Top 10 AI Trends to Watch in 2021

Artificial intelligence and its subdomain Machine Learning (ML) have been showing promising trends over the past few years. At one side, AI is transforming the way of living and human interactions almost in every industry at large scale. On the other side the restrictions and polices imposed during COVID-19 pandemic has turned out to be an advantage for AI to grow. Given the lockdown situation and businesses turning towards digital transformation, AI has emerged as only futuristic technology that is not only solving and automating manual business workflows but also helping in reducing the cost. Year 2020 has witnessed many unique platforms, researches and tools that utilize AI to great extent, but year 2021 has promised much more and quite rightly called as the golden year for AI implementation.

The global AI market size was calculated as $39.9 Billion in 2019 and expected to achieve compound annual growth rate (CAGR) up to 42.2% from 2020 to 2027. Technology has made innovations in big fields like healthcare, retail, automobile, and finance with continuous research. AI is one significant element that is promising to dominate and transform the digital era entirely with high accuracy and precision.

In this article, we have come up with Top 10 Artificial Intelligence Trends to watch in year 2021. These have the potential to hit great innovation in future. Let's have a look at these strategies:

1. Robotic Process Automation (RPA)

It's one of the most disruptive AI technologies that help in performing repetitive manual tasks. It can efficiently perform a high-volume, repetitive task on the desktop without creating any mess. The work might be of invoicing a client. For it, the robot opens email via RPA, copy the given data into a CRM database and then collect data from another related database. It replies to that client with new data. Besides, it can perform the given task multiple times in a day and saves human’s time to do some other productive task.

Robotic Process Automation is a robot that works on using software for performing repetitive manual tasks. If there is something beyond the knowledge of robot, it notifies its owner to step in. in a nutshell, RPA performs the mundane task and give time to people for more exciting work.

RPA would be in use in billing, invoicing, payroll processing, extracting data, tracking, and shipment scheduling. Its also known as Hybrid Workforce that shows the collaboration of human workforce with robots.

Vanguard is a financial service providing company that comes $5.6 trillion in global assets under management department. The company uses RPA for doing exceptional trading tasks. It works with, "when x happens, do y." However, the RPA system cannot eliminate the need for humans. The combination of humans and technology helps in providing better services to clients and allowing humans to focus on complex tasks.

2. AI in Healthcare

AI is already helping the healthcare industry to a great extent with high accuracy, but further advancements will surprise everyone. AI developing companies are struggling hard to create advanced tools for enhancing the health industry’s capabilities—AI-inspired humans in recovering patients from recent pandemic COVID-19. Big Data was used to identify COVID Patients and significant hot spots. Moreover, researchers developed thermal cameras and smartphone apps for measuring the temperature of individuals and collecting data for healthcare organizations.

AI can help healthcare department in many unique ways by using data analysis and predicting different results. AI and ML tools provide insights about human health and also suggest preventive measures to stop the disease spreading. There is another AI trend; AI Watches that can help doctors to track their patient’s health remotely.

Predicting Pandemic Even Before It’s Start

Now researchers are working on advanced AI algorithms for accurately predicting future outbreaks. Some of the significant research is already done on it that generated some earliest alerts about the current pandemic. In Wuhan, China, the BlueDot Tool by Toronto was scanning over 100,000 governmental and media data daily and shared an alert about the potential pandemic.

3. AI for Cybersecurity & Data Breaches

The use of advanced AI tools will collect and analyze a wide range of data sets. It will fetch information from news, blogs, websites, and stories to identify all threats. As it collects more data, the system will become more precise.

In 2021 and beyond, digital data will be at more risk to be hacked and vulnerable to phishing attacks. AI and advanced technologies will provide support to the security department against malicious activities in every field. AI will help to prevent cybercrimes in future with enhanced enterprise cybersecurity measures. The AI-supported system will spot fake digital activity or transactions that follow criminal patterns.

Its preventive alarms will protect sensitive data information from data hacking firms. Furthermore, it will take only a few seconds to detect any threatening activity, including suspicious IP addresses. It allows security dealers to respond to these activities faster than usual. Because of its high efficiency and advantages, the demand for AI in cybersecurity will rise in 2021.

4. Natural Language Processing (NLP)

Here machine learning models teach computers to understand what's written or spoken material describing a specific process. It becomes one of the top and highly-demanded application of AI in the present time. The popularity of NLP is rising because of its significant usage as Amazon Alexa and Google Home. NLP eliminated the need for writing or interacting with a screen as now humans interact with robots that understand their language.

Natural Language Processing comes with two sub-applications.

Natural Language Understanding: As its name shows, it enables a machine to review a written text and understands its meaning correctly.

Natural Language Generation: It’s a logical response that a machine generates for any given input, for instance, any text.

The use of NLP will increase in 2021 for sentiment analysis, machine translation, summarizing a process, auto-video caption generation and as chatbots.

YouTube uses NLP technology in generating captions automatically across its platform. YouTube Video involves a speech recognition software that produces video cations. The system used this technology first in 2009 for translation of dozens of languages.

5. Reinforcement Learning

Reinforced Learning (RL) is one of the demanded skills of future by different organizations. It's a particular application of deep learning that works based on its experience for improving data's effectiveness. In this learning process, the software is ingested with several different conditions that tell about its specific task performance. Thus, various actions define about self-learned actions of software that it performs to get the final result.

For instance, Chatbot has information to respond to a general user's queries like greetings, order booking, or consultations calls. Machine Learning Development Companies can add sequential conditions in chatbots by using RL. It will make them more productive and helpful in getting more sales and transferring calls to the relevant department. Some other useful applications of RL are robotics in planning business strategies, advertising content optimization, automating industries, controlling aircraft, and making motion control robots. Moreover, it allows personalized recommendations with the optimization of the product's advertising budget.

Alibaba, an outstanding Chinese e-commerce site, uses Reinforced Learning to boost its return by 24% for online advertisement without rising its budget. The team at Alibaba explained in a research paper that how they used RL in optimizing sponsored search campaign. They created a bidding model for impression every hour and performed real-time bidding with it.

6. The Joining of the Internet of Things with AI (AIoT)

Internet of Things (IoT) is in use for proper management of interconnected devices. These devices are performing exceptional tasks in different organizations, homes, and companies. However, researchers enhanced the capabilities of IoT devices by coupling them with AI. IoT technology has potential to offer real-time information in software and customer relationship management (CRM). It will also monitor the performance of several interconnected gadgets.

These AI-powered smart solutions can be used for high maintenance in industrial devices. It also helps in delivering or discussing problems remotely. AI and IoT, when employed together, will offer an incredible ear for exciting insights. Sensor powered AI will help in bringing predictive maintenance in manufacturing goods. Smart Home Devices like Nest (Google's application) will gain popularity. According to an estimation, 28% of the US homes will become smart homes by 2021. It will resultantly boost efficiency to achieve the next level.

Another example is AI applications allowing field agents to spot faulty machines. It works with image recognition feature embedded in Field Service Applications. AIoT supports businesses by detecting defects and providing predictive maintenance.

7. Facial Recognition- A Breakthrough in 2021

Because of the current COVID-19 issues, facial recognition technology will grow at a rapid pace in 2021. It identifies facial features from images and videos by using biometrics and then compare this information with the already available database.

Facebook is a social platform that uses Depp Face Program in tagging family members and friends in a photo. There is an embedded Facial Recognition system in iPhones that assist users in unlocking the phone while paying bills or performing other related tasks.

This outstanding technology will use in healthcare, personalizing the customer experience, retail, and aviation. In the coming years, the face-recognition system will become more sensitive and precise than today.

8. Enhanced Focus on Quantum AI

Advanced businesses will start using quantum supremacy to quantify the Qubits for use in supercomputers. Quantum computers solve problems at a faster rate than classic computers do because of quantum bits. Moreover, they help in analyzing data and then predict several unique patterns.

Google and IBM will prepare these extraordinary computers that will represent the next step towards exploring quantum computing. It will open the doors to making potentially string machines to predict business' outcomes with quantum computing research.

Quantum computers will surprise several firms by finding inaccessible problems and also predicting meaningful solutions. Future computers will also provide breakthroughs in fields including healthcare, finance, chemistry, and biology. It can be referred to as a significant AI trend to watch in 2021 as many companies are looking for it.

9. AI-Powered Business Processing, Forecasting, and Analysis

AI-powered tools help in redefining business processing and functioning strategies with real-time updates. The researchers coupled hyper-automation with cognitive automationprocess for understanding business needs deeply. Content intelligent technologies, along with AI-supportive processes, will help the digital worker to get exceptional skills. These skills will help them to deal with natural language automation, judgement, creating context, reasoning, and offer data-related insights.

Moreover, business analysis with time has become a popular trend since last years, and it's still a hot topic. It allows analysts to gather and analyze a specific set of data information over a specific period; it helps in predicting various aspects of smart businesses. If diverse data sets train ML networks, then they can provide forecasts with 95 per cent accuracy.

In 2021, many companies will introduce recurrent neural networks for obtaining highly accurate forecasting information. Deep Learning solutions will be embedded to get hidden patterns and actual forecasts. In real-world applications, it will help in detecting possible frauds that otherwise costs very high.

10. Edge Computing

There is a lot of online data that moves around smartphones, smartwatches, and IoT-enabled devices in our homes or businesses. Processing and collecting all this data in one place is a complicated procedure. Also, processing requires all information shared with cloud computing devices and having no internet connection makes it more complicated without any solution.

Edge computing offers servers and data storage for gadgets to access their devices and allow them to put data in them. It's known as real-time data processing that's more efficient than cloud computing services. Another example of edge computing is carried on nodes. It's a mini-server that is placed near to a local telecommunication provider. Nodes help in creating a bridge between the cloud and the local service provider. It costs less and also time-saving technique; thus, offering a fast service to the customers.

It will be used for interconnecting many smart devices and growing IoT (internet of things) technology. The Amazon Echo comes with Alexa Assistant Technology that is not inside the device but responds when connected to wi-fi. It detects the “wake-word” of “Alexa,” but can’t process it without an internet connection. However, it always requires a cloud-based server to respond to a complicated or straightforward request. Amazon hopes to introduce simple questions like "What time is it?" n the device by using specially designed AI chips. It will help in reducing response time, providing faster user experience.

The Next-Generation Technologies Powered by AI system

From those mentioned above top 10 AI trends to watch in 2021, it seems that AI will gain more popularity in the coming years. However, it also comes with lot of challenges and problems to achieve advancement in every domain. Researchers, experts, and professionals will join hands to use the potential AI for improving customer experience and optimizing operations.

The scope of AI is diverse and varies from one business type to another. AI tools are already helping businesses to get maximum output form projects. Organizations must follow current trends and find ways to implement these solutions for the betterment of their businesses.