The process of digitalization is taking the world by storm, and it’s only possible due to revolutionary advances made in artificial intelligence and machine learning. AI and ML solutions are finding an application in most industries and business practices, with a trend that keeps growing rapidly every year.
By TOMAS MCKENNIE
Of course, introducing new technologies into existing systems comes with its own set of challenges. However, the benefits outweigh the risks, so businesses of all sizes are starting to adopt this new technology. Let’s see how AI and ML improve business operations and why they are so popular.
Development of AI and ML Models Focus On Hyper Automation
Automation has already been a part of most manufacturing processes for decades. Hyper Automation, on the other hand, is the push towards automating most business processes. As AI models become smarter, they can complete more tasks. Companies are constantly looking for new areas where they can apply AI.
The need for complete automation became obvious during the COVID-19 pandemic, as most businesses had to move from traditional operations to a digital environment. That’s why hyper-automation is also known as digital process automation.
Of course, the practice rests on AI and ML as the key components. When coupled with robots and other automation tools, AI and ML can provide some truly incredible results. However, hyper-automation comes with all kinds of challenges. For example, as new technologies get introduced, they affect automated processes, completely changing the logic in the process. Automated businesses have to develop new models in an ever-changing environment. That often proves to be too expensive and time-consuming.
Engineers and AI developers found a solution for that as well. They use advanced AI, ML, and deep learning models to speed up the learning process. With the use of advanced learning algorithms, new AI and ML models can learn from new processes automatically. The practice is still in its early stages, but it will soon become the norm among AI systems everywhere.
Optimizing AI Development Through AI Engineering
As mentioned above, AI solutions are finding their way into most aspects of everyday life. From online search engines to optimizing production lines, AI already proved that it can find and solve various problems.
However, developing a new AI solution takes a lot of time, money, and effort. Even so, only about 53% of all AI projects get to see the light of day. Businesses find it hard to develop AI and ML models that fit with their existing infrastructure as well as business goals. The constant back and forth between the developers and other departments leads to errors and complications that often exceed planned budgets.
Most AI models are designed to improve performance, provide scalability, and management. However, most models struggle to provide all of these features. That’s why developers started using AI to train and engineer new AI solutions.
The process of AI engineering makes more sense because it incorporates all elements into one. In other words, projects don’t have to go from one department to another. AI engineering takes care of all DataOps, DevOps, and ModelOps automatically. That eventually leads to faster development and leading to better results.
Correlation Between AI/ML and IoT
IoT stands for the Internet of Things, and it’s one of the fastest-growing technologies in the past decade. The current estimations say that the IoT market will grow to $1.5 trillion by 2030. That shouldn’t be a surprise when you consider the immense power and capabilities this technology provides.
If you still don’t know, IoT technology uses small sensors installed on all devices and assets within a system. These sensors monitor individual devices and send performance data to an AI/ML system that learns how everything works. Once it has enough data, the AI can find bottlenecks, and other operational issues. Once it has all the information, it can propose solutions to improve efficiency and productivity. There is no IoT without AI and ML.
The system is designed perfectly. AI and ML need a ton of data to improve accuracy, and IoT constantly generates huge amounts of information. When put together, these technologies can provide incredible insights used to improve operations on many different levels.
This technology has an application in industrial settings and manufacturing industries. IoT sensors are installed across entire production lines to collect performance data through real-time monitoring. The data is sent to the AI system that analyzes everything and provides solutions that improve production and efficiency. These massive amounts of data can be used for other revolutionary practices, such as predictive maintenance. A company called Wizata-industrial manufacturing software is one of the leading names in this area, and their AI solutions are already redefining manufacturing practices in industries all over the globe.
AI for Cybersecurity
Cybersecurity is one of the areas where AI and ML proved extremely useful. As cybersecurity becomes tighter, cybercriminals have to develop new ways of breaching systems. No matter how hard businesses try to keep them out, hackers always find ways of stealing sensitive information. Since most cyberattacks are caused by human error, it only makes sense to use AI and ML to minimize threats.
AI cybersecurity solutions are introducing techniques that were never used before. Instead of acting like a shield between internal systems and the internet, AI collects data from all networks and monitors all activities. That way, it can identify many more threats than standard firewalls to minimize the chances of data breaches.
Home security systems are also changing rapidly. AI found an application there too. For example, smart homes use AI-managed systems for video camera monitoring and remote management. However, new AI solutions will be able to learn the habits and preferences of occupants, making it easier to recognize intruders when no one is home.
Ethical Concerns About AI Use
As AI becomes a normal part of many processes around us, there’s always a question of where to draw the line. Who can use AI-powered facial recognition technology? Should it be only used by the police, or should it become available for commercial use? These are just some of the issues bothering millions of people around the globe.
The truth is that AI can be abused and used to manipulate people. You must have heard about deep fake software that can create realistically fake videos. But that’s the least of our worries. Imagine the types of AI already used by governments to spy on people. Businesses also use AI to improve relationships with customers and boost marketing efforts.
Lastly, where will the word end up if AI takes over all processes around us? Human workers will become obsolete, which will lead to many new problems in the future. That’s why countries and governments everywhere are creating new laws and regulations about the use of AI. We need more transparency about the use of AI and ML models in everyday life. Until that is achieved, the question of ethics and AI will stay prevalent.
AI is one of the most revolutionary technologies the world has ever seen. However, its capabilities and applications are so immense, it’s quickly taking over business processes across most industries. It’s a powerful technology that can do a lot of good or a lot of damage in the right hands.
There is no doubt that the world needs AI to improve, but the line between a useful tool and a scary thing from sci-fi movies is becoming increasingly thinner. We can only hope that new laws and regulations will define the legal use of AI and prevent it from taking away our privacy and freedom.