Published by Jessica Weisman-Pitts
Posted on September 17, 2024
7 min readLast updated: January 29, 2026
Kirill Iaroshenko
By Kirill Iaroshenko, Senior Management Consultant and Expert in AI Investments
Emerging markets are often viewed as the underdogs in the global economic landscape, but the rapid adoption of artificial intelligence (AI) is turning this narrative on its head. These regions are not just following in the footsteps of developed nations; they are forging new paths with AI technologies that have the potential to leapfrog traditional development stages. However, there’s more to AI than meets the eye: while generative AI (GenAI) is making headlines with its transformative impact on content creation and customer engagement, machine learning (ML) and traditional data analytics continue to play a critical role in optimizing financial operations, risk management, and market predictions. In this article, we explore how both GenAI and traditional AI models are revolutionizing investment strategies in emerging markets, assess the AI maturity of key regions, and examine the opportunities and challenges that lie ahead.
AI’s role in emerging markets spans from traditional ML applications to more cutting-edge GenAI use cases. While ML focuses on analyzing historical data to predict future outcomes, GenAI, a subset of AI that generates new content and solutions, is revolutionizing sectors that rely on personalized customer interactions, creative outputs, and dynamic problem-solving.
Generative AI Use Cases: GenAI excels in areas requiring creative and conversational abilities, such as virtual assistants, automated content generation, and personalized customer interactions. In Southeast Asia, for instance, GenAI is powering chatbots and virtual financial advisors that help millions of users access financial services without the need for human intervention. In the Middle East, companies are leveraging GenAI to provide dynamic customer support, automate legal document drafting, and generate market analysis reports, enhancing client engagement and operational efficiency.
Traditional AI (Machine Learning and Data Analytics): Meanwhile, ML continues to dominate tasks that require processing large volumes of structured data, such as fraud detection, algorithmic trading, and predictive analytics. In Kazakhstan and Uzbekistan, for example, ML is critical in enhancing stock market efficiency and risk management, allowing financial institutions to analyze market trends in real time.
Emerging markets face unique challenges when adopting AI technologies. One significant hurdle is the lack of skilled AI professionals, which can limit the implementation of more sophisticated GenAI applications. Additionally, the regulatory landscape in many of these regions is still evolving, which can create uncertainty for investors and businesses looking to deploy AI at scale.
To capitalize on the growing AI landscape in emerging markets, investors need to adopt a nuanced approach that considers both GenAI and ML opportunities. Here are some strategies for investors looking to make the most of this AI-driven transformation:
AI’s impact on emerging markets is multifaceted, encompassing both the transformative capabilities of GenAI and the foundational strengths of traditional ML. As these technologies continue to evolve, they will redefine investment strategies, enabling investors to tap into high-growth opportunities in regions that were once considered too volatile or underdeveloped.
The convergence of government support, entrepreneurial innovation, and technological advancement is setting the stage for a new era of AI-driven growth in emerging markets. Investors who recognize this potential and are willing to engage with the complexities of these dynamic regions will be well-positioned to reap significant rewards.
By balancing traditional AI models with the creative power of GenAI, emerging markets are not just catching up—they are pioneering the future of global investment. The key lies in understanding the unique characteristics of each market and leveraging AI’s full spectrum of capabilities to unlock new pathways to success.
Generative AI refers to a subset of artificial intelligence that focuses on creating new content and solutions, such as text, images, or music, based on learned patterns from existing data.
Emerging markets are economies that are in the process of rapid growth and industrialization, often characterized by lower income levels and higher volatility compared to developed markets.
An investment strategy is a plan designed to guide an investor's decisions on how to allocate resources in order to achieve specific financial goals.
Risk management involves identifying, assessing, and prioritizing risks followed by coordinated efforts to minimize, monitor, and control the probability or impact of unfortunate events.
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