Conference Agenda

Introduction

Rwanda aims to become a digital economy leader in Africa, leveraging digitalization to "leapfrog" from an agrarian to a service-driven economy. While digitalization has the potential to accelerate economic transformation and close employment gaps, its impact on job quality and inclusivity remains unclear. Despite Rwanda’s strong policy ambitions, structural barriers—including a large informal sector, persistent skills mismatches, and uneven digital adoption—limit the extent to which digitalization is generating decent and equitable employment opportunities.

Research questions

This study examines the extent to which Rwanda’s service-led digital transformation is being realized. It investigates:

1. How digitalization affects the intensity and composition of tasks and skills across occupations and sectors.

2. Whether digital job creation reduces inequalities or reinforces existing labour market disparities.

3. How employment policies can better align with digital skill development and workforce needs.

Methodology

The study introduces a novel task-based approach to measuring digitalization in employment, applying the Occupational Information Network’s (O*NET) digital intensity classification to Rwanda’s Labour Force Survey over a five-year period. Unlike conventional sector-based classifications, this method provides a granular assessment of digital task penetration across all sectors. Additionally, time-trend analysis evaluates mobility patterns among workers in digital-intensive jobs. Qualitative insights from ICT employers and job-seekers in six “high-potential” districts (Kamonyi, Musanze, Kirehe, Rwamagana, Huye, and Gasabo) complement the quantitative findings.

Findings

Initial findings reveal that digitalization is reshaping job composition as workers in digital-intensive jobs experience greater mobility across sectors and occupations. However, low skilled, rural based and informal workers are experiencing more limited transformations due to limited internet adoption, inadequate digital training and gender disparities. While Rwanda has achieved widespread mobile network coverage, only a small proportion of workers actively engage in the digital economy, signalling a gap between digital access and actual usage.

Contribution to literature

This study challenges the common assumption that digitalization is inherently equalizing, highlighting how its impacts vary across different economic and social contexts. Current research on digitalization mainly examines employment impacts in advanced economies, overlooking its effects in developing countries like Rwanda. Moreover, existing studies often rely on sector-based classifications, neglecting the task-based dimensions of digital work. This study offers a more granular approach to measuring digitalization in employment. It provides new insights into job transitions, evolving skill requirements, and persistent structural barriers in digitally transforming economies. It bridges political economy and labour studies by examining how digital transformation interacts with employment policies.

Introduction

The launch of AI tools, especially ChatGPT, represents a major turning point, fostering widespread adoption across diverse fields. While AI offers enhanced efficiency, it also poses risks to cognitive development, particularly through overreliance among youth. Relying on AI for basic tasks such as remembering, understanding, and applying knowledge hinders higher-level cognitive functions like analyzing, evaluating, and creating (expertise paradox). Excessive dependence on AI also limits Gen Z's ability to think creatively (innovation paradox). Additionally, AI disproportionately benefits experts, leaving novices at a disadvantage (equity paradox). The meta-cognitive illusion, created by AI's use, leads youth to believe they possess more skills than they truly do. Collectively, these AI paradoxes are contributing to the deskilling of youth, with potential negative impacts on the global economy, including a widening gap between high and low-skilled workers, wage inequality, economic instability, and rising crime rates. There is a lack of studies on youth deskilling due to AI overexposure, globally and particularly in India. In this context, the study aims to answer research questions: “Are AI paradoxes deskilling the youth?” and “Can AI paradox awareness reduce AI overdependence triggered deskilling?”

Methodology:

312 post-graduate university students from West Bengal, India were surveyed for this study using a structured questionnaire. The ‘Overreliance on AI’ indicator was constructed to evaluate the extent of deskilling. Simple statistical tools and regression analysis were for the analysis. In the second phase, an experimental study with 85 students, divided into treatment (made aware of the AI paradoxes and associated deskilling) and control groups, examined the impact of awareness intervention on reducing AI overdependence.

Findings:

The study signals a rising overreliance on AI, contributing to deskilling in key areas like writing, idea generation, critical thinking, research, and problem-solving which underscores the AI overdependence-induced deskilling (prevalence of innovation and expertise paradox). Many students fall into the meta-cognitive illusion, misattributing AI content as their own. Factors such as socio-economic and demographic background, tech familiarity, perceived AI effectiveness, and academic pressure, peer effect, easy accessibility etc. affect the AI overdependence. However, the study finds that raising awareness of the AI paradox can help reduce overdependence and safeguard essential skills.

Contribution:

This article advocates for the requirement and the ways of integration of specific policies (such as AI paradox awareness) to deal with AI paradoxes-induced de-skilling in the AI governance policies of different countries to address the potential wage inequality in the future and ensure social justice.

Understanding the significance of skills development and its impact on people’s lives is essential for designing effective policies that enhance labour market outcomes. While existing literature has extensively examined how changing skill demands affect workers’ vulnerabilities in high-income economies—particularly in the U.S. (e.g., Autor 2022; Atalay et al. 2020)—there remains limited knowledge about how skill supply and demand have evolved in other regions. This gap is particularly evident in emerging economies, where there is scarce evidence on which skills, or skill bundles, are most strongly associated with better employment and firm outcomes.

This paper seeks to bridge this gap by developing a comparative analysis of skill endowments and their evolution over time. A major challenge in studying skills is the availability of appropriate data. To address this, we leverage a newly constructed framework for measuring skills, enabling a systematic assessment of skill supply and demand across multiple countries. We focus on selected emerging economies with available big data from online job vacancies and applicant profiles.

First, we provide a descriptive overview of skill endowments, separately analysing the demand and supply sides. We categorize skills into 15 subcategories and assess how they are described in job postings and applicant profiles using textual analysis techniques (NLP), including word clouds that visualize the key expressions defining each skill. Second, we conduct a dynamic analysis of the evolution of skill requirements and observed skill supplies over time, utilizing time-series data to track trends across different countries.

To further understand the composition of occupational skill profiles, we construct detailed skills profiles based on applicant data from job boards, exploring whether different groups of workers systematically exhibit distinct skill offerings. We then assess skills gaps across countries where data on both supply and demand is available. Importantly, we examine whether possessing a particular skill mix (supply side) or requiring certain skill combinations (demand side) predicts future skills trends.

Finally, we investigate the relationship between various skills and labour market outcomes, including both wages and non-wage amenities, using big data methods for causal inference. By analysing cognitive, socio-emotional, and manual skills, and their 15 subcategories, we uncover significant variations in returns to skills across different economies. Our findings highlight the importance of tailored skills development policies that address country-specific challenges and opportunities, shedding light on the bundles of skills that enhance workers’ labour market transitions and improve job quality throughout the life cycle.

The world of work is undergoing profound transformations driven by rapid advancements in digital technology. Over the past decades, breakthroughs in digital tools and automation have redefined industries, reshaping labour markets worldwide. In this context, workers' ability to adapt and remain resilient has become increasingly dependent on their skills. However, while prior research has examined the employment effects of digital technologies, most studies focus on developed economies, leaving a critical gap in our understanding of these dynamics in low- and middle-income countries. Moreover, the role of skills in shaping labour market outcomes amid digital transformations remains underexplored.

This paper addresses these gaps by providing new empirical evidence on two key dimensions: (i) the impact of exposure to digital technologies on employment across countries at different income levels, and (ii) the role of specific skills in mediating these effects. Our analysis relies on the TechXposure measure developed by Prytkova et al. (2024), which quantifies global exposure to 40 emerging digital technologies. To estimate the causal impact of digital exposure on employment, we employ an instrumental variable shift-share approach, combining industry exposure scores from the TechXposure database with baseline employment shares at the first subnational level. The analysis covers 50 countries, drawing on labour force and household surveys from the ILO microdata repository.

To examine the mediating role of skills, we integrate big data from online job vacancies sourced from a job board in Uruguay. Using a skills taxonomy and empirical approach from Escudero et al. (2024), we construct subregional measures of occupational skills composition. These measures are then interacted with our subregional exposure indicators to assess how specific skills mitigate adverse employment effects or enhance positive outcomes associated with digital transformation.

Our findings provide crucial insights into the heterogeneous labour market impacts of digital exposure across different economic contexts. We find that the effects of digital transformation on employment vary significantly by country income level and pre-existing workforce composition. Moreover, certain skills—such as digital literacy, problem-solving, and adaptability—play a crucial role in buffering against job displacement while enhancing access to emerging job opportunities.

These insights contribute to policy discussions on lifelong learning and workforce development, emphasizing the need for targeted skill-building initiatives. By identifying the skill sets that enable workers to navigate digital disruptions, this research informs strategies for fostering inclusive, adaptive labour markets in an era of rapid technological change.

This research examines differences between women and men in terms of training opportunities and wages over the Covid-19 Pandemic in the UK, using lagged event analysis of longitudinal data (UKHLS). Within this approach, training and wages are viewed through an occupation and gender segregation lens, constraining the notion of individual preference, career commitment or self-selection. Building on research from Luchinskaya & Dickinson, 2019, this theory delineates between non-skills and skills-related functions of training, as well as considering the quality and participation of training to capture more multifaceted and detailed aspects of in-work skills development opportunities (Green et al., 2016). Covid-19 disruptions are grouped into two major forms: (1) employment-status related (furloughed, laid-off and reduced hours workers), and (2) the remote versus key, frontline or essential workers divide. This theory hypothesises that workers in the employment-status group suffered a ‘stagnation’ of skills, and lower wages in the long-term as a result of reduced training opportunities compared to those in regular employment able to work from home. While the second group did not see long-term wages suffer, they received less skills-related training as a result of Pandemic-related pressures. Instead, we test the hypothesis that these key workers undertook more perfunctory or non-skills-related training, mainly due to new health and safety regimes. Finally, compounding effects from existing labour market discrimination, segregation, and Pandemic home-schooling/child-care pressures, accumulate resulting in reduced skills-related training opportunities for women.

The data is treated as repeated cross-sectional individual-level data, from 2017 to 2022. The methodological approach is a quasi-experimental design, in which treatment groups (key workers and furloughed workers), are compared to control groups (those in regular employment and not in the other treatment groups), overtime, comparing pre- and post-Covid. We use firstly linear probability models to assess inequalities in terms of access in to training, and lagged linear models to estimate the long-term effect of training (or lack thereof) on wages.

Our preliminary findings are that there a key differences between key worker men and women in terms of accessing training during the Pandemic, and the long-term impact of skills and non-skills-related training on subsequent wages (scarring effects). Secondly, we also observe that these findings intersect with childcare responsibilities, in which women are more negatively affected than men.