Digital transformation is common in today's high-pressure world.
We all know that Artificial Intelligence (AI) and Machine Learning (ML) are buzzwords these days. But what do they actually mean? And how can businesses use them to improve their operations? In this article, we'll explore some of the most common use cases of AI & ML and Artificial Intelligence & Machine Learning business applications so that you can get a better understanding of how these technologies can be applied in the real world. But before diving deep into the topic, let's first see, if AI and ML are the same.
Are AI and ML the same?
Machine Learning and Artificial Intelligence are interconnected and closely related. Due to their interdependence, contrasting AI and Machine Learning mean really comparing how they interact to one another. Despite their similarities, Artificial Intelligence and Machine Learning are not the same. Machine Learning is a component of Artificial Intelligence.
What is Artificial Intelligence?
A subfield of computer science called Artificial Intelligence (AI) focuses on building intelligent agents—systems that can think, learn, and act on their own—and is concerned with the development of such agents. How to build machines that are capable of intelligent behavior is a topic of AI study. AI is considerably more about the process, the ability for superhuman thought, and the data processing than it is about any particular format or purpose.
What is Machine Learning?
Machine learning is an application of AI. Using data instead of explicit programming, computers can be taught to learn using this technique. This makes it possible for a computer system to keep picking up new skills and getting better as it goes along. Machine Learning algorithms have been used in a variety of tasks, including facial recognition, speech recognition, and detecting fraud.
AI & ML Use Cases
Businesses across various sectors are developing applications that benefit from the interrelationship between Artificial Intelligence and Machine Learning. Here are just a few examples of how AI and ML are assisting businesses in modernizing their operations and goods. So let's look at some real-world use cases and examples of how AI and ML are currently changing various industries:
Healthcare
AI/ML in healthcare is increasing clinical effectiveness, enhancing diagnosis speed and accuracy, and enhancing patient outcomes. With the use of AI and ML, applications like image processing for more accurate cancer detection and predictive analytics for genomes study are more easily possible.
Automobiles
The development of driverless vehicles is based on Artificial Intelligence. AI can be used to control the car in addition to its cameras, radar, cloud services, GPS, and control signals. AI has the potential to enhance the in-car experience and offer new features such as emergency braking, blind-spot detection and driver-assisted steering.
Finance and banking
The financial services sector is utilizing AI and ML to modernize and enhance its offerings, notably to personalize customer service, enhance risk assessments, and more effectively spot fraud and money laundering.
Agriculture
Artificial Intelligence is used to identify flaws and nutritional deficiencies in the soil. AI can determine where weeds are growing by using computer vision, robotics, and Machine Learning technologies. AI bots can pick crops more quickly and in greater quantities than human employees.
Cybersecurity
AI and ML are effective cybersecurity tools that aid firms in safeguarding both themselves and their clients by spotting irregularities.
Sales and marketing
For personalized offers, campaign optimization, sales forecasting, sentiment analysis, and customer churn prediction, sales and marketing teams employ AI and ML.
Energy
The energy sector already makes use of AI/ML to build intelligent power plants, optimize costs and consumption, create models for preventative maintenance, improve field operations and safety, and enhance energy trading.
These are some of the real-life applications of Artificial Intelligence and Machine Learning that we have covered in this article. There are hundreds of thousands of other AI/ML applications that we cannot cover in one article.
Conclusion
While it is obvious that AI/ML is a profoundly disruptive technology that can add significantly to any sector, getting started can be a bit intimidating. Hope this article gives an initial start in AI/ML.
As this technology advances, the world will witness brand-new businesses, and a wide range of consumer applications, displacing some employment and creating completely new ones. Although its impacts are still unknown, Artificial Intelligence and the Internet of Things have the potential to disrupt the economy dramatically.
