Waves In Startups
Recently, I caught up with an old college friend who invests in Vietnam. After spending the majority of lunch stalking our college crushes on LinkedIn, we spent some time talking about investing.
After our conversation, I’ve come to believe there is alpha in investing in how innovation spreads globally. Essentially, the tech sector almost moves in cycles between phases of global technological breakthroughs and regional innovations that adapt these foundations to fit local needs. This pattern has played out consistently in the past with innovations such as the internet and mobile, with each cycle generating over 100 billion in combined market value.
Fast forward a decade, AI models have attracted over $40 billion dollars of investment in 2023 alone, which leads me to believe that we are again at the cusp of phase one and its advancement of foundational technology. Soon, as these platforms mature, opportunities for regional adaptations will emerge, setting the stage for another phase two.
A Lesson From History:
First, let’s take a step back and look at the past. The early 2000s saw the emergence of a once-in-a-generation technology in the Internet. Platforms like Amazon revolutionized retail by building infrastructure for e-commerce, growing from $2.8 billion in sales in 2000 to over $74.5 billion by 2013. Their innovation in logistics, digital payments, and marketplace dynamics created the blueprint for the online commerce we know today. Uber launched in 2009, and transformed transportation by pioneering real-time ride matching and dynamic pricing, reaching a $50 billion valuation by 2015. Paypal established the foundations for digital payments, processing $578 billion dollars worth of payments by 2015, mainstreaming online transactions.
Yet, as these platforms expanded globally, they faced complex market realities. Amazon’s 2013 entry into India came with a $5 billion investment commitment. However, they struggled with unexpected challenges in India’s cash-heavy economy and complex geography. this created an opening for Flipkart, which built on Amazon’s e-commerce foundation with their own cash-on-delivery network that reached 97% of India’s postal codes, for beyond what existing Amazon infrastructure supported. Their unique rural distribution network extended to 27,000 pin codes, supported by a collective funding model for rural entrepreneurs. Following Amazon’s footsteps, the company pioneered India’s first customer loyalty program with "Flipkart Plus," tailoring e-commerce for local shopping habits. These innovations led Flipkart to capture 31.9% of India's e-commerce market by 2018, culminating in a $16 billion acquisition by Walmart.
On the flip side (pun most definitely intended), Uber’s expansion into the Southeast Asia market reveals a similar pattern. After investing $700 million in the region between 2013 and 2015, they struggled to gain traction. Grab, understanding local transportation dynamics, built on Uber's foundation while adding a crucial adaptation: bikes. Their GrabBike service, launched in 2014, grew to 300,000 motorcycle drivers by 2018, addressing the region's unique transportation needs. The introduction of GrabPay in 2016 transformed the company into Southeast Asia's largest digital wallet by 2020. They established driver training centers in 150 locations and developed a super-app model integrating food delivery, payments, and other essential services. These innovations helped Grab achieve 72% market share by 2018, leading to Uber's exit from the region in exchange for a 27.5% stake in Grab.
In Africa, PayPal's traditional digital payment model faced infrastructure limitations. M-Pesa transformed this challenge into opportunity by building a network of over 200,000 local agents for cash handling. Their simple SMS-based interface worked on basic feature phones, making digital payments accessible to millions without smartphones. By integrating with local savings groups and microfinance institutions, M-Pesa processed $314 billion in transactions in 2021, demonstrating how regional adaptation can unlock massive market potential.
Re-entering Phase one:
Today, the landscape of AI development mirrors these earlier cycles. OpenAI's ChatGPT reached 100 million users within two months, establishing new paradigms for human-AI interaction. Google's investment in AI has exceeded $30 billion since 2015, while Microsoft committed $10 billion to OpenAI alone. These investments are creating the foundation for AI applications globally.
As these platforms mature, regional opportunities will be sure to emerge. Different regulatory frameworks will be sure to create distinct AI environments across regions: The EU's AI Act mandates transparency and accountability, China requires data localization and government oversight, and India's draft regulations emphasize data sovereignty.
Early movers are already positioning themselves for regional adaptation. Vernacular.ai (now Skit) secured $23 million in Series A funding to develop voice AI for Indian languages. Their technology covers 22 languages and 160 dialects, achieving 85% accuracy in mixed-language conversations while optimizing for low-bandwidth voice operations common in emerging markets. Sarvam AI, with $41 million in funding, is developing India-focused foundation models with built-in support for 11 Indian languages. Their technology optimizes for edge computing devices and ensures compliance with Indian data protection laws, demonstrating how regional players can adapt global AI advances for specific market needs. across the pond, France’s LightOn is developing AI solutions specifically designed to meet the stringent requirements of European data privacy laws (like GDPR) and regional industry needs in sectors like banking and defense. In Africa, CDIAL is pioneering conversational AI for previously underserved African languages. Where global models like ChatGPT and IBM Watson typically lack support for indigenous African languages, CDIAL is building solutions that bridge this crucial linguistic gap. Smartcat secured $43 million in Series C funding to develop AI-powered localization tools that go beyond simple translation, helping businesses adapt their content both linguistically and culturally for diverse regional audiences.
The Road Ahead:
Global technological innovation followed by regional adaptation will always be a consistent pattern. While global platforms create new fundamental possibilities, finite resources and focus will always create opportunities to transform these foundations to better serve local needs. With AI, the potential for regional innovation may be even greater, given the technology's broad applicability and the increasing importance of local data sovereignty and cultural context. As the technology matures, regional regulations will only differentiate themselves more.
For entrepreneurs and investors, understanding this pattern provides strategic insight. While global AI development continues to attract attention, I believe the next wave of opportunities will emerge from companies that can effectively adapt these foundations for specific markets, use cases, and cultural contexts. :)