What Will Analytical Science Look Like in 2036? Part One: The AI Age - Summary - MDSpire
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What Will Analytical Science Look Like in 2036? Part One: The AI Age

  • October 14, 2026

  • 7 min

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Objective:

Present expert perspectives on how artificial intelligence may shape analytical science over the coming years.

Approach:
  • Format: A collection of forecasts from researchers and industry scientists, rather than a report of a single study.
  • Topics: Contributors discuss AI in data analysis, experimental design, instrument operation, method development, and laboratory workflows.
Key Findings:
  • Contributors anticipate broader AI integration across analytical science, from instrument development and experiment planning to data interpretation and reporting.
  • Several experts foresee autonomous or lab-in-the-loop systems that use experimental results to guide subsequent experiments and optimize methods in real time.
  • AI-assisted analysis is expected to help interpret complex datasets, including multi-omics and high-resolution mass spectrometry data, and to identify patterns or compounds that may be difficult to detect with traditional approaches.
  • Experts describe structured, shared records of prior experiments as a way to make analytical knowledge more accessible and workflows more reproducible and transferable.
  • Contributors emphasize that scientists will continue to contribute through experimental design, question selection, and scientific judgment in evaluating AI-generated insights.
Interpretation:

The article presents expert expectations, not measured outcomes. Its contributors generally envision AI as integrated into analytical workflows while retaining a role for human expertise and scientific judgment.

Limitations:
  • The material consists of individual expert opinions and forecasts, not a systematic review or empirical study.
  • The supplied context ends partway through Francesca Rigano's contribution, so her full perspective is unavailable.
  • No source URL was provided.

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