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Maria Thompson, Nov 18, 2022
Hyperautomatization is understood as the process of applying innovative developments for accelerated and simple tasks with minimal use of human power and knowledge. This concept is often called digital or intelligent automation. Many modern companies are forced to work with large flows of information, and automation is needed to extract them effectively. Knowledge about data and its analysis can be found everywhere and nowadays these tools are becoming more accessible to everyone.
Data science is suitable for financial institutions, industries, insurance companies, marketing firms, etc. Hyperautomatization is needed to perform research that can increase the company's profit.
The main advanced technologies of this direction:
- Automation of processes using robots (RPA). - Artificial Intelligence and Machine Learning (AI/ML). - Automation of cognitive processes. - Software for correct process management (iBPMS).
The main idea is to combine innovations to simplify, design and automate business processes instead of using methods that are based on narrow activities. The specific methods of using hyperautomatization in the company may differ.
For example, to improve the quality of customer support, you can use a conversational AI and RPA company. This will help automate responses to customer emails, as well as improve the CSAT score. The introduction of technologies into labor-intensive processes allows to improve the productivity of the company's employees. Due to this implementation, manual work is reduced, productivity is improved. System integration will enable the company to integrate any digital technologies into working business processes.
One of the important components of the modern world is information security. AI and ML technology makes it possible to create new methods of reliable protection, and all cybersecurity becomes risk-free and automated.
The main methods of improving cybersecurity using machine learning and AI:
1. Artificial intelligence is suitable for classifying, processing, clustering and filtering incoming information, since there is a lot of information data in such an area. 2. Machine learning makes it possible to analyze past information, provide optimal solutions for the future and the present. With the help of past data, algorithms provide instructions that allow you to find threats or malware. AI and ML help disrupt the work of anyone who wants to get into the system. 3. The introduction of technologies systematizes information according to specified parameters, allowing you to compare different information, track any threats. 4. AI will simplify the audit of information security methods, which will make it possible to quickly learn about the effectiveness of implementing restrictions. This protects the users of a particular company. 5. AI and ML quickly find threats, malware, creating a security platform for scanning large amounts of information.
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Intersection of AI and ML with loT
Modern devices and services on the Internet are becoming more intelligent and secure, which is achieved through the introduction of AI and ML.
In 2022, more than 80% of Internet of Things projects in corporations have AI and ML. For timely response to any situation based on the collected information, all devices must be connected to the Internet.
In the described model, the importance of innovation lies in the ability to quickly obtain information to determine patterns and detect anomalies. All this works with the help of intelligent sensors, additional devices.
Business forecasting and analysis
In comparison with the methods described above, forecasting and analysis in business using AI is the simplest thing that can be. AI and ML makes it possible to make highly accurate forecasts. Financial companies are already using technology today to find out the demand for currency pairs, based on the market situation, show people's behavior, and the level of fear in real time. This makes it possible to provide the financial and technical sector with the necessary volume of supply that meets demand.
The rise of augmented Intelligence
The next trend is combining machines and people to enhance cognitive performance.
By 2023, according to Gartner, 40% of infrastructure and operational groups will start using automation with AI to achieve increased IT productivity. As a result, half of the complex work will be assigned to machines.
With the help of additional intelligence, different platforms quickly make information collection with its structuring according to templates. The data is taken from different sources, and the company receives complete information about the product, the customer, etc.
This trend is perfect and will be actively developed in 2023 in the financial services, healthcare, travel and trade sectors.
For the success of any type of activity, AI and machine learning play an important role in managing complex tasks and supporting their correctness. The robotization of processes has shown impeccable results, excluding the human factor, errors, etc. The active and large-scale development of industrial spheres further increases the need for trends and development of artificial intelligence and machine learning.