Health Evaluation TIG Week: Leveraging AI to Draw Conclusions and Develop Actionable Recommendations by Jenna Murrow and Lauren Toledo

Date: Saturday, July 19, 2025

Hello, we are Jenna Murrow and Lauren Toledo, from Deloitte’s Evaluation and Research for Action (ERA) Center of Excellence (CoE), writing on behalf of the Health Evaluation TIG. Thanks for joining us this week to hear about how our evaluators are using AI applications throughout the evaluation process! Today, we’ll explore ways that AI, in general, can be used to draw conclusions and develop recommendations to drive action.

Triangulating and making sense of your data can be a challenging step of an evaluation, especially when dealing with a variety of sources or large volumes of information. Sometimes, you might feel “too close” to the data and struggle to identify the clear story. These challenges can prolong timelines and can limit the ability to promptly inform decision-making. To help navigate this, we are exploring how AI can enhance the way that evaluation data is interpreted and communicated.

By using AI to develop dashboards, visualizations, and conduct predictive modeling, you can efficiently identify insights to develop conclusions and recommendations. Next, we’ll dive deeper into some of these benefits and some tools that could be used.

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• Dashboarding: As evaluators, dashboards can play a crucial role in helping to monitor and evaluate a program or project’s progress. With AI, dashboards can be customized to your needs, updated in real time, and made to display key program metrics that can help us understand the program impact and make decisions. AI algorithms can automate the integration of data from multiple sources into a dashboard and include text summarization and pattern recognition, which helps evaluators and other stakeholders engage with the data to make decisions.
• Data Visualization: AI can quickly analyze large amounts of data to develop and update visualizations in real-time, such as the automatic generation of charts or graphs. These can be customized to one’s needs to identify trends and patterns, explore different program scenarios, or share relevant insights with stakeholders. AI visualizations help us easily analyze and interpret findings, making them especially beneficial for conveying evaluation outcomes or informing decisions to drive change.
• Predictive Analytics: Predictive analytics is powerful in analyzing historic data to provide insight into future trends and outcomes, such as program effectiveness or resource allocation efficiency, which can enable evaluators to proactively anticipate opportunities and address potential challenges. Predictive analytics has the capability to predict at-risk areas or populations and then suggest tailored solutions that address specific program needs. By bringing a forward-looking perspective, predictive analytics can be essential in strategic planning and having responsive program management.
• Organizing Evidence for Recommendations: AI can help to structure and cluster conclusions based on strength of evidence, relevance to interest holders, and alignment with program goals, helping evaluators more clearly link data to specific, actionable recommendations.

While AI can efficiently draw conclusions and develop recommendations, it is not a substitute for human sensemaking. As in any evaluation, you’ll need to engage interest holders to interpret your findings and develop useful and culturally relevant recommendations. Using AI in the final stages of an evaluation has the potential to make work more efficient and creative, but the key to ethical and transparent evaluation lies in thoughtful integration of these technologies rather than automating judgment.

How have you used AI to develop recommendations and conclusions? What tools would you recommend? Drop them in the comments below! 

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The American Evaluation Association is hosting Health Evaluation TIG Week with our colleagues in the Health Evaluation Topical Interest Group. The contributions all this week to AEA365 come from our Health Evaluation TIG members. Do you have questions, concerns, kudos, or content to extend this AEA365 contribution? Please add them in the comments section for this post on the AEA365 webpage so that we may enrich our community of practice. Would you like to submit an AEA365 Tip? Please send a note of interest to AEA365@eval.org. AEA365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators. The views and opinions expressed on the AEA365 blog are solely those of the original authors and other contributors. These views and opinions do not necessarily represent those of the American Evaluation Association, and/or any/all contributors to this site.