In the long process of digital transformation, enterprises should build smart strategic plans across functional and process silos, make full use of smart tools such as RPA, iBPMS, DTO, and AI and integrate them with existing systems to achieve Continuous digital transformation. The complementarity and integration of technologies will further improve work efficiency for enterprises, and these trends will grow rapidly in the next five years, are highly volatile, and reach a critical point, becoming an important tool for the new generation to change the way enterprises work.
There are many smart technology, tools and solutions are people-centric, no matter how good and efficient tools are to serve people; the application trend of technology should be based on the background of people and organizations, rather than building a technology stack. When companies are exploring digital transformation, they must first consider the combination of business and humanistic environment, which is also called the “people-oriented smart space”.
Based on top reports the following are the corporate strategic planning data evaluated:
· By 2022, 70% of enterprises will provide consumers with an immersive consumption experience, and 25% of them will deploy it into production;
· By 2024, 75% of large enterprises will use at least 4 low-code (or no-code) development tools or daily office tools;
· By 2021, robotic process automation will enable data scientists to produce higher and higher quality data analysis;
· By 2022, 30% of enterprises will use AI to make decisions;
· By 2020, the online transaction volume of high-reputation companies will increase by 20%;
· By 2022, 30% of all AI cyber-attacks will use training data models to resist virus attacks.
The following are the “Top Technology Trends of 2020” :
1. Super automation
Automation refers to the use of software technology to automatically execute the work that needs to be performed by humans, thereby helping enterprises and organizations to effectively improve work efficiency and save time. Super automation refers to the sum of machine learning (ML), software toolkits, and automation tools used to deliver work. Automation not only involves the breadth of the tool platform, but also all the steps of automation itself, including: discovery, analysis, design, automation, monitoring, intelligent analysis, etc. Super-automation requires the selection of appropriate tools and technologies to meet current challenges. Understanding the scope of automation, the relationship between business and automation, and the combination and coordination between them is the main focus of hyper-automation.
- Robotic Process Automation (RPA): It mainly uses software robots to automate those rule-based, repetitive, and boring tasks. For example, RPA robots can easily transplant the data of system A to system B. And it also has the characteristics of convenient deployment, non-intrusive, easy-to-use, and convenient maintenance. RPA have many application like RPA in healthcare, retail, finance. Automation in healthcare is widely helping specially at this time of pandemic. RPA use cases is specially helping while implementing it to processes.
- Intelligent business process management: Intelligent business process management is a comprehensive technology that integrates coordinating people, machines, and businesses. The working mechanism of iBPMS relies on processes and rules to help users systematically manage work tasks. Usually the integration with external systems is achieved through powerful APIs. In addition to processes, powerful decision-making capabilities can simplify the work environment and provide natural integration points for advanced analysis and machine learning.
2. Multiple experiences
By 2028, user experience will usher in tremendous changes in perception and interaction with the digital world. Virtual reality and augmented reality along with NLP can contribute a lot to user experience. The changes in perception and interaction modes will bring us unprecedented multi-sensory and mode experience in the next few years. Although the potential of VR, AR and MR is expected, there are still many challenges and obstacles, such as: identifying key target characters and exploring the target scene, exploring the target user in different locations (at home, in the car or work), etc. By 2022, 70% of enterprises will try to provide users with immersive consumption, and 25% of them will deploy it in production.
3. Democratization of technology
Democratization refers to the provision of professional technology (for example: ML, application development, artificial intelligence) or business domain expertise to staff, which completely simplifies the application process of these technologies, and can be applied without time-consuming and expensive training. The currently developed code-free software and visual drag-and-drop operations are good examples. The trend of technological democratization from 2020 to 2023 will usher in rapid development in the following aspects:
- Democratization of data and analytical skills (tools originally targeted at data scientists are rapidly expanding and gradually serving the general developer community).
- Democratization of development skills (using AI tools to achieve customized development of applications).
- Democratization of design skills (development through a low-code, no-code model, and enhancement of developers’ abilities through built-in automated development functions in applications).
4. Intelligent technology enhancement
The continuous enhancement of smart technology will ultimately serve people. Enhancing human capabilities refers to the use of technology and science. Human beings have always been influenced by this technology and science to realize the progress of civilization. For example, before the introduction of computers, technologies such as typewriters and photocopiers have enhanced the ability of humans to create, copy, and publish texts. With the rise of new technologies such as computers, the Internet of Things, artificial intelligence, smart speakers, and virtual reality, as well as new technologies such as CRISPR 18 that have emerged from biological sciences, all aspects of humanity are continuously being enhanced.
5. Artificial Intelligence Security
Artificial intelligence and machine learning will continue to be used to improve human decision-making capabilities in various application scenarios. Although this brings great opportunities to realize hyper-automation and use automated objects for business transformation, it also adds a large number of potential attack points to security due to the Internet of Things, cloud computing, micro services, and highly connected systems in the smart space. With the expansion of the speed and types of network attacks, it is increasingly difficult for network security personnel to defend against these malicious attacks. AI ML tools can help in enhancing security and filtering. Organization are taking help of AI consulting firm and RPA consulting services for automating their manual and time consuming processes.
