AI as a strategic priority for 2025
At Itad, we’ve always been committed to learning and innovation. This year, we’ve taken a bold step forward by making the integration of generative artificial intelligence (AI) one of our strategic priorities. This commitment reflects our belief that AI can enhance how we generate insights, support decision-making, and deliver value to our clients.
From streamlining literature reviews to supporting grant portfolio analysis, generative AI is already helping us work smarter. But our ambition goes further: we want to embed AI into the core of how we design, deliver, and learn from our work.
Why AI, why now?
The rise of generative AI is reshaping industries—and monitoring, evaluation and learning (MEL) is no exception. Our clients are increasingly seeking digital and AI-enabled solutions, and we’re responding by building our capabilities and integrating new tools. AI offers powerful capabilities across the MEL spectrum—from synthesising evidence and analysing qualitative data to supporting strategic foresight and adaptive learning.
But AI is not a silver bullet. It must be applied thoughtfully, ethically, and with a clear understanding of its limitations. That’s why we’ve developed a generative AI policy for staff and suppliers, prepared guidance for staff on how to safely and effectively use generative AI, and ensured that every AI application we use includes a human-in-the-loop to validate outputs and ensure quality.
We’re also seeing growing momentum across the sector. This year, we’re participating in the AI for Good Global Summit, an international platform for sharing ideas on how AI can support the Sustainable Development Goals. It’s an opportunity to learn, contribute, and connect with others who are navigating similar challenges and opportunities.
Opportunities and risks
We’ve seen first-hand how AI can enhance our work—but also where caution is needed. Here’s some of what we’ve learned:
- Accelerating evidence synthesis. In our evaluation of the Fleming Fund, we piloted the use of generative AI to conduct literature reviews. The result? Faster turnaround times and more consistent outputs compared to human researchers.
- Supporting strategic learning. For Mastercard Foundation’s Young Africa Works strategy, we are using Copilot to support landscape analysis and validate emerging themes.
- Improving portfolio analysis. In our work with Wellcome, the Hewlett Foundation and an international HIV prevention initiative, we are using AI tools to analyse large volumes of grant data, applying consistent criteria and surfacing insights for expert review.
- Addressing bias and opacity. In our work with USAID’s Equitable AI Challenge, we identified gender bias in AI tools used in education and developed an ethics guide to help mitigate such risks.
- Avoiding over-reliance on AI outputs. We’ve learned that AI is most effective when it augments—not replaces—expert judgment. That’s why we always ensure human oversight in our AI workflows.
Itad’s expertise: strengthening internal processes through Gen-AI innovation
At Itad, we’re embedding generative AI into the core of our internal operations and delivery processes. A growing group of internal “Gen-AI Champions” is driving this effort—piloting new tools, capturing learning, and helping scale successful applications across the organisation. Here are a few ways we’re developing and refining our internal processes using Gen-AI:
- Organisation-Wide Use of Copilot 365
We’ve rolled out Copilot 365 across the business, integrating it into daily workflows for business development, HR, and project delivery. This not only enhances productivity but also ensures that our use of AI is secure, enterprise-grade, and aligned with best practice. - Theory of Change Development: We’ve embedded Copilot 365 into our internal Theory of Change guidance, helping teams more efficiently map causal pathways and surface assumptions. This strengthens both consistency and quality in early-stage evaluation design.
- Optimal Grants Agent Tool: We’ve developed a Retrieval-Augmented Generation (RAG) tool to support internal workflows around evaluating grants made by an international HIV prevention initiative. This tool helped streamline the extraction of relevant insights from large volumes of documentation—improving both speed and accuracy.
- Online news and social media analysis: Working with a technology partner, Itad has employed machine learning to train an algorithm to classify online news articles and social media posts.
This capability enables our teams to better understand stakeholder sentiment in real time and apply that insight during evaluation design and delivery, as seen in work with the Gates Foundation and British International Investment.
Looking ahead: Scaling innovation and shaping the future
In the second half of 2025, Itad is focused on scaling innovation and deepening our contribution to the responsible use of AI in MEL. Our priorities include:
- Scaling up successful use cases: We are expanding the application of proven AI tools – such as those used for literature reviews, grant analysis, and strategic learning—across more of our projects. At the same time, we are developing new AI applications tailored to emerging client needs.
- Developing a bespoke portfolio analysis solution: Building on our experience with grant portfolio analysis, we are designing a dedicated Itad solution that can be applied across a wide range of projects to support strategic decision-making and learning.
- Partnering with clients to drive efficiency: We are working with clients like the UK Government Foreign, Commonwealth and Development Office (FCDO) to explore how AI can help deliver efficiencies in the face of shrinking aid budgets—ensuring that limited resources are used more effectively and strategically.
- Supporting a more inclusive, responsible AI ecosystem: We are committed to contributing to a global AI ecosystem that is ethical, inclusive, and grounded in evidence. This includes continuing to share our learning, engaging in global forums like the AI for Good Global Summit, and supporting the development of responsible AI practices across the sector.
Let’s collaborate
At Itad, we see generative AI not as a replacement for human expertise, but as a powerful complement to it. By integrating AI thoughtfully and ethically, we can enhance the quality of our work, respond more effectively to client needs, and contribute to a more evidence-informed world.
If you’re interested in collaborating with Itad on the use of AI in MEL—whether you’re a donor, implementer, policymaker or peer—we’d love to hear from you. We’re just at the beginning of this journey and we’re excited about what lies ahead.
