Artificial Intelligence

With the rise of accessible and affordable AI tools, many fields—including evaluation—are jumping on the bandwagon and testing them out. These tools are now helping to replace, support, or enhance tasks that were once done solely by people (Nielsen et al., 2024). As a result, they are opening up new possibilities for how evaluations are conducted.

Recent research offers several examples of how AI can contribute to evaluation practice:

• AI transcription tools can speed up the capture and analysis of qualitative data (Ziulu et al., 2024).
• AI-powered chatbots can help reach populations that are often excluded from traditional surveys or interviews (Bruce et al., 2024).
• Drones and geographic information systems (GIS) can provide new types of data for evaluators (Anand et al., 2024).

So far, most published work on AI in evaluation is conceptual or exploratory. It tends to highlight potential benefits and risks in specific settings, but there hasn’t yet been a broad look at how AI tools are actually being used in practice. Some researchers have called for more investigation in this area (Rinaldi & Nielsen, 2024).

Understanding how widely AI is used—and what opportunities or risks it brings—can help improve both current evaluation practice and future research. Our project aims to describe the current use of AI in evaluation across Canada and the United States. We will do this through a survey of evaluation practitioners in both countries.