Usage of AI and Robotics in Project Management

Technological progress has allowed the humanity to use the technologies they could not implement in the past centuries. Some of these innovations include robotics and artificial intelligence (AI), which help individuals to perform regular tasks and often present the features humans do not have. The purpose of this paper is to address the differences between robotics and AI, the impact of these fields on project management, and the examples of possible applications of such innovations. This report discusses the definitions of AI and robotics and features the information about the technologies these fields utilize.

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Moreover, the literature review is provided to show how AI and robotics can improve project delivery and efficiency. In addition, the report presents several AI and robotics brands and features to illustrate the aspects of these fields. The paper concludes that AI and robotics can be applied to project management both as a combined solution and separately, depending on the needs of an organization.

Differences Between Robotics and AI

Before analyzing the topic in detail, it is vital to outline the differences between robotics and AI. In the early days of the development of AI, these fields were closely related; however, currently, there are significant variations between them (Rajan & Saffiotti, 2017). In the beginning, the initial and primary goal of AI was building embodied intelligent systems, which became possible with the rapid global progress in hardware and the increase in data due to the development of the Internet. The impact of these factors allowed computer scientists to run complex algorithms and use more data for their work and experiments. However, currently, the objective of AI is creating expert systems that may not look similar to people but are designed to help them due to their human-like intelligence (Rajan & Saffiotti, 2017).

The point presented above can be illustrated by the example that with AI, programs can learn from their users, while without it, they can only perform pre-set functions. Some of the functional areas of AI are fuzzy logic systems, natural language processing, and expert systems (Doncieux, Bredeche, Mouret, & Eiben, 2015). The major functions programs having AI may perform include learning, decoding, problem solving, language detection, and speech recognition.

Thus, it is possible to say that AI can be applied to various spheres of life and fields of operations, including project management. On the contrary, the growth and development of robotics as a field has become significant within the past two decades (Rajan & Saffiotti, 2017). Robotics is also associated with the concept of embodied intelligence, which studies the robots, its environment, and the interaction between its components (Doncieux et al., 2015). These facts will be discussed and reviewed in detail below.

Literature Review

The literature review on robotics and AI allows for identifying both of these notions and analyze the facts presented above deeper. The study by Hassabis, Kumaran, Summerfield, and Botvinick (2017) shows that the term AI can be associated with the work in the fields of machine learning and statistics, as well as the technology that helps to build intelligent machines. AI can be defined as the field that uses deep learning methods related to neuroscience that assist scientists in developing neural networks, logical processing systems, and associated algorithms to develop intelligent programs (Hassabis et al., 2017).

Lu, Li, Chen, Kim, and Serikawa (2018) add that AI is a rapidly developing technology that supports individuals’ daily lives and economic activities by helping them to perform regular tasks. Recent AI systems can perform various tasks; one of them is presented in Figure 1. As mentioned above, they can also decode and recognize speech, observe and analyze events, and play games.

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The imagination of realistic environments in deep networks.
Figure 1. The imagination of realistic environments in deep networks (Hassabis et al., 2017).

At the same time, in simple terms, robotics can be identified as the field that designs robots. Robotics can be identified as the field studying the powers of embodied intelligence (Doncieux et al., 2015). Robots are machines that can be programmed and work semi-autonomously or autonomously. Thus, it is possible to say that robots may not have the intelligence to perform their tasks and are presented in some physical form while AI is a program based on particular technologies aimed at performing the functions discussed above.

It is vital to mention that, although being a well-developed technology, AI has some limitations compared to the human brain. For instance, such innovations experience limitations in some intellectual areas, including speech and image recognition, as well as dialogue response (Lu et al., 2018). To resolve these problems, computer scientists develop AI programs that work in individual areas. The techniques they implement include Deep Residual Learning (ResNet) used for visual recognition, Deep Neural Networks (DNN) utilized for speech recognition, and Represent Learning (RL) that improves dialogue understanding (Lu et al., 2018).

Currently, all of these technologies can only work as substitutes for the functions that are performed by different parts of the human brain. It means that at today’s stage of development, AI cannot be compared to the real brain, especially in function like self-motivation, self-consciousness, and self-control (Lu et al., 2018). This point is illustrated in Figure 2 and Figure 3, which compare the functions the brain and AI have. Moreover, AI programs are typically limited to a single type of programs and may encounter difficulties in linking symbols with their meanings. However, the advancements of AI as a field can be applied in project management successfully.

Inventing Moving Sensing Talking Thinking Learning Listening Looking
AI No No No Yes Yes Yes Yes Yes
Human brain Yes Yes Yes Yes Yes Yes Yes Yes

Figure 2. Relative shortages of current AI compared to the human brain (Lu et al., 2018).

The relative number of functions AI and the human brain have.
Figure 3. The relative number of functions AI and the human brain have.

Application in Project Management

It is crucial to mention that AI and robotics can be applied in project management and ensure significant results. For instance, their use can be associated with the increased competitiveness of the organization, as well as improved profits (Wang, 2019). Companies can utilize AI and robotics to analyze the quality of their products, implement natural language processing (NLP) to extract keywords from emails, and complete other routine tasks. The utilization of these innovations can help project managers to have more time for other tasks and goals. The impact of AI and robotics on project management, as well as the examples of applications in this field, will be discussed in detail below.

Impact on Project Management

As mentioned above, the implementation of AI and robotics can have a significant positive impact on project management. For instance, the report by Schmelzer (2019) shows that in the field of project management, there is always a need to interact with several teams at a time, while paying attention to various outgoing projects. This sphere is associated with a high level of optimization and efficiency, which means that it is crucial to implement technologies that can support these goals. In project management, AI programs can be utilized to analyze working teams’ patterns of operation, schedule tasks or meetings, and perform follow-up measures to ensure progress among employees.

It is possible to say that the most significant impact of AI on project management is that they can save individuals’ time by ensuring that no problems and accidentally neglected, navigating communication and cooperation, and optimizing processes within a company.

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The use of robotics can also have a positive impact on project management. However, the robots that do not have AI features may only perform a limited number of tasks. As mentioned above, robots cannot make decisions or analyze the information and the environment around them, which makes them less efficient for project management. Thus, their potential benefits for project management will be discussed in detail below.

Analysis of Brands

One of the brands that use artificial intelligence is Apple, who has designed Siri, a highly popular virtual assistant used on iOS. Siri can be considered an example of AI because it is a voice chatbot or a voice query engine that is able to recognize users’ voices, use NLP to process them, sent queries to databases, and convert text to speech (Hoy, 2018). Siri was first introduced in 2010 and is now available on all Apple devices, including smartphones, computers, laptops, tablets, and watch designed by the company. Today, Siri can search for information and answer users’ questions, make calendar appointments, set reminders, read messages, and complete other required tasks. Moreover, this technology can help individuals to navigate, translate words, and handle payments.

One of the other brands that utilize AI in their technologies is Google. It uses AI in many of its products, including Google Home devices and Google Assistant, presented in Figure 4 (Finley, 2019). Due to the technologies implemented in these devices, they can make the search results more accurate, ensure improved user experience, and offer relevant information to individuals. Moreover, AI allows Google Assistant to analyze consumers’ behaviors, such as the places they typically visit or the activities they prefer based on their location information or searches. AI helps the company to obtain data from emails and events, too, using it to help individuals find the relevant information as soon as possible in the future.

Google Assistant.
Figure 4. Google Assistant (Finley, 2019).

It is vital to mention Boston Dynamics, one of the American brands that work in robotics. One of the products it has introduced is Atlas, which is a humanoid robot that can perform various tasks, including the ones requiring physical and intellectual efforts (Nelson, Saunders, & Playter, 2019). Statistical data reveals that the organization has worked on various types of this robot since 2009, adding at least three new key behaviors with each edition (Nelson et al., 2019). Besides having significant physical powers, the robot can open doors, use human tools and machinery, and handle the unstable ground. Moreover, the technologies used in Atlas allow the robot to analyze sensor data, communicate, and plan tasks.

It is vital to mention that, to create Atlas, the company has utilized the 3D printing technology; some of the parts of the robot are 3D printed. It is vital to mention that AI can also be used for 3D printing as a separate field because it may decrease the possible error humans may make. In the case of Atlas, such a solution has allowed the developers to reduce Atlas’ weight, allowing it to perform a broader number of tasks, such as standing on two legs. The picture of two versions of Atlas by Boston Dynamics is presented below.

Two versions of Atlas built for Robotics Challenge.
Figure 5. Two versions of Atlas built for Robotics Challenge (Nelson et al., 2019).

It is crucial to add that the features of AI and robotics can be combined to create artificially intelligent robots. In such robots, AI programs are embedded onto their systems, which allows them to learn and perform the features pertinent to AI programs and neural networks. The major benefit of combining AI with robotics is that AI systems do not have physical forms, while the utilization of robots can allow people to communicate with them, as well as help such systems to interact with physical objects.

As seen from the example of Atlas above, robots can perform many tasks themselves; however, usually, they can do only the things they are programmed to do. It means that they are limited to the sets of pre-programmed tasks and cannot learn from their environment. At the same time, the implementation of AI can allow robots to act spontaneously, as well as perceive and analyze objects and events. For instance, some of the tasks that AI robots can perform include facial detection, interpretation of the handwritten text, and object recognition. Moreover, such robots are able to follow human commands

Examples and Applications in Project Management

Application of AI in Project Management

As mentioned above, the utilization of AI may play a significant role in improving processes pertinent to project management. One of the features of AI organizations may use is its ability to monitor patterns, assisting project managers. Schmelzer (2019) reports that these employees typically spend more than half of their time on various administrative tasks, including managing updates and check-ins.

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These tasks require much time and usually cannot be performed by other members of the team; however, they may not allow project managers to focus on more significant aspects of their job. In the case of such administrative tasks, AI can be utilized to manage record-keeping and reporting, as well as handling team members’ reports. The implementation of such innovations can help managers to work on more complex goals and interact with the employees more, which can improve their dedication and productivity while reducing budget costs (Schmelzer, 2019).

Another way in which AI can be applied in project management successfully is the use of it for predictive analytics. The utilization of such technologies can allow companies to evaluate the progress of the project and make educated predictions about its future and possible challenges that may be associated with it and that the team should address timely (Schmelzer, 2019). In such a case, the features AI has are more beneficial than humans’ abilities because employees may be overly concentrated on their problems and concerns, neglecting some of the significant shifts in ongoing projects unconsciously.

Moreover, they may not realize the connections between some events and the possible negative outcomes associated with them. At the same time, AI programs are designed to pay attention to all aspects of projects, monitoring available budgets, scheduling, and making predictions. With time, they can learn the links between events and outcomes, identifying potential effects of ongoing processes within projects.

It is vital to add that AI has the potential to monitor employees and make predictions based on the patterns of actions it is able to identify (Schmelzer, 2019). For instance, AI may be utilized to monitor the time employees spend working on various projects and analyze whether there is an opportunity to optimize their operations. AI programs can notify project managers about possible scheduling conflicts due to delays or complexities of tasks and offer suggestions on likely completion dates based on the activities they monitor. To summarize, it is possible to say that AI can benefit project management processes crucially, as they have excellent predicting capabilities and can notify managers about the details they may overlook, while allowing them to spend more time on more urgent and significant tasks.

Application of Robotics and AI Robots in Project Management

As mentioned above, robots, such as Atlas, are typically designed to perform programmed tasks and cannot learn from the environment when AI technologies are not implemented into them. The utilization of robotics itself may be possible in project management for tasks that do not involve non-standard situations or approaches, such as creating invoices and sending them to clients, as well as extracting data from Excel files. Moreover, they can perform physical tasks that humans cannot do; for instance, they can lift and transport heavy goods.

It is possible to say that although robotics without the use of AI may not have such a high impact on project management, their implementation is still beneficial. For instance, they can support 24×7 operation, define target processes even with no or limited technical integration, and replace manual activity (Lamberton, Brigo, & Hoy, 2017). Moreover, the utilization of robotics can be associated with reduced costs, the elimination of human errors, a faster completion rate, and the reduction of possible employee burnout.

It is vital to add that AI robots can also be utilized in project management, and their use may be more feasible that the implementation of robots. Such a combined solution may be beneficial for organizations that require AI programs to interact with physical objects and people, such as the companies working in the fields of social and medical care or farming. However, it is vital to add that for the majority of firms, the use of AI may be more appropriate because there may not be the need to utilize embodied intelligence to perform tasks associated with project management.

Conclusion

The presented report reveals that the primary difference between robotics and AI is that AI is the technology that uses machine learning and associated innovations, while robots are machines that can be programmed to perform particular tasks. Without AT programs, robots cannot learn or act spontaneously because they can only work with pre-programmed data. It is possible to say that both AI, robotics, and their combination can be beneficial for project management; however, the implementation of AI can be considered the most feasible option in this case. The reason for it is that AI can perform various significant tasks, such as monitoring employees, making predictions, and evaluating the progress of ongoing projects. For many companies, there may be no need to use embodied intelligence to perform such tasks. However, the choice of innovation should depend on the goals an organization has, as each of them can be used to improve the project management process.

References

Doncieux, S., Bredeche, N., Mouret, J. B., & Eiben, A. E. G. (2015). Evolutionary robotics: What, why, and where to. Frontiers in Robotics and AI, 2. Web.

Finley, T. K. (2019). The democratization of artificial intelligence: One library’s approach. Information Technology and Libraries, 38(1), 8-13.

Hassabis, D., Kumaran, D., Summerfield, C., & Botvinick, M. (2017). Neuroscience-inspired artificial intelligence. Neuron, 95(2), 245-258.

Hoy, M. B. (2018). Alexa, Siri, Cortana, and more: An introduction to voice assistants. Medical Reference Services Quarterly, 37(1), 81-88.

Lamberton, C., Brigo, D., & Hoy, D. (2017). Impact of Robotics, RPA and AI on the insurance industry: Challenges and opportunities. Journal of Financial Perspectives, 4(1), 8-20.

Lu, H., Li, Y., Chen, M., Kim, H., & Serikawa, S. (2018). Brain intelligence: Go beyond artificial intelligence. Mobile Networks and Applications, 23(2), 368-375.

Nelson, G., Saunders, A., & Playter, R. (2019). The PETMAN and Atlas robots at Boston Dynamics. In A. Goswami & P. Vadakkepat (Eds.), Humanoid Robotics: A Reference (pp. 169-186). Frankfurt, Germany: Springer.

Rajan, K., & Saffiotti, A. (2017). Towards a science of integrated AI and robotics. Artificial Intelligence, 247, 1-9.

Schmelzer, R. (2019). AI in project management. Web.

Wang, Q. (2019). How to apply AI technology in project management. PM World Journal, 8(3), 1-12.

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