From novelty to necessity, Machine Learning (ML) and Artificial Intelligence (AI) have come a long way. According to GlobeNewswire, the global machine learning market value is projected to climb from $8 billion in 2019 to $11.7 billion by 2027 at a CAGR of 39%. Furthermore, according to Businesswire, 91.5% of leading businesses have ongoing investments in AI. Given this massive adoption of AI and ML by businesses, it is very hard to find a sector where they are not proving to be an asset nowadays.
Manufacturing
The AI/ML market size in the manufacturing sector is expected to go beyond $2 billion by 2025, with an average annual growth of more than 40% from 2019.
Healthcare
The global AI/ML market size in the healthcare sector is projected to touch $120 billion by 2028, at a CAGPR of 41.8% between 2021-2028.
Business
48% of companies use ML, Data analysis, AI tools internally. 86% of CEOs say that AI is the mainstream technology in their office in 2021.
It is evident from such widespread adoption of ML and AI that life in the twenty-first century now depends greatly on these two interlinked technologies. And with all that they are doing for us, it is valid to ask ourselves—what’s next for AI and ML?
So today, let us look into the future and find out how ML and AI will transform business in 2022. In the aftermath of the covid pandemic, we need a swift recovery to normalcy. And AI and ML are vital for that to happen. So given below is a list of the top 6 AI/ML trends that will change the way business drastically in 2022.
AI/ML Enhancing Hyper-Automation
For the uninitiated, hyper-automation is the extension of the traditional automation process. With the help of tools like AI, ML, robotic process automation (RPA), etc., hyper-automation takes automation beyond the scope of individual processes and can virtually automate any repetitive task in a business. It can even automate automation by detecting repetitive tasks and creating bots that can automate them. Hyper automation is the next logical evolutionary level for automation, and AI/ML is at its core.
Businesses deal with a lot of data these days. Data science helps these businesses in studying their data and mine crucial insights. Given the market’s competitive nature, most industries are using data science and, by extension, hyper-automation to mine the data.
Hyper automation also helps companies provide better customer support, improve employee productivity, and integrate internal systems.
The idea behind hyper-automation is to use the right tools to simplify, design, and create automation for processes across an organization instead of script-based automation for every process. The top tools that will drive hyper-automation forward are,
Artificial Intelligence
Machine Learning
Robotic Process Automation
Cognitive Process Automation
AI/ML will Improve Cybersecurity
AI and ML are great tools in the right hands. But in the wrong hands, they are agents of destruction. Hackers and scammers online are developing complex AI and ML governed malware and botnets and it is becoming almost impossible for businesses to counter them using traditional cybersecurity methods.
Fighting fire with fire, businesses are now increasingly using ML/AI to beef up their cybersecurity efforts. By studying past data, AI and ML can detect anomalies in a network, thus revealing possible threats. They can also detect fraud patterns which allows businesses to safeguard their infrastructure before the attack comes.
Email spam filtering is also something AI and ML help companies with. By looking for the tell-tale signs of spam, AI and ML filter out all the suspicious emails, thus making sure that you don’t open one by mistake and fall prey to a cyberattack.
Not all cyber threats come from the outside or with malicious intents. Sometimes, a simple oversight can lead to the biggest cyber threats. Data leak is a very real problem in the twenty-first century. With streams of data flowing in every way, it is very common for sensitive information to be leaked. AI and ML detection can sift through text and non-text documents and, using trained classifiers, check if a certain document contains sensitive information.
AI and ML will Make IoT Smarter
In the digital age, everything is online. From our computers, TVs to our coffee makers, everything is internet-enabled these days. An ecosystem of such internet-enabled things/appliances is called the Internet of Things (IoT). But it is not as simple as it sounds. A true IoT is a network/mesh in which data flows among the connected devices. For instance, data can be observed by a CCTV camera that goes to the server where AI detects suspicious behavior and sends the instruction to the alarm system to start ringing or the door to get locked.
As you can probably tell by the above example, in IoT, AI/ML sits in the middle, computing the data and sending instructions to the various nodes. It can be a central intelligence or a leaner, node-level intelligence in the smart devices themselves.
AI/ML, when merged with IoT, enhances:
Wearables
Nowadays, smartwatches, health trackers, wireless earbuds, etc., all use at least some level of AI/ML implementation that makes them useful for people.
Smart Factories
Using AI and ML, sensors can keep the temperature in control. IIoT can also help in production and supply chain processes.
Smart Home
All the internet-enabled devices inside a house, from TVs to thermostats and ACs, can all be controlled using a central interface with AI/ML implementation.
Smart Cities
These are larger implementations of IoT in which the entire city is connected. AIoT can help in creating safer cities with implementations like smart grids, smart public transportation, etc.
AI/ML Ethics Come into Spotlight
Given the meteoric rise and adoption of AI and ML, it is becoming increasingly important for the industry to focus on AI Ethics. In the simplest terms, AI ethics is the moral framework by which AI is used and implemented. It is a policy statement that governs the stakeholders when faced with an ethical conundrum about the use of their artificial intelligence or what it should and shouldn’t do.
AI systems are developed to mimic or replace human intelligence and are governed by tremendous data. But when the data is incorrect, or there are no ethical parameters involved, AI can be downright catastrophic. Due to the way it has been put together, an AI can simply break down ethical complexities of situations to logical and illogical actions, thinking that it is mimicking what a human would do in the same position. But being emotional and infinitely complex beings that we are, humans are also programmed to show compassion, understand nuance, and not see the world through a lens of logic all the time.
More than the AI programs themselves, AI ethics are meant for the people creating them. They are a set of rules as to what their AIs can and can’t do. Many attempts have been made throughout the history of AI to make sure that robots never become a Sci-Fi novel or movie-level threat to humanity. Even before AI was a real thing, Isaac Asimov, the science fiction writer, anticipated the dangers of an unchecked and infinitely powerful AI and came up with The Three Laws of Robotics:
Seeing how AI/ML are beginning to embed themselves in our daily lives, it is vital that industries pay close attention to their AI ethics to prevent any disaster from happening.
Augmented Intelligence Revolution
What happens when you take human cognitive powers and couple them with the logical prowess of AI? You get Augmented Intelligence.
Augmented Intelligence is one of the top machine learning trends. It is a fusion of humans and machines to improve the cognitive performance of a system like learning, decision making, and new experiences.
Augmented intelligence helps businesses in solving problems that neither humans nor AI can solve alone. For instance, with the help of AI-augmented automation, IT teams can position themselves to have better partnerships with peripheral business units. According to Gartner, 40% of I&O teams will use AI-augmented automation in big companies to achieve better IT productivity.
Business Analysis and Forecasting
AI and ML are of great help for businesses when it comes to studying their vast seas of data and finding trends and useful insights. Many companies are already employing AI and Ml to help their in-house data scientists get a better pool of trends to work with. But in 2022, we can expect some major shift in how AI and ML enable companies. AI and ML can forecast the coming surge or drop in demand for a particular product using historical data.
Moreover, by studying the current and past market conditions, AI and ML can help companies better prepare for a recession or a boom. Using these forecasts, companies can make the necessary changes to their business and market strategies to ensure that they are ready for whatever comes their way.
Conclusion
AI and ML technologies have changed our world in more than one way. Nowadays, it is almost impossible to imagine life in the twenty-first century without them. From businesses to personal health, AI and ML have done a lot of good and have enabled us in many ways. And given above are just six ways in which AI and ML will shape our 2022. The AI and ML revolution is far from over, and the coming year will prove just that and it is not too late for those businesses who didn’t jump on the trend right away. AI and ML are just entering their adolescence and there is still a lot to come and promises to be fulfilled.
If you are looking to start your own AI/ML journey and take your business to new heights of efficiency, productivity, and customer satisfaction, then contact Matellio. We have years of experience in digitizing companies inside out with the flawless implementation of AI and ML technologies.
