Artificial intelligence adoption dynamics knowledge is a B.Tech project topic for Computer Science & Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
Artificial intelligence adoption dynamics knowledge Project Details
| Abstract |
This project builds an analytical decision‑support system that lets users compare how small and medium enterprises (SMEs) and large organizations adopt artificial intelligence (AI). The system follows the Technology‑Organization‑Environment (TOE) framework and puts into practice ten key dimensions found in the research, such as technology readiness, data needs, financial capacity, and regulatory compliance. It uses natural‑language processing (NLP) and machine‑learning classification algorithms to examine an organization’s profile data. From this analysis the system rates the firm’s AI readiness and flags likely implementation bottlenecks. A bibliometric and text‑mining pipeline pulls trend information from academic papers and industry sources. This gives users data‑driven insight into new AI tools and methods. By sorting
organizations into capability categories and matching them with past adoption patterns, the tool offers concrete advice for planning technology integration. It connects theoretical adoption models with real‑world diagnostics, helping both small and large firms make structured decisions. Interactive visualization dashboards let users benchmark their own firm against industry standards, making it easier to allocate resources efficiently.
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| Reference Paper |
Artificial intelligence adoption dynamics and knowledge in SMEs and large firms: A systematic review and bibliometric analysis |
| Domain |
Artificial Intelligence & Machine Learning |
| Sub-Domain |
Artificial Intelligence & Machine Learning |
| PDF Download |
Download / View PDF |
| Get Help |
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Message: Hi FE, I need help with “Artificial intelligence adoption dynamics and knowledge in SMEs and large firms: A systematic review and bibliometric analysis” in “Artificial Intelligence & Machine Learning”
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