American Journal of Advanced Multidisciplinary Research and Innovation

E-ISSN: XXXX-XXXX   •   Impact Factor: -

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 8, Issue 5 (September-October 2026) Submit your research before last 3 days of October to publish your research paper in the issue of September-October.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 8 Issue 5
September-October 2026

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

AI-Augmented Knowledge Discovery: New Approaches to Interdisciplinary Scientific Research and Innovation

Author(s) Michael A. Cusumano
Country United States
Abstract The rapid expansion of scientific literature, experimental datasets, digital repositories, simulation outputs, and computational resources has created both unprecedented opportunities and significant challenges for interdisciplinary research. Artificial intelligence (AI) is increasingly being used to augment knowledge discovery by identifying relationships across large and heterogeneous information sources, generating research hypotheses, synthesising evidence, predicting emerging trends, and supporting collaborative innovation. This paper examines the emerging role of AI-augmented knowledge discovery in interdisciplinary scientific research and innovation. A conceptual qualitative methodology is adopted to analyse AI-supported literature mining, knowledge graphs, natural language processing, multimodal learning, scientific foundation models, generative AI, automated hypothesis generation, and human–AI collaboration. The study proposes an integrated AI-augmented knowledge discovery framework that connects data acquisition, semantic representation, cross-domain knowledge integration, pattern identification, hypothesis generation, computational validation, expert assessment, and continuous learning. The analysis demonstrates that AI can help overcome disciplinary boundaries by connecting concepts, methods, datasets, and findings that may remain isolated within conventional research structures. However, important challenges include data quality, hallucination, algorithmic bias, explainability, reproducibility, intellectual property, research integrity, and overdependence on automated systems. The paper argues that AI should function as an augmentation layer rather than a replacement for scientific reasoning. The future of interdisciplinary research is likely to depend on effective integration between domain expertise, AI reasoning systems, scientific databases, computational modelling, and human-led experimental validation. Responsible implementation of these technologies can accelerate discovery while preserving scientific transparency, accountability, and intellectual rigour.
Keywords Artificial Intelligence, Knowledge Discovery, Interdisciplinary Research, Scientific Innovation, Generative AI, Knowledge Graphs, Scientific Foundation Models, Natural Language Processing, Human–AI Collaboration, Research Intelligence.
Field Engineering
Published In Volume 6, Issue 3, May-June 2024
Published On 2024-05-02
View / Download PDF File

Share this



E-ISSN XXXX-XXXX
CrossRef

CrossRef DOI prefix of AJAMRI is 10.00000/AJAMRI

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About AJAMRI
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +1-872-302-3851 editor@ajamri.com