- AI will play more role in hyper-automation
Hyper automation, the process where advanced technologies are used to automate tasks, is fast gaining momentum. Companies nowadays are working with a lot of data which demands advanced technologies to extract information from massive amounts of data. This is where automation comes in handy. The increased role of big data analytics in corporate decision-making makes AI and ML algorithms necessary to sift through massive amounts of data and draw patterns that can be used to make decisions. Data science can now be found everywhere, and data science tools will become increasingly available moving forward.
- AI and ML will be used more in Cybersecurity
Cyberattacks have increased in number and severity than at any other time in history. With this advancement, AI and ML technologies will play a crucial part in scanning and fighting attacks. With the help of AI and ML, organizations are now developing new methods of automating cybersecurity. In addition to helping improve cybersecurity, it will also power up the cloud migration strategy while enhancing performance. In fact, cybersecurity use will reach 38.2 billion by 2026. ML will be used in cybersecurity data clustering, classification, processing, and filtering. AI can analyze past data and present solutions for the present and future. Based on the results from the analysis, systems will offer instructions on various patterns while also detecting threats based on the past behavior of malware.
- Machine learning and IoT
The linkup between machine learning and the internet of things (IoT) is one of the trends that tech professionals are waiting for the most. The link between these two will impact the use of 5G, which is now being implemented across the world. As 5G comes with more speed, IoT devices will connect better via the internet. As the number of connected devices increases, the amount of information shared between devices will also increase. This will demand better data processing algorithms, which are made possible by machine learning. ML will ensure there are fewer errors and increases the speed of communication between devices.
- ML in business forecasting and analysis
Business forecasting and analysis will be easy with the application of technology than using traditional methods. It increases accuracy and leads to advanced predictions and forecasts. Companies in the financial sector are using AI to forecast demands for different currencies depending on the conditions of the market and the behavior of the customer based on patterns shown by data in real-time. This will help improve accuracy and make the right decisions regarding supply and demand.
- Augmented intelligence will rise
The collaboration between humans and machines to enhance cognitive performance will be useful to organizations. According to Gartner, 40% of infrastructure and operations teams will embrace augmented automation by 2023 as they seek to improve IT productivity. This will increase the productivity of digital workers by more than 50% by 2022. Augmented intelligence will help platforms gather all types of data, including structured and unstructured, from different sources and present it to the customers. Some sectors such as financial services, retail, healthcare, and travel have already taken advantage of this technology.