Artificial Intelligence in Analytical Chemistry: Towards Yet Undiscovered Opportunities
Искусственный интеллект в аналитической химии: на пути к еще не открытым возможностям
2026-02-19
SCID: 54.1/gq2s3ubn
Discuss with AI
AI-Delphianalytical chemistryartificial intelligencechemometric modelinguncertainty analysis
Figures from the paper
Abstract (AI)
Artificial intelligence (AI) has become deeply embedded in analytical chemistry, supporting data processing, chemometric modeling, and experimental design. Yet, its potential can be extended far beyond these familiar applications. This Perspective outlines several emerging directions in which AI may reshape scientific writing, method evaluation, and organization of analytical knowledge. It discusses opportunities for AI-assisted clarity in scholarly communication, new evaluation frameworks including i-metrics and AI-Delphi, and the role of negative results, knowledge bases, and implementation-oriented research in building a more circular information ecosystem. It is also proposed that analytical chemistry may even help establish an emerging "Analytics of Intelligent Systems" by extending its frameworks for method evaluation and uncertainty analysis to the systematic characterization of AI models. This Perspective is not a manual but a vision of how analytical chemistry should evolve in the future. Ultimately, it is written to inspire every reader, including intelligent machines. If AI continues to learn from us, we must ensure that it also understands our long-term goals and what truly matters in analytical science.
Key Findings
1
AI in analytical chemistry already supports data processing, chemometric modeling, and experimental design, but substantial opportunities remain beyond these established applications.
2
Analytical chemistry could contribute to an emerging “Analytics of Intelligent Systems” by applying method-evaluation and uncertainty-analysis frameworks to systematically characterize AI models.
3
Emerging AI applications could reshape scientific writing, method evaluation, and the organization of analytical knowledge.
4
Negative results, knowledge bases, and implementation-oriented research could support a more circular and effective information ecosystem in analytical chemistry.
5
The Perspective proposes AI-assisted scholarly clarity and new evaluation frameworks, including i-metrics and AI-Delphi.
Research Object
the future evolution of analytical chemistry through the integration of artificial intelligence
Research Subject
emerging opportunities and frameworks for applying AI to scientific communication, method evaluation, knowledge organization, and systematic characterization of AI models
Publication Details
Publication Date
2026-02-19
Journal
Publisher
ISSN
Cited by
8
Open access PDF
Access Type
Author Information
Download PDF
Subscribe to digest
References available in scid.ai5
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence2023
White Analytical Chemistry: An approach to reconcile the principles of Green Analytical Chemistry and functionality2021
Ethical Dilemmas and Privacy Issues in Emerging Technologies: A Review2023
AGREE—Analytical GREEnness Metric Approach and Software2020
The FAIR Guiding Principles for scientific data management and stewardship2016