Top 3 AI Trends For 2021

Artificial Intelligence (AI) is one of the most useful technologies today as it shapes a new way of life. New jobs arise from AI innovation and we expect the platform to redefine how businesses operate. Practically every industry, including healthcare, education, finance, and digital signage, benefits from AI that promotes the use of Machine Learning (ML) and Big Data analytics.

AI and ML are changing the way we live and run businesses on a large scale. Given how enterprises are showing a growing interest in digital transformation, AI has emerged as a promising technology. Look how Google Home, Amazon’s Alexa, and Apple’s Siri have improved our everyday lives. These inventions will inspire even greater developments in the coming years, with AI leading the way.

If you are a tech expert or enthusiast, you know that AI goes beyond automating manual business workflows and enabling cost-savings. “What’s next”, you ask? Let’s explore three of the biggest Artificial Intelligence trends to look forward to in 2021.

AI-Driven Decision Making

Governments and health authorities are working together to enhance data accumulation, aggregation, and analysis when it comes to addressing uncertain times like the COVID-19 pandemic. Scientists are using AI-inspired solutions to conduct experiments and publish findings that can assist people. Researchers have come up with more sophisticated Natural Language Processing (NLP) algorithms to search through the wealth of information we have. These practices contribute further to communications, data analysis, and advancements in medicine.

For instance, healthcare experts use AI programs to diagnose certain illnesses with at least 90% accuracy. Big Data enables doctors and nurses to identify COVID-19 patients and hot spots. Professionals have created smartphone applications and thermal cameras to measure patient temperature and gather useful data.

Also, what about leveraging data analysis and predicting results in hospitals and clinics? AI and ML solutions offer meaningful insights into human health and recommend preventive steps to stop the spread of diseases. If you explore the market, you will come across AI watches that even help doctors monitor their patients’ health remotely. 

Other industries also utilize AI and Big Data to drive success. Marketing has transitioned from single article purchases to subscription and tier-based systems especially in the SaaS sector. Tiered systems encourage customers to buy products that meet their needs and budget. This practice is on the rise because of the information companies collect across marketing platforms using AI. 

Moreover, marketing, sales, and customer services use Big Data to make better marketing decisions and solve challenging problems. For instance, businesses utilize data to target the right audience. AI, along with IoT, analyzes information to enhance customer experience. These practices gather and optimize data about every customer. Companies can use technology to predict a client’s next action, such as making a purchasing decision or craft a promotion that is sure to deliver results. 

Not to mention how smart machines and self-teaching algorithms will help us rethink and revisit our business strategies and priorities. All this will further increase in 2021 as companies look to streamline workflows, work smart, improve efficiency, and address customer pain points more effectively. 

According to Oberlo, a 2019 Gartner study reveals that by 2021, AI will drive around 15% of customer service interactions around the world. This represents a huge 400% increase from 2017 statistics. These numbers give us food for thought and are certainly worth taking into account.

Top 3 AI Trends For 2021

AI-Powered Chips

The rising investments in AI solutions introduce the need for processors that are quick enough to process data that these solutions require. Even advanced CPUs cannot keep up with the processing speed that AI needs to perform activities involving ML, NLP, computer vision, object detection, facial recognition, and speech recognition. This is where AI-enabled chips matter.

AI-powered chips can deliver the processing speed that CPUs cannot. It enables us to increase efficiency and tackle straightforward tasks within seconds while simplifying complex assignments. The reason is AI chips can perform more computational functions per unit of energy. Researchers also develop these chips to enable advanced calculations, query processing, and predictive analytics that AI algorithms demand. 

Why are businesses interested in AI-enabled chips? Notably, AI software operated on graphical chips with a high capacity for parallel processing. With time, experts discovered that they can architect microchips with powerful features for Deep Learning and optimize them for use in high-performance industries. If you conduct R&D on these microchips, you will see that they integrate massive amounts of data such as images, text, and language.

What does this leave us with? We can safely say that AI is rapidly advancing at both the software and chip levels. Companies are rapidly integrating AI into their systems, making the technology more accessible to developers who can apply it to data and applications. For instance, cloud providers like Google, AWS, and Azure embedded and extended their AI products for both public and hybrid cloud deployments. If others do the same, they can increase accessibility to computing power and algorithms that incorporate AI into mobile devices, smart speakers, ERP software, etc.

AIOPs

The IT operations landscape is evolving with AI at the forefront. Businesses are looking to increase efficiency and productivity by implementing more automation so they can focus on addressing complex problems and business challenges. In 2021, AI will continue to automate repetitive work and save time. 

Let’s come to AIOPs which is shifting from one data type to multiple data type algorithms. It all started when experts applied AI, ML, and statistical analysis methods to a single data type which was either logs, metrics, or transactions. In 2021, we can expect data scientists to innovate AI algorithms for multiple datasets. This means examining logs, metrics, and transaction information together, understanding how they correlate, and what signals professionals can filter for fast troubleshooting. 

At the start of 2020, employees across the globe had no choice but to work from home on short notice due to COVID-19. For many businesses, the new reality is remote work, and this is where they have to modify their IT infrastructure accordingly. If we talk about AIOPs, it does not matter where your employees perform their job duties. Once it puts an algorithm into use, it accepts the input data, draws business intelligence (BI), and outputs the optimized value. Remote work becomes easier to manage with productivity levels remaining consistent.

Also, organizations require smarter algorithms to predict challenges related to employee productivity or the customer experience of using a product remotely. These translate into different data sources that become difficult to analyze due to the massive volume of information. AI can help by automating the complicated processing of disparate data streams that anticipate problems before they take place. 

Top 3 AI Trends For 2021

The list does not end here. AIOps will become more common in IT observability solutions, starting from the customer experience that defines business performance and value. This metric indicates how well your clients are interacting with your business or engaged using your products. Then, you have user productivity that outlines how productive your employees are with the proper tools and technologies. The last, and perhaps the most important, is your digital infrastructure that connects the customer experience and user productivity to a unified platform. If these elements do not go hand in hand, then you will have insufficient transparency or visibility into business performance.

Another benefit of AIOPs is it effectively combines security and IT operations to identify infrastructure performance issues and prevent cybersecurity vulnerabilities in real-time. AIOPs features will become more mainstream within company products, especially SaaS monitoring solutions. This will allow companies to extract valuable insights and new opportunities without incurring high R&D costs. 

Conclusion

At Clouve, we offer the latest cloud, DevOps, and automation solutions that see your business through to completion from beginning to end. Please contact one of our experts today to change the future of work and maximize productivity as well as profitability.