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We write as qualitative researchers to respond to the open letter opposing the use of generative artificial intelligence (GenAI) in reflexive qualitative research (Jowsey et al., 2025a). We believe that rejecting the technology in its entirety risks closing off methodological evolution, misunderstanding current practices, and isolating qualitative research from broader epistemic developments. We therefore advocate for a position grounded in critical engagement, methodological literacy, and...

AI’s role in evaluation: so long and thanks for all the synthesis How generative AI can enhance evaluation and analysis? We share three real-world case studies to explore what works, what doesn’t, and how to harness AI responsibly. Generative AI is everywhere—but is it really the answer to Life, the Universe and Everything? At Itad, we see AI as a powerful assistant, not a replacement for human judgment. Our new learning brief, The evaluator’s guide to generative AI, shares lessons from...

This blog by Jonathan Kuhn-Patrick (UK Evaluation Society Trustee and AI Working Group Lead) explores the five emotional stages many evaluators experience as they begin working with AI.

Quality assurance strategies when working on unfamiliar topics

The Digital Justice Network produced a guide that originated from the realisation that civil society organisations and activists need help in establishing generative AI policies and properly utilise these tools when necessary. “Some of our activists are drafting statements with ChatGPT, and I’m worried about what approach we should take.” Many organisations are likely having similar concerns. With the emergence of various generative AI services—such as chatbots like ChatGPT and Gemini, and...

This practical guide from the UK Evaluation Society explores how evaluators can use AI tools responsibly and transparently across all stages of the evaluation process.

Despite an emerging body of scholarship on applying generative AI (GenAI) to qualitative data analysis, this area remains underdeveloped. This article evaluates how GenAI can support thematic analysis using a publicly available interview dataset from Lumivero. It introduces Guided AI Thematic Analysis (GAITA), an adaptation of King et al.’s (2018) Template Analysis. This framework positions researchers as a reflexive instrument and intellectual leader while thoroughly guiding GPT-4 in four...

The CGIAR 2030 Research and Innovation Strategy commits organizational change with seven ways of working, including “Making the digital revolution central to our way of working”. In that context, Artificial Intelligence (AI), introduces both opportunities and risks to evaluation practice. Guided by the CGIAR-wide Evaluation Framework, integrating AI tools requires a governance approach to balance innovation with ethical responsibility, ensuring transparency, fairness, accountability, and...

One of the main questions evaluators have when using AI is: "How can I know if it performs well?" To answer this question, we have developed a guidance note aimed at capturing what we have learned so far about integrating AI into evaluation and to offer a framework for further exploration. Since we began our experiments with Large Language Models (LLMs) in the Spring of 2023, we have made significant progress in using Generative Artificial Intelligence (GenAI) for processing and analyzing...

This article presents an artificial intelligence-assisted causal mapping pipeline for gathering and analysing stakeholder perspectives at scale. Evidence relevant to constructing a programme theory, as well as evidence for the causal influences flowing through it, are both collected at the same time, without the evaluator needing to possess a prior theory. The method uses an artificial intelligence interviewer to conduct interviews, automated coding to identify causal claims in the...

Generative AI (GenAI) is evolving rapidly, and its use in violence against women research remains new and largely experimental. While researchers are beginning to explore GenAI’s potential, uncertainty around its risks, ethical challenges, and real-world application persists. Recognising the need for clear guidance, the Sexual Violence Research Initiative (SVRI) partnered with The MERL Tech Initiative (MTI) to develop this resource. This guide aims to provide background on GenAI, strengthen...

Artificial Intelligence and Evaluation: Emerging Technologies and Their Implications for Evaluation is a groundbreaking exploration of how the landscape of program evaluation will be redefined by artificial intelligence and other emerging digital technologies. In an era where digital technologies and artificial intelligence (AI) are rapidly evolving, this book presents a pivotal resource for evaluators navigating the transformative intersection of their practice and cutting-edge technology....

**A New York Times Bestseller**'Co-Intelligence is the very best book I know about the ins, outs, and ethics of generative AI. Drop everything and read it cover to cover NOW' Angela DuckworthConsumer AI has arrived. And with it, inescapable upheaval as we grapple with what it means for our jobs, lives and the future of humanity.Cutting through the noise of AI evangelists and AI doom-mongers, Wharton professor Ethan Mollick has become one of the most prominent and provocative explainers of...

AI already is being used in some areas of process improvement, and the usage of this technology — including generative AI — promises to grow. That’s because it can perform tasks faster and much less expensively than humans alone. But it will never fully replace people — and that poses management challenges.

“Hacking by the prompt”—writing simple yet creative conversational instructions in ChatGPT's message window—revealed many valuable additions to the evaluator's toolbox for all stages of the evaluation process. This includes the production of terms of reference and proposals for the dissemination of final reports. ChatGPT does not come with an instruction book, so evaluators must experiment creatively to understand its potential. The surprising performance of ChatGPT leads to the question:...

Large language models (LLMs) are a type of generative artificial intelligence (AI) designed to produce text-based content. LLMs use deep learning techniques and massively large data sets to understand, summarize, generate, and predict new text. LLMs caught the public eye in early 2023 when ChatGPT (the first consumer facing LLM) was released. LLM technologies are driven by recent advances in deep-learning AI techniques, where language models are trained on extremely large text data from the...

While many knowledge workers may fear that the rise of artificial intelligence (AI) will threaten their jobs, this article argues that small evaluation businesses should embrace AI tools to increase their value in the marketplace and remain relevant. In this article, consultants from a research, evaluation, and strategy firm, Intention 2 Impact, Inc., make a case for using AI tools to disrupt business as usual in evaluation from theoretical and practical perspectives. Theoretically, AI may...

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