DB FPX 8720 Assessment 3

DB FPX 8720 Assessment 3 Business Project Idea- Developing a Business Study Student Name Capella University DB FPX 8720 Professor Name Submission Date   1.1 Introduction The use of artificial intelligence (AI) in the analysis of large volumes of data is transforming the way that industries are operating and changing the employment dynamic in today’s digital world, while also improving productivity. The ability to analyze huge datasets at a rapid pace and with high accuracy, offering businesses more insight for better decision-making and creatively exploring solutions, is another key benefit of AI integration. For example, AI’s ability to analyze large volumes of data can enable companies to make predictions, streamline supply chains, and tailor their services to individual users, all of which can give them an edge. As revealed in Jada and Mayayise’s study, the level of productivity that can be gained from implementing AI in data analytics is up to 40%, which is truly a transformative opportunity. As effective big data analysis becomes more crucial, AI technologies are essential for businesses to maximize their benefits, thereby changing job descriptions and boosting productivity. 1.2 Problem of Practice The general challenge is that organisations with a big data analysis theme are struggling to fully realise the value of big data because of the complexity and quantity of the data, and are not making optimal decisions and therefore missing opportunities. It is a problem that can manifest itself in many industries and sectors, impacting businesses, the health care sector, educational institutions, and more. Adversity faced is manifested as inefficiencies, increased expenses, and failure to take advantage of opportunities for innovation and development (Kulkov et al., 2023). While artificial intelligence (AI) can definitely benefit big data analysis, it’s difficult for many organizations to effectively make use of AI technology. The issue is that while U.S. businesses have access to all this big data, they don’t know how to use the right skills and strategies to adopt AI into their processes, leading to the inefficient use of data and loss of productivity. It is felt especially in the sectors where making decisions is highly reliant on data, e.g., finance and health. 1.3 Gap in Practice Today, numerous organisations find themselves battling the challenges of massive amounts of data and are unable to make the best use of the skills and intelligence that AI technologies offer. This leads to sub-optimal use of the data, higher costs and lost opportunities to innovate and grow – in many cases, these businesses lack appropriate methods and strategies with regard to efficient data usage. In today’s scenario, where organizations are facing challenges with the inability to fully leverage the capabilities of big data without AI integration, the problem lies in the lack of proper AI integration. Businesses or healthcare service providers find it difficult to effectively make data-informed decisions and thus experience poor performance metrics and less competitiveness. The desired state is a future where these entities have fully embraced AI in their data analytics workflows, seamlessly analyzing data to generate actionable insights, improve decision-making, and fuel organizational growth and success. The gap in practice is between the actual struggles with the integration of AI and the potential for optimized use of data. 1.4 Purpose of the Project and Project Questions Purpose The team needs to include a purpose and a set of questions. The team should have a purpose and project questions. Qualitative inquiry project aims: Explore case study approach and skills that will help business leaders in the United States to effectively incorporate artificial intelligence (AI) into their big data analytics processes. Through the identification and understanding of these strategies and skills, the project will help close this gap in practice by ensuring that data is used more effectively and improving productivity in industries that are heavily reliant on data, such as Finance and Healthcare. This study will employ a case study approach to gain more in-depth knowledge from business leaders who have been successful in implementing AI in their data analysis. Project Questions What are business leaders’ specific skills that they feel they need to be successful with the integration of AI in their big data processing? What strategies have business leaders been able to employ that have proven effective in tackling the challenges of incorporating AI into big data analysis? 1.5 Preliminary Terms and Definitions Artificial Intelligence (AI): AI, or artificial intelligence, is intelligence exhibited by machines, which, like humans, are capable of learning and making informed decisions. In big data analytics, AI helps automate processes, augment data analysis, and create insights that can assist in better decision-making and operational efficiency. Big Data Analytics: Big Data Analytics is the ability to analyse these large and varied datasets or “big data” to discover information, including hidden patterns, correlations, market trends, and customer preferences. This information can prove useful to companies to aid them in making business decisions that are informed, and boost productivity and efficiency. Data-Driven Insights: Data-driven insights are worthwhile insights that can be gained from studying data, and they assist in making well-informed business decisions. Insights from patterns and trends within the data sets can help a lot in the decision-making process. These insights can be improved by AI’s capacity to take data into account and analyse it more effectively, as it’s able to process huge amounts of data more efficiently (Oncioiu et al., 2019). 1.6 Project Justification The intended project is to combine artificial intelligence with big data analysis to improve leadership development in organisations. This project has identified a need highlighted in practitioner and scholarly literature that explores the need to harness AI tools to manage and analyze vast amounts of data in today’s business landscape. The amount of information organizations are collecting has never been greater, and it’s no longer possible to rely on conventional data analysis techniques to cope. AI can greatly enhance decision-making and leadership development initiatives by analyzing and comprehending vast amounts of information. The emphasis on business leaders is important because they are key decision makers when it comes […]