A glimpse on top 10 Artificial Intelligence (AI) innovation trends in 2021
Although the COVID-19 pandemic affected many areas of industry, it did not lessen the impact of Artificial Intelligence in their daily lives. Thus, we can assume that AI-powered solutions will undoubtedly become more widely used in 2021 and beyond.
Here are the top 10 Artificial Intelligence (AI) innovation trends to watch out for this year:
AI for Cybersecurity and Data Breach
Knowledge will become more available in the coming years, putting digital data at higher risk of being hacked and vulnerable to hacking and phishing attempts. AI and new technologies will help the security service in combating malicious activities in all areas. With strengthened safety initiatives, AI can help prevent cybercrime in the future.
AI can Assist in Structuring Data
More unstructured data will be organized in the future using natural language processing and machine learning methods. Organizations can take advantage of these technologies to generate data that can be used by RPA (Robotic Process Automation) technology to automate transactional operation. RPA is one of the tech industry’s fastest-growing segments. Its only drawback is that it can only work with structured data. Unstructured data can be easily translated into structured data with the aid of AI, resulting in a valuable performance.
Many industries and companies have deployed AI-powered chatbots in the previous years. Better customer service automation is possible with AI chatbots. These conversational AI chatbots will begin to learn and develop their understanding and communication with customers in 2021.
The Covid-19 pandemic is quickly shifting automation priorities away from front-end processes toward back-end processes and business resilience. Intelligent Automation can, in reality, combine robotic and digital process automation with practical AI and low-code devices. While growing their operations, these innovations will help companies become more competitive and robust.
Quantum AI is set to grow in popularity as more businesses seek to implement the technology in supercomputers. Using quantum bits, quantum computers can tackle any possible problem much faster than traditional computers. This can be useful for processing and analyzing large sets of data in real-time, as well as rapidly predicting specific patterns. In the next decade, quantum AI is predicted to make significant advances in fields such as healthcare and banking.
Robotic Process Automation (RPA)
RPA is one of the most revolutionary AI systems for automating repetitive tasks. On the desktop, it can effectively execute a high-volume, repetitive process without making a mess. It’s possible that the job entails invoicing a customer. Furthermore, it can repeat the process several times a day, freeing up human time for more productive activities.
AI in Healthcare
AI is now assisting the healthcare industry in a significant way and with high precision. AI can help healthcare facilities in a variety of ways by analyzing data and predicting different outcomes. AI and machine learning tools provide insights into human health and also propose disease prevention measures. AI technologies also enable doctors to monitor their patients’ wellbeing from far away, thereby enhancing teleconsultation and remote care.
AI with the Internet of Things (AIoT)
Artificial intelligence is a wonderful technology that, when combined with the power of the Internet of Things (IoT), can provide a powerful business solution. The convergence of these two technologies in 2021 would lead to significant changes in the automation domain.
Face recognition technology will evolve at a rapid pace in 2021 as a result of the recent Covid-19 problems. It uses biometrics to identify facial characteristics from photographs and videos, and then compares the information to an existing database.
Businesses can use edge computing to convert their daily data into actionable insights. It provides servers and storing data solutions for computers and apps to ensure a smooth operation while allowing for real-time data processing that is much more efficient than cloud computing. Edge computing will also improve the efficiency of cloud servers because it can be carried out on nodes.
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