Data science

Top 10 Artificial Intelligence Trends and Predictions For 2022

By 2022, top artificial intelligence (AI) trends will boost the technology-driven industry.
Artificial intelligence is transforming the tech sector by assisting organizations in achieving their objectives, making important choices, and developing novel goods and services. Companies are expected to have 35 artificial intelligence initiatives in their businesses by 2022. The AI and machine learning industry are expected to expand at a CAGR of 44% to US$9 billion by 2022. Several advancements in AI and machine learning technology have occurred in recent years. In this article, we will discuss some of the most important AI trends for 2022.

 

AI’s Expanded Role in Hyper Automation
Hyper automation is the process of automating operations utilizing sophisticated technology. Digital process automation and intelligent process automation are other terms for the same thing. Robotic process automation (RPA), artificial intelligence (AI), machine learning (ML), cognitive process automation, and intelligent business process management software are some of the advanced technologies commonly utilized in hyper-automation (iBPMS). Companies may use conversational AI and RPA to react to client inquiries automatically and enhance their CSAT score. Companies can minimize employee manual labor and boost productivity by automating time-consuming procedures. Hyper automation allows companies to integrate digital technology into their processes. Hyper automation is one of the finest AI trends.

 

Artificial Intelligence (AI) in Cybersecurity
Information security is increasingly reliant on AI technologies. Organizations are creating new techniques to make cybersecurity more automated and risk-free with the aid of AI. AI is assisting businesses in enhancing their cloud migration plan and enhancing the effectiveness of big data technologies. By 2026, the market for AI and machine learning in cybersecurity is expected to reach US$38.2 billion. Cybersecurity entails a large number of data points. As a result, AI may be utilized in cybersecurity to cluster, categorize, analyze, and filter data. AI helps you correlate multiple data sets and search for risks by organizing data in a certain manner. By establishing a security platform that scans massive quantities of data, you can identify malware and threats using AL and ML.

 

Forecasting and analysis of the business
Business forecasting and analysis using AI and ML have shown to be far more straightforward than any prior approach or technology. You may consider thousands of matrices using AI and ML to generate more accurate predictions and forecasts. Fintech businesses, for example, are using AI to anticipate demand for multiple currencies in real-time based on market circumstances and customer behavior. It aids Fintech firms in having the correct quantity of supply to satisfy demand.

 

The Evolution of Augmented Intelligence
One of the popular AI trends is Augmented Intelligence. The combination of robots and humans to improve cognitive performance is known as augmented intelligence. According to Gartner, 40% of infrastructure and operations teams will utilize AI-augmented automation to boost IT efficiency by 2023. In fact, by 2022, the contribution of digital employees will have increased by 50%. Platforms with augmented intelligence may collect all sorts of data, both structured and unstructured, from multiple sources and show it in a 360-degree picture of consumers. Financial services, healthcare, retail, and travel are all examples of industries where augmented intelligence is becoming more prevalent.

 

The intersection of AI and ML with the Internet of Things (IoT)
Artificial intelligence (AI) and machine learning (ML) are rapidly being used to make IoT devices and services smarter and more secure. According to Gartner, by 2022, over 80% of IoT initiatives in companies will use AI and ML. The Internet of Things entails connecting all of your gadgets to the internet and allowing them to respond to various scenarios based on the data they collect. The following are the key segments where AI and machine learning intersect:

Fitness and health trackers, heart rate monitoring apps, and AR/VR gadgets that employ AIoT, such as smartwatches, AR & VR goggles, and wireless earphones, are examples of wearables.

AIoT is being utilized to make cities safer and easier to live in. Smart energy networks, smart street lighting, and smart public transit are just a few examples.

AIoT is utilized to optimize operations, logistics, and supply chain by providing real-time data analytics.

 

AI in Healthcare
COVID patients have been identified using big data extensively. AI is already assisting the healthcare industry in a significant way and with high accuracy. Thermal cameras and mobile applications have also been created by researchers to monitor individual temperatures and collect data for healthcare institutions. Artificial intelligence can help healthcare institutions in a variety of ways by analyzing data and anticipating various outcomes. AI and machine learning tools provide insights into human health and also propose illness prevention measures. AI technologies also allow doctors to follow their patients’ health from afar, increasing teleconsultation and remote treatment.

 

Natural Language Processing (NLP)
NLP is currently one of the most commonly utilized artificial intelligence applications. The rising popularity of NLP can be attributed to its widespread use by Amazon Alexa and Google Home. NLP has reduced the necessity for writing or interacting with a screen since humans can now speak with machines that comprehend their language. Sentiment analysis, machine translation, process description, auto-video caption creation, and chatbots are all anticipated to grow in popularity by 2022.

 

Conversational AI
Conversational AI, or AI-powered chatbots, improve the reach, responsiveness, and customization of the customer experience. Conversational AI solutions, according to Forrester, result in improved customer service automation. An AI-powered chatbot utilizes natural language processing (NLP) and machine learning to create a more natural, near-human-level conversation by better understanding what the human says and needs. This is also one of the best AI trends.

 

Demand for ethical AI is on the rise
There is a rising need for ethical AI, which is at the top of the list of new technological advances. According to Forrester, CIOs will be required to adapt to digital acceleration while also proactively managing uncertainty and business continuity through the ethical use of artificial intelligence in the coming decade. Given how quickly trends change, customers and employees with strong values want firms to use artificial intelligence responsibly. In the next years, businesses will actively seek out partners that are devoted to data ethics.

 

Quantum AI 
Advanced businesses will begin exploiting quantum supremacy to measure qubits for usage in supercomputers. Quantum computers solve problems faster than traditional computers because of quantum bits. They also aid in the understanding of data and the forecasting of numerous distinct trends. Quantum computers will assist a variety of businesses in identifying inaccessible challenges and predicting viable remedies. Future computers will also be able to handle a wide range of applications in sectors such as healthcare, finance, and chemistry.

Back to top button