?
5) Benefits: Artificial Intelligence & Decision Making
6) Examples of Artificial Intelligence in Decision Making
7) Conclusion
What is Artificial Intelligence?
Artificial Intelligence, popularly known as AI, is a branch of modern computer science. In simpler terms, it is nothing but making machines think like human beings. It imparts human behaviours such as analysing, problem-solving, reasoning, learning, etc. It has been one of the most discussed topics in the past few years, and there is definitely a reason why it is in the spotlight.
Types of Artificial Intelligence
There are basically three types of AI based on their intensity to work like a human. Given below are the three broad categories of AI.
Artificial Narrow Intelligence (ANI)
ANI Is also known as weak AI. It has limited performance capabilities compared to human intelligence. It does not have the ability to fully carry out human intelligence but operates within a restricted scope. Some of the tasks it can carry out include facial recognition, speech recognition, natural language understanding, etc.
Artificial General Intelligence (AGI)
AGI, also known as strong or deep AI, can mimic human intelligence and behaviour. It has the power to learn autonomously and apply its intelligence to solve complex problems. The ultimate goal of AGI is to enable machines to impart human-like thinking and behaviour to improve their understanding of human emotions. However, achieving this level is still a work in progress.
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Artificial Super Intelligence (ASI)
Many see this concept as a fantasy rather than a reality, ASI would grant machines superiority over humans, and it also involves injecting machines with emotions, beliefs, and desires. It elevates AI to a level far beyond what we currently experience. However, it's essential to understand that these notions are still largely theoretical and speculative in nature.
What is Artificial Intelligence Decision Making?
AI Decision Making involves using AI platforms to analyse and process data. It provides more accurate predictions and recommendations compared to alternate traditional methods. Tasks such as data analysis, trend identification, anomaly detection, and complex evaluations can be efficiently carried out. There are various degrees at which decision-making takes place:
Decision support
Decision support is the starting level of AI-human interaction, which involves gathering algorithms and presenting analytical insights from databases. Human employees make the final decisions using their experience and common sense.
Decision augmentation
In decision augmentation, AI goes a step further and provides various decision options based on the gathered data. Employee experience becomes less critical as the machine takes responsibility for the final decision-making process.
Decision automation
In decision-automation, AI entirely takes over daily tasks, allowing employees to focus more on human involved activities. This approach makes sure that consistent decision-making happens while allowing human resources to focus on higher-value tasks.
How does AI influence in Decision Making?
Artificial intelligence has become everything in modern businesses due to its remarkable learning capabilities. By processing large amounts of data, AI brings more informed and data-driven decisions to the table. One of AI's strengths is its ability to train itself and create models based on data collection. It leads to more precise decision-making.
Prominent companies like Amazon have made use of the power of AI by utilising customer transaction data. This approach allows businesses to gain insights into customer interests and identify patterns of products frequently purchased together. AI-powered recommendation systems are used on websites to offer complementary products, enhancing the customer experience and boosting sales.
In the past, humans would analyse data to identify target customers and determine product launch costs. However, with the integration of AI, businesses can now make smarter, data-driven decisions, reducing risks and making way for new growth opportunities.
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Benefits of Artificial Intelligence & Decision-Making
Today, AI is becoming an irreplaceable force that is responsible for almost everything, be it a breakthrough in medicinal research or an innovation in technology. Here are a few benefits of Artificial Intelligence:
a) It improves businesses in making decisions quickly and precisely by analysis of large data.
b) AI-driven decision-making applications, such as Natural Learning Process, enable businesses to understand customer interactions with different brands, tones, and the tone customer would like.
c) AI tools, including machine learning algorithms and chatbots, provide key insights into customer satisfaction and expectations.
d) AI's ability to interpret real data sets proves invaluable, especially in situations where the desired outcomes are well-defined and measurable.
Examples of Artificial Intelligence in Decision Making
The latest advancement in AI has enabled it to autonomously make decisions on behalf of businesses, with the primary objective of maximising Return on Investment (ROI). Here’s a list of examples of AI in Decision Making.
Teva and Hoka
MakerSights uses a product decision engine in the retail sector, which helps to make well-informed decision-making from product creation to market launch. Teva and Hoka utilise it to gather customer input to test product hypotheses. The platform's mobile user experience enhances usability.
MakerSight empowers Teva and Hoka with an improved decision-making framework, identifying opportunities and resolution of issues throughout the product creation process.
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Volvo
In recent years, the automotive industry has utilised AI to improve vehicle safety and performance. With the growing number of sensors integrated into vehicles, including autonomous ones, the amount of data being generated has increased exponentially.
Volvo, renowned for its commitment to safety, started using AI in 2015. They equipped 1,000 cars with sensors to monitor driving conditions and analyse vehicle performance. The data gathered from these sensors is then sent to Volvo's cloud infrastructure.
One of their notable achievements is the implementation of an early warning system that looks at over a million events weekly. This system predicts potential breakdowns and failures in Volvo cars, thereby upholding their safety reputation.
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Infervision
AI-powered image recognition and analysis are transforming cancer diagnosis in healthcare. With cancer becoming a leading cause of death, the demand for efficient diagnostic methods is crucial. However, the overwhelming number of CT scans and a shortage of radiologists create challenges.
Infervision's AI system offers a solution by analysing CT scans for early signs of lung cancer. This technology makes radiologists' workflow much easier. It reduces fatigue-related errors as the ratio of doctors to scans is unbalanced. It also ensures more accurate and efficient cancer diagnoses.
With the help of AI, healthcare professionals can thus make informed decisions. It leads to earlier detection and improved treatment which can save more lives in the fight against cancer.
BP plc
BP plc is a British oil giant operating in more than 70 countries worldwide. It uses AI to monitor the working conditions of its gas and oil reservoirs. They have installed censors at each site, which helps them collect valuable data.
The data includes various things such as temperature, gas, humidity, and vibration from oil and gas wells. It helps them to make strategic plans to improve business efficiency. It reduces operational costs and improves the quality of production.
Using AI thus helps them keep track of their performance and enables smooth working conditions for the employees. AI thus helps them meet to tackle the challenges their global competitors pose.
Conclusion
AI Technology revolutionised the decision-making process for both businesses and consumers. For businesses, setting AI with their growth objectives is very important. Doing so can achieve the best possible return on investment (ROI) for the business. Through its data-driven results and faster capabilities, AI can pass through complex situations and identify opportunities humans may fail to observe. This can lead to improved efficiency and maintain profit for your organisation.
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