Sustainable intensification (SI) is promoted as a rural development paradigm for sub-Saharan Africa. Achieving SI requires smallholder farmers to have access toinformation that is context-specific, increases their decision-making capacities, andadapts to changing environments. Current extension services often struggle toaddress these needs. New mobile phone-based services can help.

This policy brief shows how digital tools can help to ensure that public money for agricul-tural extension is spent wisely. Governments often fund offices, training centers, and the salaries of extension officers, but cannot eas-ily review the impacts of these expenditures. This is because the activities of extension agents are not monitored systematically. Ex-ension services rarely generate quantitative data on the effects of their work.

Agricultural extension in the Global South can benefit greatly from the use of modern information and communication technologies (ICT). Yet, despite two decades of promising experiences, this potential is not fully realized. Here, it is reviewed the relevant research literature to inform future investments into agricultural information services that harness the full potential of digital media.The study describes a recently emerging innovation agenda that is, in part, a response to the eventualfailure of many new agro-advisory initiatives.

This document intends to provide an analysis of the outcomes of the application of the TAP Common Framework in the eight countries of the Capacity Development for Agricultural Innovation Systems (CDAIS) project.  The TAP Common Framework (TAP CF) was developed at the global level as an initial activity of the CDAIS project in order to guide capacity development (CD) and strengthening of Agricultural Innovation Systems (AIS). The project then tested this framework in eight pilot countries (Guatemala, Honduras, Burkina Faso, Angola, Rwanda, Ethiopia, Lao PDR, Bangladesh).

This training manual, which is based on a methodology developed by FAO’s Research and Extension Unit (OINR), presents a training course on assessing AIS consisting of eight modules.