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              <text>Designing Artificial Intelligence-Enabled Training Approaches and Models for Physical Disabilities Individuals</text>
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              <text>The focus of this research is on investigating AI-based strategies and models that can be used to develop workforce training systems specifically for individuals with physical disabilities. The goal is to leverage the advancements in artificial intelligence (AI) and its potential impact on workplace learning and development. There is an increasing demand for utilizing AI capabilities to design comprehensive training programs that are both inclusive and effective for people who face physical challenges. The research will examine effective strategies, real-life examples, and current AI-based training platforms for people with physical disabilities. Additionally, it aims to tackle the obstacles and ethical matters linked to incorporating AI in workforce training. These concerns include mitigating biases, ensuring accessibility, and safeguarding privacy. The outcomes of this study will assist in creating progressive approaches and frameworks driven by AI that can empower individuals with physical disabilities by improving their employability prospects while simultaneously fostering inclusivity within workforce training. The chapter will also explore the integration of AI-powered solutions in training programs for physically challenged individuals. By utilizing AI technologies like personalized learning algorithms, predictive analytics, and adaptive content delivery systems, training can be customized to cater to the unique requirements and learning needs of everyone. The implementation of AI has the potential to automate processes, analyze data effectively, and generate personalized learning pathways for improved accessibility.  2024 selection and editorial matter, Alex Khang; individual chapters, the contributors.</text>
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              <text>Gupta C.; Khang A.</text>
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              <text>AI-Oriented Competency Framework for Talent Management in the Digital Economy: Models, Technologies, Applications, and Implementation, pp. 388-415.</text>
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              <text>2024-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1201/9781003440901-24" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1201/9781003440901-24&lt;/a&gt;
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              <text>ISBN: 978-104002225-2; 978-103257605-3</text>
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              <text>Gupta C., School of Commerce, Finance and Accountancy, Christ University, Bengaluru, India; Khang A., Department of AI and Data Science, Global Research Institute of Technology and Engineering, Fort Raleigh, NC, United States</text>
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