However, leveraging the automated benefits of homegrown AI technology alone will not suffice. Countries, regardless of where they fall on the development divide, need to confront the impending foreboding of AI replacing jobs. The threat is particularly disastrous to labour-intensive sectors of the economy such as manufacturing, customer service, and even education, potentially replacing millions and leaving them jobless. This will lead to added woes to the state of developing economies – almost nullifying the effects of investing in and adopting AI. Thus, the challenge for developing countries is twofold – to foster a homegrown AI that optimises national growth without feeding on domestic jobs.
Need for an inclusive global economy
To better contextualise the challenge, it becomes important that we recognise the existing inequalities between developed and developing countries. Most developing countries today only possess basic digital infrastructure that allows for smooth transmission of information through access to the internet or telecommunication services. However, this basic infrastructure is neither adequate to incentivise sustained investments on innovation from global giants, nor capable of equipping the youth with the necessary competencies and exposure to cultivate homegrown AI solutions or utilise existing ones – a complete contrast to established economies which have already laid the groundwork for an AI-driven economy.
This existing inequality results in the further widening of the digital divide between developed and developing countries, as the latter lack the adequate resources to leverage the benefits that AI offers across multiple sectors of the economy – optimising outputs, minimising costs, and eventually creating the optimal supply chain for businesses. Moreover, a lack of resources in these countries – energy and human, in particular – does not aid the rapid expansion of national digital infrastructure that is necessary to keep up with the swiftly widening divide.
One solution to bypass these regional incompetencies is deliberate international collaboration to establish robust digital infrastructure, which would function as a foundation for the skill development of the workforce in these developing countries, subsequently resulting in the integration of AI into everyday economic transactions, eventually creating a local AI ecosystem. Additionally, global policy frameworks aimed at collective development of digital infrastructure – such as the ASEAN digital masterplan 2025 – not only enable countries to create a shared pool of resources that helps with national development but also help create an integrated and cohesive global digital economy. Hence, a resilient national digital infrastructure that is inclusive, future-oriented, and aligned with global systems is key in the creation of an inclusive AI-powered future.
Need for a versatile workforce
To combat what seems like the inevitable event of AI replacing jobs, it is imperative that governments across the globe invest in reskilling and upskilling their workforce, incorporating modules on AI, data management, and other technical skills that would help in an economy powered by AI. However, it is not only the government’s responsibility to upskill youth. While technical know-how now becomes an essential in classrooms across educational institutions, it is also the responsibility of leaders and managers to upskill their employees, as exemplified by corporate giants like TCS, Infosys, and Wipro, which have expressed their commitment towards the upskilling of thousands of employees in AI and other technical skills through comprehensive training programmes. Furthermore, student upskilling programmes, like Ericsson’s ‘Connect To Learn’ initiative, where the tech-giant has offered upskilling of almost 485,000 students in fields such as AI, Machine Learning (ML), Internet of Things (IoT) etc across 43 countries, further underlines the importance of private players in evolving the youth. The principle behind it is that a skilled workforce would help in augmenting traditional methods of transactions through the integration of AI, instead of being replaced. Moreover, A BCG study done in 2019 – a time where generative AI models were non-existent – estimates that almost two-thirds of workers globally are aware of the incoming disruptions in their fields and are willing to reskill to retain their positions, indicating positive will from the workforce that further underscores the pressing need for the implementation of upskilling or reskilling programmes. Additionally, in developing countries, there should be provisions for public access to AI, especially in rural areas. This means either the development of AI-compatible infrastructure through shared devices and localised AI models that are built subject to different contexts or developing community-based tech mediation, where skilled youth support their communities in the use of AI to optimise growth and solutions at a micro-level. This can be achieved through partnerships with rural cooperatives or schemes targeted at achieving rural literacy of AI.
As AI strides in with the potential of restructuring the entire landscape on which the foundations of the current global economy was built on, it is especially critical for emerging economies to adapt to this evolving topography – through targeted policies that focus on localised innovation, international cooperation that aims to build an inclusive economy, and responsible skilling of youth who can adapt to and thrive in an AI-driven world – if there are any aspirations to harness the benefits of the ongoing digital revolution.
(Amit Kapoor is chair, Institute for Competitiveness and Praveen Senthil is a Business student at Rotterdam School of Management, The Netherlands).
