Generative AI unlocks innovation in informal economies

A new research sheds light on an unlikely yet potent engine of innovation - the informal economy. The analysis reveals how generative artificial intelligence (GAI), smartphones, and digital infrastructure are creating a self-reinforcing growth loop in developing countries, awakening underused resources and redefining the global innovation map.

The study, titled “The New Paradigm of Informal Economies Under GAI-Driven Innovation,” published in Telecom, investigates how GAI can transform traditionally overlooked informal economies into thriving innovation ecosystems. Drawing from empirical data across 39 countries, including a focused lens on nine African nations, the research unpacks a dynamic framework where smartphones, AI, and the Internet coalesce to fuel economic advancement through “sleeping resources.”

How does digitalization create leapfrogging growth in developing economies?

The study presents a chronological model tracing the evolution from pre-Internet computing to the current generative AI era. It shows that in contrast to the slow infrastructure buildup seen in developed nations, many developing economies are bypassing traditional growth stages - a phenomenon known as "leapfrogging." This shift is enabled by the explosive spread of Internet access and smartphones, which create the foundation for economic participation without extensive fixed infrastructure.

The research identifies a feedback loop in which greater Internet penetration drives smartphone adoption, which then accelerates digitalization. This cycle enables countries with limited physical infrastructure to integrate rapidly into the digital economy. The model is supported by data from 39 countries, showing that smartphone ownership and Internet usage have a statistically significant impact on GDP per capita. Notably, in 2019, the elasticity of smartphone ownership with respect to growth was higher in developed countries, indicating a mature feedback loop, but emerging nations showed rapidly closing gaps in other metrics.

The evidence demonstrates that digitalization fosters a virtuous cycle, particularly in developing nations. This cycle not only enhances access to education, finance, and markets but also generates conditions for innovation by leveraging mobile technologies and cloud-based services.

What are “sleeping resources” and how are they being awakened?

The paper explores a concept called “sleeping resources” - underutilized economic and social assets residing in informal economies. These include youth labor, female participation, untapped land, traditional knowledge, and even data that are often overlooked in formal economic planning. The authors argue that awakening these resources through GAI can drive transformative growth.

A comparative analysis of nine African nations shows varying degrees of success in utilizing these resources. For instance, Kenya and Nigeria demonstrate high engagement with mobile finance and agricultural innovation, while others lag due to limited infrastructure or sociocultural constraints. The study outlines 10 categories of sleeping resources, from geothermal energy and arable land to elderly knowledge and underexploited tourism assets.

The paper presents global case studies to show how similar resources have been revitalized in developed nations through digital transformation—such as Germany’s youth employment initiatives using AI job-matching, Estonia’s data integration systems, and Canada’s use of AR/VR in tourism. These examples underscore how structured digital interventions can unlock growth even in traditionally dormant areas.

How can generative AI drive sustainable and inclusive innovation?

The authors propose a new framework for innovation based on coevolutionary dynamics, using Amazon Web Services (AWS) as a model. Amazon’s approach to R&D, blurring lines between technology and content, and continuously iterating through soft innovation resources, serves as a blueprint. AWS’s integration of user feedback and machine learning has created a self-propagating innovation cycle, where growth drives further innovation and vice versa.

The paper extends this model to propose a global GAI-driven coevolutionary system that fosters inclusive growth. For instance, a suggested Japan-India collaboration model combines Japan’s manufacturing technology with India’s “Jugaad” innovation ethos, an approach emphasizing thrifty, flexible, and inclusive solutions. This, the authors argue, represents the kind of dynamic partnerships needed to scale GAI applications in informal economies.

The report also provides a mathematical model of growth fueled by dynamic carrying capacity, where innovation generates new space for itself rather than hitting saturation. It uses Amazon's data to illustrate how growth in knowledge stocks (via R&D and learning from counterparts) pushes the boundaries of digital value, setting the stage for generative AI to continuously uncover and exploit new opportunities.

GAI, the study suggests, could dramatically reduce the time and cost barriers for local entrepreneurs, artists, and small businesses to enter formal markets. From content generation and financial modeling to language translation and product design, generative tools can equip informal sector actors with capabilities previously reserved for large enterprises. However, for this transformation to succeed, the study highlights three critical prerequisites: improving access to AI-enabling infrastructure, creating datasets that reflect informal economy dynamics, and developing AI-related human capital in emerging markets.