Posted: April 12th, 2022

Artificial Intelligence

Artificial Intelligence
Computer Sciences and Information Technology

Artificial Intelligence
1. What are the three types of artificial intelligence applications?
There are three types of artificial intelligence applications that include process automation, cognitive insight, and cognitive engagement.
2. What is an RPA? What are its benefits and issues?
RPA entails both physical and digital tasks that incorporates the robot process automation technologies (Davenport and Ronanki, 2018). In this regard, the tools used in performing automated financial and administrative activities function like men taking information and consuming it from various systems thus enabling tasks to be performed.
Furthermore, RPA has a wide range of benefits in the various applications it is incorporated. In this case, RPA is the easiest and least expensive cognitive technology that can be employed in various fields. Moreover, brings high and quick returns upon making investments. The RPA generates a lot of revenue to the business and other fields it is employed thus increasing the profit levels. More so, the RPA is flexible and it can be changed and advanced with time. In this respect, the application can be approved with time by adding learning and intelligence capacity with time.
Lastly, the issues arising from the application of RPA in various activities are that the application will put a lot of people out of work. The application makes people jobless but this was not the primary intention of employing the RPA.
3. What type of problems can Cognitive Insight solve?
The cognitive insight application can be used to address various problems based on its ability to use the algorithm to establish patterns and give an interpretation of their meaning (Davenport and Ronanki, 2018). In this case, the problems solved entail the elimination of redundancies in contracts thus ensuring that businesses pursue contracts easily. Additionally, cognitive insight has been employed in improving job performances on jobs done by machines. Moreover, the cognitive insight has been used to handle huge databases in banks and for audit purpose and simplifying them making work easier.
4. What is the use of cognitive engagement applications?
The cognitive engagement is used in conducting various activities that include engaging customers, employees and the public using intelligent agents, natural language processing chatbots and machine learning (Davenport and Ronanki, 2018). In this regard, intelligent agents give 24/7 customer service by addressing various arising issues, internal sites answering queries, and giving treatment recommendation based on the status of a patient as well as previous treatments.
5. What technology is needed for the AI application mentioned in the article?
The technology needed for the application of AI is robotic process automation and rule-based expert systems (Davenport and Ronanki, 2018).In this case, before the application of the technology organizations need to consider limitations, strengths, and types of the task involved to evaluate if they are implementable.
6. What steps are needed for implementing these technologies?
The implementation of technoloigies is done in steps to increase the chances of success (Davenport and Ronanki, 2018). In this respect, the first step entails the identification of opportunities that business and other activities would realize in using such technologies. In these considerations, the opportunities are established by analyzing and evaluating bottlenecks involved in the flow and distribution of information, challenges that can be solved by incorporating the technology and availability of firepower. Consequently, one establishes the use case to acknowledge the areas and positions to employ the technology to realize business success and substantial value from the technology. Furthermore, one moves to select the appropriate technology to use in addressing the various task in the organization. In this case, one may opt for intelligent agents, chatbots or other relevant application. Moreover, the organization moves to launching pilot projects on the chosen technology to establish the success levels and if they are viable. This fact enables the company to make a decision if to continue with the projects or not. Finally, the business implements the technology if they are viable and improves it from time to time by scaling it up.

References
Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard business review, 96(1), 108-116.

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