The growing use of artificial intelligence in professional environments has placed an expanding set of tools at the disposal of researchers, consultants, and monitoring and evaluation teams. Among the most widely known are ChatGPT, Claude, Perplexity, and Gemini — platforms that offer different functionalities and address distinct needs.
Rather than searching for a single tool capable of handling every task, the recommended approach is to select a solution based on the work to be done. Content creation, review of lengthy documents, information research, and integrated work with files and applications may each require different capabilities.
ChatGPT for creation, analysis, and automation
ChatGPT emerges as a tool particularly suited to content creation, data analysis, production of visual materials, and automation of repetitive tasks.
In the context of monitoring and evaluation, it can be used to draft briefings, templates, checklists, training materials, emails, and social media content. It can also support the exploration of datasets, the synthesis of survey results, and the creation of tables.
Additional applications include the production of infographics, diagrams, and other visual resources, as well as the creation of customised assistants for specific tasks such as report review or data quality checking.
Claude for lengthy documents and in-depth analysis
Claude is presented as a particularly suitable option for work involving extensive documents, complex reasoning, qualitative analysis, and report review.
Possible applications include checking the consistency between findings, recommendations, and evidence; synthesising terms of reference and evaluation matrices; and analysing interview notes or existing literature.
The tool can also support the review of theories of change, enabling users to identify assumptions, knowledge gaps, and weaknesses in causal logic, as well as to organise themes and compare interview findings.
Perplexity focuses on research and sources
When the primary need is to search for up-to-date information and identify sources, Perplexity is presented as one of the options to consider.
The tool can be used for documentary research on sectors, policies, and national contexts, as well as for gathering references for evaluation projects, methodological notes, and evidence syntheses.
It can also support research on evaluation methods and standards, and the analysis of recent changes in specific areas of public policy.
Gemini integrates with the Google ecosystem
For teams that conduct much of their work through Google Workspace, Gemini offers a different approach, with integration into tools such as Gmail, Google Drive, Docs, Sheets, and Slides.
Within an evaluation context, it can support the location and synthesis of documents stored in Google Drive, the analysis of emails, the identification of next steps, and the preparation of responses.
The tool can equally be used to analyse indicators in spreadsheets, assist in the preparation of reports, and develop content for documents, presentations, and meetings.
A choice that depends on the task
A comparison of the four tools points to different areas of application. For creation or automation tasks, ChatGPT is the suggested option; for review, reasoning, and in-depth analysis, Claude; for research and source identification, Perplexity; and for tasks integrated into the Google ecosystem, Gemini.
In practice, an evaluation project may draw on more than one of these solutions. A possible workflow involves using Perplexity to locate sources and current guidance, Claude to review the logic and evidence in a report, ChatGPT to create tables or visual materials, and Gemini to work with files stored in Google Drive.
The human factor remains decisive
Despite the range of possibilities offered by AI tools, their use requires care — particularly when participant, partner, or organisational data is involved.
Highlighted best practices include not entering confidential information into tools without authorisation, ensuring human validation of evidence and interpretations produced by AI, and using sources that allow information to be traced and verified.
The guidance also points to avoiding generic, automatically generated content, and ensuring that reports continue to be grounded in concrete evidence, clearly identified limitations, and actionable recommendations.
Ultimately, rather than seeking a single tool to address every need, the use of AI in monitoring, evaluation, and research may be best served by combining different solutions, each chosen according to the nature and objectives of the task at hand.
Source: Diário Económico
Original article: https://www.diarioeconomico.co.mz/?p=545677
