In 2022, the new trends that AI will bring about is something that organizations across the world are curious about. AI development is now maturing and showing a lot of promise for businesses of all sizes. We might be witness to these trends and get to see the kind of impact that it will have on businesses and humans alike. There has been an increase in digital transformation across a variety of industries, a phenomenal change that happened faster than expected. It is expected that there will be significant innovations in these technologies in the year 2022.
Natural Language Processing:
Without a doubt, NLP is one of the most used AI technologies. Its specialty is that it comprehends human talk and reduces the necessity to type or interact with a screen. AI-powered devices can turn human languages into computer codes which can efficiently run applications and programs.
Metaverse:
It is a virtual world, just like the Internet, where people can work and interact with the help of immersive experiences. A total of $106 million was spent on virtual land in the metaverse. AI and ML will be the technologies that propel the metaverse forward. They will help enterprises create a virtual world where users will feel at home with virtual AI chatbots.
Focus Approach On localized AI/ML models:
Everyone knows that the strength of an AI/ML model is derived from the data that it is fed. With businesses relying on such models to grow, they need to be careful of the external factors which can affect the outcome that they desire. That’s exactly why businesses need to experiment with localized AI/ML models so that they have a clear understanding of the demographics that they are dealing with. The first few versions of your AI/ML model might bring in a lot of success. But when you move further, it can become much harder as the use cases will keep differing. For example, your AI model might work perfectly well in North America, but they will fail when you are looking at markets in Europe. With localization, you will be able to adjust the differences and get accurate AI/ML models.
Low-code or No-code AI:
The number of skilled AI engineers doesn’t meet the demand in the market. Organizations require engineers who can develop the necessary tools and algorithms. Thanks to low-code and no-code solutions, this issue can be addressed just by providing intuitive interfaces that can be used to create complex systems. Most of the low-code solutions have drag-and-drop modules which makes it easy to build applications. Low code based systems can be used to create smart applications with the help of pre-created modules and adding specific data into them. By using NLP and language modeling technologies, voice-based instructions can be given to complete tasks.
Use of Artificial Intelligence In Cyber Security:
With technology seeping in almost every aspect of our lives, the damage that cyber attacks cost us is even more sinister than we could possibly imagine. With each device that is added to the network, the risk only increases. Obviously there is no way to reduce the number of devices being added as it would mean that we are negatively dealing with this issue. The networks are also becoming complex with each passing day. Here is where Artificial Intelligence and Machine Learning can play a big role in tackling this issue head on. AI/ML systems have the ability to identify patterns, predict trends and see for anomalies. It can look for suspicious activity by developing smart algorithms for it. The coming years will see a lot of focus on AI/ML to combat the dangers of cyberattacks.
Workforce Augmentation:
The fear that AI will replace human jobs is something that we have been hearing for quite some time. The truth is that companies will use AI/ML to gather data, analyze, and leverage the insights to make business decisions. In such a case, it becomes even more important for businesses, employees and AI machines to work in tandem. If you look at most departments, they are already using AI and ML systems. Let it be sales, marketing or customer service, AI is already being leveraged. You will see that these AI/ML systems have only increased the effectiveness of each of the departments. In manufacturing industries, AI systems are used right from predicting sales to forecasting inventory. Technology companies are using AI/ML to increase the effectiveness of its software. Each industry has multiple use cases when it comes to AI.
Conversational AI chatbot:
There has been no technology which has revolutionized the way in which conversational AI chatbot has affected customer support. Conversational chatbot solutions are AI-powered virtual assistants which do rule-based operations and also carry on natural conversation. From doing mundane tasks such as responding to queries, resetting passwords, etc., to understanding human queries, the dent it has created is immeasurable. By almost replacing customer support agents, it has reduced the operational costs of businesses by a huge margin.
Hyper Automation:
Organizations will leverage AI and ML technologies to automate a number of processes which would entail large volumes of information and data. You will see an increase in the rate of automation in multiple industries using robotic process automation and intelligent business process management software.
More focus on AI ethics:
There has been a spurt in AI use cases across almost every industry that you could possibly imagine, in the last few years. Although the technologies are incredibly beneficial for mankind, the potential risks cannot be discounted. We will see a bigger focus on AI ethics in the coming few years as things could go awfully wrong if there is no deliberate intent to use these technologies only for the good. Even a technology as useful as facial recognition can be used to create a police state. Companies which have integrated AI into their business processes will find the most success with it, as opposed to one that goes with the flow.
Quantum AI:
It is the use of quantum computing for computation of machine learning algorithms to achieve results which is not possible on a traditional computer. Although there has been incredible progress in AI in the last few years, it is still limited by technological challenges. With quantum computing, the obstacles to achieve Artificial General Intelligence (AGI) can be eliminated. An AI that is powered by quantum computing can complete years of analysis in a short period of time.
The above AI trends will soon make a dent in the business world. AI is a transformative technology that will only keep improving with time and help organizations achieve their business objectives by assisting in building innovative solutions for products and services.
