Building AI Talent in Organizations – An Experiential Learning Approach
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| Publicado en: | Journal of Information Systems Education vol. 36, no. 3 (Summer 2025), p. 277-287 |
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| Outros autores: | , , |
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| Acceso en liña: | Citation/Abstract Full Text Full Text - PDF |
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| 100 | 1 | |a Samuel, Jayarajan | |
| 245 | 1 | |a Building AI Talent in Organizations – An Experiential Learning Approach | |
| 260 | |b EDSIG |c Summer 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Rapid digitization in industries is transforming the way corporations conduct their core businesses and interact with their customers. The proliferation of data in these corporations and the ability to process them using the latest AI/ML techniques are compelling them to transform themselves into data-driven organizations. However, acquiring new talent with data science skills and/or reskilling existing employees with deep domain experience presents a major challenge. In this paper, we illustrate how a unique collaboration between industry and academia to impart AI and machine learning (ML) skills to domain experts contributed to furthering an organization's AI aspirations. Specifically, the collaboration has created a continuous learning environment that is conducive to active experimentation and reflective practice, both of which are essential to gaining actionable business insights. Our methodology can be applied to reskill workforces in the future in transformative new-age technologies while adding value to the organization at the same time. | |
| 653 | |a Teaching | ||
| 653 | |a Students | ||
| 653 | |a Collaboration | ||
| 653 | |a Data acquisition | ||
| 653 | |a Curricula | ||
| 653 | |a Organizations | ||
| 653 | |a Skills | ||
| 653 | |a Machine learning | ||
| 653 | |a Linear algebra | ||
| 653 | |a Case studies | ||
| 653 | |a Research methodology | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Data science | ||
| 653 | |a Experiential learning | ||
| 653 | |a Employees | ||
| 653 | |a Workforce | ||
| 653 | |a Subject specialists | ||
| 653 | |a Algorithms | ||
| 653 | |a Large language models | ||
| 653 | |a Education | ||
| 653 | |a Experiments | ||
| 653 | |a Ability | ||
| 653 | |a Learning environment | ||
| 653 | |a Companies | ||
| 653 | |a Customers | ||
| 653 | |a Data | ||
| 653 | |a Reflective practice | ||
| 653 | |a Consumers | ||
| 653 | |a Business | ||
| 653 | |a Digitization | ||
| 653 | |a Productivity | ||
| 653 | |a Educational Opportunities | ||
| 653 | |a On the Job Training | ||
| 653 | |a Influence of Technology | ||
| 653 | |a Reflection | ||
| 653 | |a Entrepreneurship | ||
| 653 | |a Learning Processes | ||
| 653 | |a Learning Theories | ||
| 653 | |a Observation | ||
| 653 | |a Entry Workers | ||
| 653 | |a Program Descriptions | ||
| 653 | |a Program Development | ||
| 653 | |a Mathematics Instruction | ||
| 653 | |a Reflective Teaching | ||
| 653 | |a Classrooms | ||
| 653 | |a Labor Force Development | ||
| 653 | |a Language Processing | ||
| 653 | |a Professional Education | ||
| 653 | |a Lifelong Learning | ||
| 653 | |a Computational Linguistics | ||
| 653 | |a Programming | ||
| 700 | 1 | |a Nerur, Sridhar | |
| 700 | 1 | |a Mahapatra, RadhaKanta | |
| 700 | 1 | |a White, Brian |u Ericsson Inc. Plano, TX 75024, USA | |
| 773 | 0 | |t Journal of Information Systems Education |g vol. 36, no. 3 (Summer 2025), p. 277-287 | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3252289617/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3252289617/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3252289617/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |