In 2016, the artificial intelligence company generated a valuation of fund revenue of 8 billion U.S. dollars, and this figure is expected to quadruple in the next three years. Entrepreneurs have invested in artificial intelligence, not only as a way to reduce costs, but also to use it to change the customer and employee experience. Accenture’s 2017 Technology Vision shows that in more than 5,400 IT industry and corporate executives, approximately 79% believe that artificial intelligence will accelerate the use of technology in their organizations. The disruptive development of artificial intelligence is an established fact, but the impact of disruptive development on the workforce is the part that makes it most difficult for companies to describe and handle. What must be clear now is that the leaders of various industries should begin to adopt the right way to view the role of different types of employees, whether human employees or machine employees, in the future labor market. These impacts on the labor force are particularly prominent in the IT field. From analysis to cloud computing, CIOs are dealing with large-scale destruction. Artificial intelligence is both a huge challenge and an opportunity for a hundred years for IT organizations to promote industry changes and open up industry capabilities. In order to seize the opportunity, leaders of IT companies must take decisive action to reshape the capabilities and skills of internal personnel and meet the future of artificial intelligence. To grasp the value of machine learning and artificial intelligence, there are five key capabilities that technical personnel must master. 1. Machine management capabilities "Machine will replace humans" - this potential negative impact, it is obviously anxious to corporate managers and employees. One frequently overlooked question is: How do employees in the company develop and maintain "robotic operating automation software" (RPA), smart machines, or physical robots? Artificial intelligence is a capability of a business or organization, to a large extent It is still in its infancy. This means that in most cases, the use of artificial intelligence is a proliferation within the organization. Correspondingly, its systematic nature is still immature and scattered. IT companies have the ability to develop technology architectures and open the future of smart machines throughout the industry. However, this ability is not inherent to IT organizations. The CIO and the IT industry must unite their development paths and, through the training and development of artificial intelligence, transform them from the traditional simple "lighting on" behavior, to the period of effective artificial intelligence in the future, and to the paradigm that can make correct decisions. Character. 2. Process information capabilities From the perspective of improving the enterprise development process to reach its optimal top-level or bottom-line results, IT companies have long been underutilized resources. For example, artificial intelligence processing and processing of large amounts of information is difficult for humans to achieve, this ability can greatly improve the efficiency and quality of anti-money laundering operations. In other words, artificial intelligence can increase the proportion of human decision-making in the operational process by synthesizing data and making basic decisions. This also means that humans must redesign their operations, reshape their capabilities, support integrated approaches and respond to more complex decisions. Artificial intelligence is transforming the traditional customer-centered and internal operational processes in ways that humans have not yet mastered. This is clearly a fusion of traditional enterprise operations management and RPA operations. More broadly, there are many examples other than RPA, such as the customer voice recognition authentication system, which can greatly improve the quality of customer communication services in some industries. 3. Platform and data management capabilities Technicians must have strong information processing and technology platform management capabilities. Machine learning methods can only generate predictive models that are equivalent to the quality of the input data. Organization and data quality are obviously not a new challenge for companies. If a person does not have the ability to support and process models and platforms, artificial intelligence will encounter bottlenecks. However, people will still take a risk. IT companies are rebranding themselves as an organized cloud provider. New technology and architecture concepts require the IT team's corporate data stewardship, and ultimately break the gap between departments and harness the power of machine learning. 4. Algorithmic awareness Not everyone is going to be a data scientist, but it's really important for technicians to have basic data processing capabilities and to describe the ability of artificial intelligence algorithms from creation to final output data. A company has two core sources of interest. First, IT can describe artificial intelligence capabilities to companies and collaborate with companies to continually improve models. Second, a basic understanding of the mathematical concepts that drive machine learning can open up knowledge and creativity. This creativity enables IT organizations to create positive benefits for companies while building an artificial intelligence capability framework. For example, Accenture collaborated with the United States Stevens Institute of Technology to develop advanced workforce analysis capabilities in key areas. 5. Leadership and judgment Daily administrative work takes up a lot of our time, but in the future, machines will help us deal with these tasks and become our “good colleaguesâ€. By then, all the company's employees need not only to accept a new world where the machine holds the decision-making power, but also to use their judgment in more challenging decisions. To complete such a transition, you need to have a more focused problem-solving ability, and master the same skills as the machine can handle and ultimately arrive at the correct guiding response. In order to grasp these related capabilities and skills as quickly as possible, what should business leaders do now? First, conduct an internal learning activity that focuses on the benefits of artificial intelligence and artificial intelligence, and reduce employees’ fear of the machine. Prepare artificial intelligence for "entry" labor. Through a series of virtual events and hands-on activities, companies can enable employees to further understand artificial intelligence and enhance their artificial intelligence capabilities. The level of these activities can be adjusted according to the level of the labor force and its ability, so that people can gradually improve their ability. In addition, to explore the work dynamics of artificial intelligence, you need to constantly emphasize this point to people: “Artificial intelligence makes work more efficient, it reduces our workload, not jobs.†Even artificial intelligence can be deployed in activities Prototype or perform practical exercises. Finally, make a summary to improve the creativity, openness, and flexibility of everyone, especially business managers, in the use of artificial intelligence. The machine is on our side. Soon, all the companies and governments in the world will have machines. Team leaders will have no reason not to adopt these automation and enhancement techniques. The opportunity for IT staff is to reshape the labor force so that their employees have the ability to use artificial intelligence in the future. Focus on the machines that can be managed efficiently, then focus on the data and algorithms they use, and finally their leadership and judgment so that the technical staff can promote the optimization of artificial intelligence in their organizations.