7 global development roles that are being transformed by AI

Artificial intelligence’s impact on development work was already well established heading into 2025, from streamlining daily operations and simplifying data analysis to more advanced applications such as predictive analytics and health diagnostics. “AI has already altered roles like M&E specialists, project managers, and policy analysts, especially by augmenting human capabilities, automating repetitive tasks, and enabling data-driven decision-making,” Bart Édes, a development professor of practice at McGill University, said. But the widespread uncertainty resulting from the U.S. aid crisis has made it difficult to assess what the relationship between AI and development work might look like today had the U.S. Agency for International Development maintained its critical role in the sector. “With so many global development jobs now eliminated, it's hard to say how some roles would have evolved in a healthy, stable sector alongside AI integration,” said Joel Levesque, a veteran development consultant and author of the “Job Search with AI” newsletter on Substack. While there are currently fewer jobs in development, there appears to be no regression in AI’s usage by sector professionals. According to a survey conducted by the Humanitarian Leadership Academy and Data Friendly Space in May and June, 70% of humanitarian workers are regularly using AI tools. “There’s widespread individual adoption of AI, or at least a strong interest in it,” Levesque said, adding that in his assessment of the sector since the U.S. aid cuts, “business development is where the shift [to AI] is most visible, [but] AI is quietly transforming workflows across every role where it's allowed.” As in other sectors, AI integration poses risks and creates new challenges for development professionals, experts told Devex. There are ethical and environmental concerns, as well as the possibility that optimized productivity leads to lower headcounts in resource-strapped organizations. However, there’s also hope that AI’s promise will extend far beyond the mere enhancement of productivity. “Too many roles in global development are over-reliant on under-resourced, overburdened professionals. If we do this right, AI can help us build institutions that are more dignified and efficient,” Anwulika Ngozi Okonjo, a digital innovation strategist, said. As AI continues to reshape development work, Devex spoke to experts who have been tracking the trend to identify the roles undergoing a significant transformation. Business development and proposal writing Proposal writers are already utilizing generative AI tools, including the Grant Assist platform, to draft early bids, draw on previous submissions, and synthesize technical language. “I think AI, and particularly generative AI, is beginning to change the landscape of grant writing and business development in both NGOs and development consultancies,” Jack Jarrett, an international development HR adviser, said. He highlighted AI’s ability to rephrase proposal sections to align with different donor tones, which should differ between humanitarian donors and private foundation donors. According to Levesque, the fallout from the U.S. aid crisis has led to proposal teams utilizing AI even more. “Organizations are under intense pressure to bring in new work, which means they’re submitting more proposals than ever, and many of these proposals are for unfamiliar sectors, making existing boilerplate language less useful,” Levesque said. “As a result, teams are scrambling to create more customized content on tight timelines.” Monitoring and evaluation Monitoring, evaluation, and learning roles have been at the forefront of AI adoption in the development space, with work evolving from early ChatGPT experimentations to more advanced applications. “With AI tools now able to automate survey analysis, detect anomalies, and even write impact reports, the work becomes less about mechanics and more about uncovering and translating the story the data is telling,” Okonjo said. Jarett also anticipates that monitoring and evaluation roles will become more strategic. “M&E professionals will need to interpret insights, ensure data integrity, and address bias in these automated systems,” he said. Program and project management Many in the sector have started to demonstrate a more adaptive, data-driven approach to program and project management, using predictive analytics and other AI-based tools. These tools are making it possible to anticipate project outcomes and identify risks, including conflict outbreaks, climate disruptions, and operational bottlenecks. While AI’s ability is advancing, Jarrett said successful integration with project and program work will still depend heavily on human quality assessment. “AI won't replace the human elements that are crucial to successful development programs, so program staff will continue to play a vital role in searching AI-generated insights, tailoring intervention to social context, and navigating complex stakeholder dynamics,” Jarrett said. Policy analysis Decision-makers are leveraging AI-enabled, data-driven support systems to simulate policy impacts, forecast risks, and inform resource allocation. Édes cited Google’s Flood Hub as an example. It combines geographic information systems with predictive analytics to anticipate and model flood risks. Okonjo believes AI will continue to significantly reshape roles in policy design. “Policy advisers will increasingly use AI to model outcomes, or even generate synthetic data to guide decisions where real-world data is scarce,” she said, referring to the ability to artificially create data that mimics the characteristics of real-world datasets. This synthetic data can then be used in training AI systems to predict hypothetical outcomes. However, Okonjo also emphasized the importance of human oversight and analysis to fully leverage AI’s usefulness in policy analysis. “The ability to question, interpret, and align these outputs with political and social realities will be the differentiator, not the tech itself,” she said. Internal communications and knowledge management For those managing institutional knowledge and internal communications, AI is being used to summarize team meetings, organize internal documentation, tag content, and even suggest strategy language, Levesque said. “As long as people can navigate the privacy factors, it's a powerful tool,” he added. This is especially relevant for junior professionals or administrative staff, who are more likely to be responsible for internal knowledge workflows, because it can automate tasks such as data entry, research, and first draft writing. “I think it's going to leave space for junior staff to contribute more strategically and analytically,” Jarrett said. Research For researchers, AI tools can scan hundreds of academic papers, synthesize findings, and even suggest research questions based on gaps in the literature. “The focus is shifting from collecting data to vetting it, structuring it, and knowing how to question it and use it,” Levesque said. “If you know how to use AI well, you can save hours — if not days — in the research process.” Given that generative AI tools can sometimes confidently produce inaccurate results, especially when users are not using best prompting practices, Levesque stressed that “the quality of research is directly influenced by the level of understanding of AI tools.” Media and communications Generative AI tools are helping communications professionals craft messaging strategies, frame advocacy narratives, and shape an organization's public voice. It can be especially useful in assisting multilingual communication, an area that is often underresourced, according to Jarrett. “Professionals are now going to need to spend more time editing, fact-checking, and rewording outputs, rather than perhaps translating from scratch,” Jarrett said. “Rather than replacing translators or communication professionals, I think these tools are reshaping their role, from being language converters to becoming quality controllers.” Okonjo agreed that what AI lacks in applying context to these tasks needs to be offset by a communication professional’s ability to preserve nuance and authenticity. “Across all of these roles, we’re seeing a shift from execution to orchestration, from doing tasks to designing better systems, validating outputs, and curating the human judgment that matters most,” she said.