Generating and Analyzing Chatbot Responses using Natural Assignment

Assignment Task

Executive Summary

With advancements in technology, there has been an increase in the development of artificial intelligence (AI) technology. One of the applications of AI is chatbots. Chatbots are made of AI and machine learning to facilitate responses to queries posed by users. As a result, chatbots can be used by firms to automate their customer service. This fastens the service delivery, prevents delays, facilitates personalised service, reduces operational costs and enhances the profitability of firms, leading to its increasing demand and usage. In order to leverage the market opportunities, the present project proposes to develop an AI chatbot as well as an AI platform that generates responses on a variety of topics by using the chatbot. A project team of 10 individuals is developed to support the project. The timeline of the project is 2 years with an estimated budget of $870,000. The project report discusses the project feasibility, resource requirements, scheduling, execution, controlling and monitoring, and handover of deliverables with the project closure.

Project Initiation

Expectations and Outcomes

To leverage the market opportunities, a chatbot is to be developed along with an end-user system that supports the usage of the chatbot. The chatbot will make use of artificial intelligence to enhance its utility among businesses. 

Feasibility

Market

Artificial intelligence (AI) is the ability of computer systems to imitate human intellectual functions. In its simplest form, artificial intelligence combines computer science and large amounts of datasets to facilitate problem-solving. It also encompasses aspects like machine learning and deep learning. AI facilitates the creation of expert systems that classify information or make predictions based on incoming data using algorithms (West and Allen 2018). In the current environment, the best applications of AI are considered an emerging industry. AI development is considered to be an emerging technology in the market. It is increasingly being used in a wide variety of applications, which include self-driving cars, expert systems, machine learning, personal assistants, chatbots and robotics. Moreover, it is also used for language processing and speech recognition. Overall, AI is a multifaceted tool that allows professionals to reevaluate how to combine knowledge, analyse data, and apply the resulting insights to facilitate better decision-making. Consequently, AI is revolutionising several aspects of human life (IBM 2023). 

One of the widely regarded applications of AI is chatbots. A chatbot is a computer program that simulates and understands human interaction, both in spoken as well as written format. This allows interactive communication with digital devices (Dahiya 2017). Chatbots have several applications among business organisations. On the commercial side, chatbots are most typically used in customer service centres to manage incoming interactions and direct clients to the appropriate personnel (Herriman et al. 2020). Moreover, it also assists in routine tasks, like scheduling, training, notifying and other tasks that do not require human support. On the other hand, consumers may use chatbots to ask queries, order tickets, and reserve hotels, among other customer services. As a result, chatbots are extensively used in the banking and retail sector to handle common customer service activities, like submitting requests, responding to inquiries and addressing issues (Herriman et al. 2020).

With a wide variety of uses, chatbots have significant benefits for business organisations and customers. With the advent of digitization, individuals are increasingly becoming reliant on digital tools and gadgets. Thus, chatbots are playing an increasingly important role in this technology-driven transformation. AI conversational chatbots are changing the way that customers and businesses interact. Chatbots allow businesses to communicate with customers without the expense of paying humans to do the same tasks. Thus, businesses can save money and improve operational efficiency by using chatbots, which can offer convenience and added services to both internal employees and external clients. These chatbots reduce the requirement for human interaction while allowing businesses to quickly resolve a variety of customer concerns and issues (Dahiya 2017). Moreover, chatbots provide businesses with the ability to scale, customise and be proactive, thereby enhancing their competitive advantage in the market. Businesses can interact with an endless number of consumers using chatbots, which can be scaled up or down based on demand and operational requirements. Moreover, a company can simultaneously offer a large number of customers fast and personalised support by deploying chatbots (Herriman et al. 2020). Research shows that in comparison to traditional call centres, chatbots used in banking save customers an average of 4 minutes for every query (Oracle 2023). Thus, chatbots can also enhance customer satisfaction and brand loyalty in addition to reducing costs and enhancing operational efficiency for firms.

Market Survey

The utility of chatbots has been increasing gradually over the years. However, the global coronavirus pandemic accelerated the demand for chatbots with various industries realising the need for chatbots. The global market for chatbots was valued at US$0.84 billion in 2022 and is expected to grow with a compound annual growth rate (CAGR) of 19.29% to reach US$4.9 billion in 2032 (Global Newswire 2023).

Competitors landscape

There are several firms that have been involved in the commercial development of AI chatbots. The key competitors in the chatbot market include IBM Corporation, Google, Microsoft, Oracle, Artificial Solutions, Botsify Inc., Acuvate and Amazon (Global Newswire 2023).

Technology

In the past, chatbots were text-based and programmed to provide previously written responses to a select group of simple questions. These chatbots performed effectively for the specific questions and answers, however, failed when confronted with a challenging issue or one that was not involved in the program. Over time, chatbots have integrated more rules and natural language processing to enable conversational interaction with end users. Modern chatbots are able to learn and develop as they are exposed to more interaction with human language. This is done with the help of natural language understanding (NLU), which is a technique used by AI chatbots to ascertain the user's needs. They then employ AI algorithms to ascertain what the user is attempting to do. This technology relies on machine learning and deep learning to build an increasingly detailed knowledge base of queries and responses based on user interactions. This enhances their capacity to anticipate user needs and appropriate responses over time. Thus, the development of AI chatbots requires chatbot architecture, which includes algorithms, AI tools like NLU, NLP engine, and technological infrastructure in the form of servers, backend integration tools and front-end systems that interact with the users (Hingrajia 2022).

Financial

Chatbots can make it simple for users to access the information they need by responding to their questions and requests via text, speech, or both without the need for human assistance. This fastens the response time and provides an opportunity for personalised service. Thus, chatbots can enhance the customer service experience of customers, which improves brand value and brand loyalty. Thus, it can positively influence sales in the market by retaining existing customers and gaining new clients. Moreover, chatbots reduce the need to employ humans while increasing the number of customers handled at a time. As a result, chatbots can reduce the customer service costs of firms by 30% (Singh 2022). Overall, chatbots can increase the revenue and profitability of firms. Consequently, chatbots can save US$11 billion annually for firms operating in the market (Nance 2022). Therefore, it can be stated that it is profitable for firms to use chatbots for customer service, which makes it financially feasible to invest in its development for commercial usage.

Project Stakeholders

In order to highlight the key stakeholders, a stakeholder matrix has been. This matrix divides the stakeholders on the basis of their influence as well as interest in the project. In this matrix, the interest of each stakeholder increases from top to bottom. Moreover, the power of stakeholders to influence the project also increases from left to right. Based on this, the matrix is divided into four groups with high-interest and high-influence stakeholders being most important for the project. On the other hand, low-interest and low-influence stakeholders are the least important for the project.

This Computer Science has been solved by our PHD Experts at My Uni Paper.