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 Scientific Discovery: Transforming Research Methodologies, Knowledge Creation and Innovation

Author(s) Henry Chesbrough
Country United States
Abstract Artificial Intelligence (AI) is increasingly transforming the processes through which scientific knowledge is generated, validated, communicated, and applied. Unlike earlier computational tools that primarily automated specific analytical tasks, contemporary AI systems can assist researchers across multiple stages of the scientific workflow, including literature discovery, hypothesis generation, experimental design, simulation, data analysis, pattern recognition, knowledge synthesis, and scientific communication. The emergence of foundation models, machine learning, deep learning, scientific machine learning, automated laboratories, and AI-assisted simulation has created new opportunities to accelerate scientific discovery while simultaneously raising questions regarding reproducibility, explainability, research integrity, intellectual property, and the role of human judgement.
This study examines the role of AI-augmented scientific discovery in transforming research methodologies, knowledge creation, and innovation. A qualitative and descriptive methodology based on secondary academic literature, scientific publications, institutional reports, and policy documents is adopted. The study analyses AI applications across the scientific research lifecycle, from problem identification and literature review to hypothesis development, experimental design, data interpretation, validation, and dissemination. Particular attention is given to scientific foundation models, automated experimentation, knowledge graphs, predictive modelling, digital twins, and human-AI collaboration. The analysis suggests that AI can improve research efficiency, identify complex patterns, expand hypothesis spaces, and accelerate the transition from data to actionable scientific knowledge. However, AI-generated outputs require rigorous validation because computational systems may reproduce biases, generate incorrect explanations, or identify statistical associations without establishing causality. The study argues that the future of scientific research will increasingly depend on a collaborative model in which AI augments rather than replaces researchers. Responsible governance, transparent methodologies, reproducibility standards, and human scientific judgement will remain essential for ensuring that AI contributes meaningfully to reliable knowledge creation and sustainable innovation.
Keywords Artificial Intelligence, Scientific Discovery, Machine Learning, Research Methodology, Knowledge Creation, Scientific Innovation, Foundation Models, Automated Experimentation, Human-AI Collaboration, Research Analytics.
Field Engineering
Published In Volume 5, Issue 6, November-December 2023
Published On 2023-11-03
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