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Artificial Intelligence In 2022: What Will Be The Next Big Thing?

Artificial intelligence is reshaping the IT industry by supporting businesses in reaching their goals, making critical decisions, and inventing new products and services. By 2022, companies are anticipated to have 35 artificial intelligence initiatives in place. By 2022, the AI and machine learning market are predicted to grow at a 44% compound annual growth rate (CAGR) to US$9 billion. In recent years, there have been several developments in AI and machine learning technologies. We’ll go through some of the most crucial AI trends for 2022 in this blog.


The expanded role of Artificial Intelligence in Hyper-automation


Hyper automation is that the process of using advanced technologies to automate tasks. Other words for the same thing include digital process automation and intelligent process automation. Some of the sophisticated technologies typically used in hyper-automation include robotic process automation, artificial intelligence, machine learning, cognitive process automation, and intelligent business process management software. Companies can utilise conversational AI and RPA to automatically respond to client inquiries and improve their CSAT score. By automating time-consuming activities, businesses may reduce employee manual work and increase production. Companies can use hyper-automation to integrate digital technologies into their processes. One of the best AI trends is hyper-automation.


Cybersecurity and Artificial Intelligence


Artificial intelligence (AI) is becoming more and more important in the field of information security. With the use of AI, companies are developing new approaches to make cybersecurity more automated and risk-free. Businesses are using AI to improve their cloud migration plans and the effectiveness of big data technology. The cybersecurity industry for AI and machine learning is anticipated to reach US$38.2 billion by 2026. A significant number of data points are involved in cybersecurity. As a result, AI could be used to cluster, categorise, analyse, and filter data in cybersecurity. By arranging data in a specific way, AI can help you correlate numerous data sets and look for dangers. You can use AL and ML to identify malware and risks by developing a security platform that scans large amounts of data.



Forecasting and business analysis are two of the most important aspects of the job



Business forecasting and analysis utilising AI and ML have proven to be significantly easier than any previous method or technology. You may use AI and machine learning to consider thousands of matrices to make more accurate predictions and projections. Fintech firms, for example, are employing artificial intelligence to forecast demand for different currencies in real-time based on market conditions and client behaviour. It enables Fintech companies to have the right amount of supply to meet demand.



Augmented Intelligence’s Evolution



Augmented Intelligence is one of the most popular AI trends. Augmented intelligence refers to the use of robots and humans to increase cognitive performance. By 2023, Gartner predicts that 40% of infrastructure and operations teams will use AI-augmented automation to enhance IT productivity. In fact, by 2022, digital employees’ contributions will have climbed by 50%. Platforms with augmented intelligence may collect all types of data from different sources, both structured and unstructured, and display it in a 360-degree view of customers. Financial services, healthcare, retail, and travel are just a few of the areas that are embracing augmented intelligence.


The convergence of AI and machine learning with the Internet of Things (IoT)


Machine learning (ML) and artificial intelligence (AI) are increasingly being utilised to make IoT devices and services smarter and more secure. According to Gartner, AI and machine learning will be used in over 80% of IoT activities in enterprises by 2022. The Internet of Things requires connecting all of your devices to the internet and allowing them to respond to different scenarios based on their location.


Wearables include fitness and health trackers, heart rate monitoring apps, that use IoT, such as smartwatches, AR & VR goggles, and wireless earphones.


The Internet of Things is being used to make cities safer and more livable. Just a few examples are smart energy networks, smart street lighting, and smart public transportation.

By offering real-time data analytics, IoT is used to optimise operations, logistics, and supply chain.


Artificial Intelligence in Healthcare


Big data has been used extensively to spot COVID patients. AI is already making a big and accurate contribution to the healthcare industry. Researchers have also developed thermal cameras and mobile applications to monitor individual temperatures and collect data for healthcare organisations. By evaluating data and anticipating potential outcomes, artificial intelligence may assist healthcare facilities in a variety of ways. AI and machine learning systems offer insights into human health and suggest ways to avoid sickness. AI also enables doctors to monitor their patients’ health from afar, allowing for more teleconsultation and remote treatment.


Natural Language Processing


NLP is one of the foremost widely used AI applications nowadays. The broad use of NLP by Amazon Alexa and Google Home is credited with its expanding popularity. Because humans can now converse with robots that understand their language, NLP has decreased the need for writing or interacting with a screen. By 2022, sentiment analysis, machine translation, process description, auto-video caption production, and chatbots are expected to become more prevalent.


Artificial Intelligence that converses


Conversational AI, often known as AI-powered chatbots, improves consumer reach, responsiveness, and customisation. According to Forrester, conversational AI systems boost customer service automation. By better comprehending what the human says and needs, an AI-powered chatbot uses natural language processing (NLP) and machine learning to generate a more natural, near-human-level dialogue. This is also one of the most promising AI developments.


The demand for ethical AI is increasing


The demand for ethical AI is growing, and it is at the top of the list of new technological developments. According to Forrester, in the future decade, CIOs will be expected to adapt to digital acceleration while also proactively managing uncertainty and business continuity through the ethical application of artificial intelligence. Customers and employees with strong values want businesses to use artificial intelligence responsibly, given how quickly trends change. Businesses will actively seek out partners who are committed to data ethics in the coming years.


AI at the quantum level


Quantum supremacy will be used by advanced industries to measure qubits for use in supercomputers. Because of quantum bits, quantum computers solve problems faster than ordinary computers. They also assist in the comprehension of data and the forecasting of a variety of different trends. Quantum computers will help a wide range of organisations detect inaccessible problems and predict feasible solutions. Computers in the future will be able to handle a wide range of applications in fields including healthcare, finance, and chemistry.




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