Will AI replace monitoring and evaluation officer jobs?

Monitoring and evaluation officers face a high AI disruption score of 70/100, but replacement is unlikely. AI will automate routine data tasks—entry, dataset creation, and basic analysis—but cannot replicate the role's core functions: stakeholder engagement, ethical judgment, systems thinking, and strategic programme evaluation. The occupation will transform, not disappear.

How will AI change the monitoring and evaluation officer role?

The 70/100 disruption score reflects a bifurcated risk profile. Vulnerable areas (57.24/100 skill vulnerability) cluster around data mechanics: maintain data entry requirements, create datasets, manage quantitative data, and perform routine analysis. AI excels here—automating data pipeline tasks and generating statistical summaries. However, the role's resilient core—ethics, stakeholder engagement, systems thinking, and SDG alignment—remains distinctly human. The Task Automation Proxy of 50/100 indicates roughly half of daily tasks can be delegated to AI tools. Near-term: AI will handle data processing, freeing officers for higher-value work. Long-term risk emerges only if organizations eliminate evaluation altogether, not from AI capability. The 68.31/100 AI complementarity score is instructive—AI enhances data analysis, survey design, and forensic data gathering when paired with human oversight. Officers who adopt AI as analytical partner rather than threat will strengthen their strategic value.

High Risk

monitoring and evaluation officer

Q: What skills does a monitoring and evaluation officer need to stay relevant with AI?

Key skills for monitoring and evaluation officer in the AI era include: perform data analysis, apply statistical analysis techniques, use specific data analysis software, survey techniques, gather data for forensic purposes. These are areas where AI augments human capabilities rather than replacing them.

Monitoring and evaluation officers are responsible for the conceptualisation, design, implementation and follow-up of the monitoring and evaluation activities of projects, programmes, policies, strategies, institutions or processes, along the relevant programming cycle. They develop monitoring, inspection and evaluation methods and instruments needed to collect and analyse data, and report on results by applying structured M&E frameworks, theories, approaches and methodologies. M&E officers inform decision-making through reporting, learning products or activities and knowledge management. They can also engage in capacity development activities by providing training and capacity building support within their organizations or for clients and partners.

ISCO 2422Explore this role

57

Skill Vulnerability

Impact: Now

50

Task Automation

Impact: 1–3 years

68

AI Enhancement

Impact: 5+ years

How AI Will Change This Role

Expected Impact Timeline

Near-term (1-3 years)

AI tools already augmenting 30-50% of routine tasks. Early adopters gaining productivity edge.

Mid-term (3-7 years)

Significant task automation expected. Role will evolve — fewer positions, higher skill requirements.

Long-term (7-15 years)

Role substantially transformed. Remaining positions require AI management skills + deep domain expertise.

Expected Salary Impact

↘

Downward salary pressure expected as AI automates key tasks

Job Demand Outlook

↘

Fewer openings expected as AI handles core tasks

Tasks Most Likely to Be Automated

⚠maintain data entry requirements
⚠create data sets
⚠manage data
⚠manage quantitative data

Tasks That Will Remain Human

✔ethics
✔engage with stakeholders
✔sustainable development goals
✔systems thinking

Skills to Develop for AI Resilience

perform data analysisapply statistical analysis techniquesuse specific data analysis softwaresurvey techniquesgather data for forensic purposes

⚠ Most Vulnerable Skills

maintain data entry requirements88%

maintain data entry requirementsUphold conditions for data entry. Follow procedures and apply data program techniques.

create data sets85%

create data setsGenerate a collection of new or existing related data sets that are made up out of separate elements but can be manipulated as one unit.

manage data82%

manage dataAdminister all types of data resources through their lifecycle by performing data profiling, parsing, standardisation, identity resolution, cleansing, enhancement and auditing. Ensure the data is fit ...

manage quantitative data82%

manage quantitative dataGather, process and present quantitative data. Use the appropriate programs and methods for validating, organising and interpreting data.

perform data analysis78%

perform data analysisCollect data and statistics to test and evaluate in order to generate assertions and pattern predictions, with the aim of discovering useful information in a decision-making process.

Exposure

✔ Most Resilient Skills

ethics25%

ethicsThe philosophical study that deals with solving questions of human morality; it defines and systemises concepts such as right, wrong, and crime.

engage with stakeholders32%

engage with stakeholdersUse a variety of processes that result in mutually negotiated agreements, shared understandings and consensus building. Build partnerships within the work context.

sustainable development goals32%

sustainable development goalsThe list of 17 global goals set by the United Nations General Assembly and designed as a strategy to achieve a better and more sustainable future for all.

systems thinking32%

systems thinkingThe integrated approach to understanding how various constituents of a system interrelate, interact and influence one another within a whole logistic system.

communicate with stakeholders38%

communicate with stakeholdersFacilitate communication between organisations and interested third parties such as suppliers, distributors, shareholders and other stakeholders in order to inform them of the organisation and its obj...

Exposure

✨ AI-Enhanced Skills

perform data analysis82%

perform data analysisCollect data and statistics to test and evaluate in order to generate assertions and pattern predictions, with the aim of discovering useful information in a decision-making process.

apply statistical analysis techniques82%

apply statistical analysis techniquesUse models (descriptive or inferential statistics) and techniques (data mining or machine learning) for statistical analysis and ICT tools to analyse data, uncover correlations and forecast trends.

use specific data analysis software82%

use specific data analysis softwareUse specific software for data analysis, including statistics, spreadsheets, and databases. Explore possibilities in order to make reports to managers, superiors, or clients.

survey techniques80%

survey techniquesTechniques on how to identify a target audience, choose the right survey method and analyse the data.

gather data for forensic purposes80%

gather data for forensic purposesCollect protected, fragmented or corrupted data and other online communication. Document and present findings from this process.

AI Boost