AI models are becoming cheaper, more advanced, and more widely accessible, the constraint on value creation may move downstream – those who hold customer relations, product catalogues, payment infrastructure, culturally specific data could benefit meaningfully. A 2026 IFC and World Bank handbook argues that AI diffusion is spreading faster than previous disruptive technologies, and that emerging markets have an opportunity to avoid legacy infrastructure issues.[1]
Morgan Stanley has described a related shift as ‘agentic commerce’: e-commerce that is initiated or shaped by an AI agent following a customer interaction, thus redrawing where value accumulates across marketing, payments, software, and logistics.
Platforms could monetise AI through three broad routes: improving existing economics, creating new interfaces and enabling AI to execute transactions on a person’s behalf.
Alibaba illustrates all three simultaneously, connecting Qwen models to Taobao and Tmall’s catalogue of more than four billion products, allowing users to search conversationally, compare options and order through an AI intermediary.[1]
Sea offers a Southeast Asian version. Shopee and Google are reportedly building an agentic shopping prototype similar to Alibaba’s idea.[2] Rather than browsing the app manually, a user would describe what they are looking for to an AI assistant, which would search Shopee’s catalogue, compare prices and options, and put together an order for the user to confirm. This coincides with Sea’s financial arm developing agent-enabled payment systems, instead of handing off this part of the experience to a separate app. Thus, Shopee would be able to control a marketplace, the checkout and the delivery network. This is a more durable solution because a standalone chatbot could be replaced by a rival at any point.
Nubank is one of the sharpest fintech examples. It says AI-driven “private banker” functions built into its app now serve millions of monthly users,[3] with its in-house NuFormer foundation models pricing credit and loan applications in near real time. Making underwriting faster and cheaper, rather than simply cutting cost through headcount reduction. Additionally, this trend also fits a broader pattern in Cambridge Judge Business School’s 2026 Global AI in Financial Services Report, which found fintechs lead incumbents in advanced AI adoption, 47% to 30%.[4]
Much of the discourse surrounding AI has been primarily centred around the infrastructure required to facilitate its operation. However, the conversation is moving towards who is positioned to benefit once someone uses it – shopping, advertising, payments and credit infrastructure that emerging-market platforms already have access to. These adaptations do not require companies to become AI businesses in the way a model developer is; it requires them to continue working how they already do, only with a more personalised, cheaper, and faster component working alongside the human layer.
Once more emerging markets present a massive opportunity. India and China continue to show strong GDP growth and rising consumer spending, while ongoing infrastructure investment has lowered the barriers to entry for internet businesses. This combination gives companies access to a large and growing customer base while also allowing them to scale efficiently.
Source: CaixaBank Research. Data as of 16.06.2025. For illustrative purposes only.
While the narrative surrounding the applications of AI is less salient than the capital expenditure being poured into chips and data centres; in order to produce returns, the developments seen across Alibaba, Sea, and others will become increasingly important.
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[1] https://www.ifc.org/en/insights-reports/2026/accelerating-ai-investment-in-emerging-markets
[2] https://www.alibabagroup.com/en-US/document-1991231293551017984
[3] https://www.reuters.com/world/asia-pacific/google-shopee-owner-sea-develop-ai-tools-e-commerce-gaming-2026-02-19/
[4] https://international.nubank.com.br/company/nubank-details-ai-transformation-strategy-built-on-data-foundation-models-and-democratized-financial-advice/
[5] https://www.jbs.cam.ac.uk/faculty-research/centres/alternative-finance/publications/2026-global-ai-in-financial-services-report/
Emerging-market platforms may monetise AI by improving their existing services, introducing new AI-powered tools and enabling AI-assisted transactions. AI can help platforms recommend more relevant products, improve advertising conversion, detect fraud, automate customer support and assess credit applications more efficiently. Platforms may also introduce shopping assistants, financial guidance tools or travel planners. Over time, AI agents could help customers compare products, prepare purchases or complete transactions within predefined limits. Platforms that already control customer accounts, product catalogues, payment systems and delivery infrastructure may be particularly well positioned because they can integrate AI across the entire customer journey.
Agentic commerce refers to shopping journeys in which an AI assistant helps initiate, shape or complete a transaction on a customer’s behalf. Instead of manually searching through a marketplace, a customer might describe what they need and allow an AI agent to compare products, prices and delivery options before presenting an order for approval. This could change where economic value accumulates across online advertising, payments, software, marketplaces and logistics. Investors researching this trend may therefore look beyond AI model developers and semiconductor companies to platforms that already have strong customer relationships, transaction data, payment infrastructure and large digital marketplaces.
Alibaba, Sea and Nubank illustrate different ways emerging-market platforms may apply AI. Alibaba is connecting its AI models with the Taobao and Tmall marketplaces to support conversational product searches, comparisons and purchasing. Sea is reportedly developing AI-assisted shopping through Shopee while also expanding payment capabilities through its financial services operations. Nubank is using AI within digital banking, including personalised financial tools and models that support credit pricing and loan assessments. These examples show how established platforms may use AI to strengthen existing marketplaces, payments and financial services rather than relying solely on standalone chatbots.
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