The way businesses move money is undergoing a major transformation, powered by advancements in AI, real-time payments, and stablecoin technologies. AI is no longer just automating basic tasks; it is enabling intelligent systems that can think, adapt, and optimize financial operations on the fly.

In this episode of ATP, Paul Harapin, Head of Asia Pacific and Japan at Stripe, explains how Stripe’s technology, now processing $1.4 trillion annually, is driving a shift from simple automation to intelligent, adaptive financial systems.

Some of the topics that Paul covered in detail:

• AI is now deeply embedded into Stripe's ecosystem, not just to optimize existing processes like fraud detection, but to reshape entire money flows.
• While generalist AI platforms like OpenAI and Perplexity dominate headlines, AI purpose-built for specific industries is where much of the near-term value is being created.
• Asia Pacific isn't just participating — it's leading the charge into real-time payments and alternative rails.
• How Agentic AI will eliminate traditional bottlenecks between sales, payments, and customer service, especially for SMEs and startups.
• Stablecoins are poised to revolutionize remittances, treasury management, and cross-border B2B commerce, especially in emerging markets.

Building technology at scale is not about chasing the latest trends or making sweeping, one-time decisions. It’s about making a series of careful, long-term choices that prioritize control, efficiency, and resilience. Companies that rush into cloud adoption or AI implementations without understanding the trade-offs risk losing the ability to innovate on their own terms.

Technology leadership is never about a single, bold decision — it’s about a series of intentional, calculated choices that evolve over time. The Asia Tech Podcast sat down with Idan Zalzberg, the Chief Technology Officer of Agoda, to learn how complex technology infrastructures are built, maintained, and reimagined.

Some of the topics that Idan cover in detail included:

• One of the most surprising themes from Idan’s leadership style is his insistence that CTOs should continue to code. Remaining hands-on creates deep trust with engineering teams and maintains sharp intuition for decision-making.
• It’s not about being pro- or anti-cloud. It’s about being in control of your tech stack and cost structures — and re-evaluating continuously.
• To scale AI effectively, companies must build internal capabilities to continuously monitor, measure, and validate AI's impact.
• Rather than replacing engineers, AI is amplifying their productivity — making the best developers even more capable.
• Agoda’s future goal isn’t just to be a booking site — it’s to be a travel companion.

What if the very way we think about money and investments is about to change forever? As we navigate the complex worlds of traditional finance, fintech, and Web3, a provocative question emerges: Should every financial asset be tokenized? Some argue that tokenization brings transparency and accessibility to financial products, especially in emerging markets, while others caution against the blanket application of this technology. Are we on the brink of a financial revolution, or are we simply chasing a trend without fully understanding the implications?

At Onchain 2025 in Bangkok, recorded at the Sofitel So by Michael Waitze, the host of the Asia Tech Podcast, we captured more than 10 conversations that challenged some of the deepest assumptions in finance.

The debates were passionate and layered. Some experts championed tokenization as a force for transparency and accessibility, particularly in emerging markets where traditional systems often fall short. Others urged caution, warning that not every asset — or market — may benefit from being put on-chain.

As we dig deeper into this conversation, the complexities become even more apparent. Is tokenization simply another tool that can empower individuals with greater control over their investments? Or is it a transformative force that could fundamentally disrupt the fabric of traditional finance? While it offers the promise of enhanced liquidity and lower costs, not all assets may be suitable for tokenization. What should be tokenized — and what should remain untouched?

The future of finance may very well depend on how we answer these critical questions.

Are we ready for the financial revolution that 2025 promises?

At Money20/20 Asia in Bangkok, the Asia Tech Podcast, hosted by Michael Waitze, recorded more than 20 conversations with some of the brightest minds in finance and technology. The discussions revealed a clear theme: the future of money is about much more than transactions—it's about trust, sustainability, inclusion, and innovation.

From the rise of green fintech to the integration of AI into real-time financial decision-making, it’s clear that a more sustainable and intelligent financial system is not just on the horizon—it’s already taking shape. Embedding sustainability data into transactions and enabling consumers to “talk” to their money are just a few examples of how rapidly things are evolving.

As traditional banks and fintechs move closer together, the key question remains: will these innovations democratize access or create new barriers? The choices we make today will define the future. One thing is certain—the way we think about money is about to change forever.

Businesses today face a growing challenge: they are generating more data than ever before, yet struggle to make sense of it in a way that drives consistent, effective decision-making. Traditional analytics tools tend to focus on specific functions, leaving teams operating in silos with little understanding of how their choices affect the broader organization. While being “data-driven” was once considered a competitive advantage, it has become a vague and often unhelpful term.

In this episode of the Asia Tech Podcast, Karen Kim, CEO of Human Managed, argues that being "data-driven" is no longer enough. Businesses aren’t suffering from a lack of information—they’re suffering from too much of it, without a clear way to turn that data into meaningful action.

Some of the topics that Karen covered in detail include:

• Decision Intelligence isn’t just about better decisions—it’s about decisions at scale.
• Karen introduced the idea of composite AI, where multiple AI tools and models—LLMs, agents, deep learning systems—are combined to build richer, more nuanced workflows.
• The problem is not access to tools—it’s connecting data to outcomes.
• The shift from data-driven to decision-centric.
• Service design will be the next frontier in AI.

Global supply chains have evolved into highly complex, technology-driven networks that power the movement of goods across borders. These systems rely on precision logistics, data-driven optimization, and seamless coordination between air, ground, and digital infrastructure.

In this episode of the Asia Tech Podcast, Kawal Preet, President APAC at FedEx, shares key insights into how logistics, emerging technologies, and leadership intersect in today’s fast-changing world.

Some of the topics Kawal covered in detail include:

• FedEx isn’t just a logistics giant; it’s an organization deeply rooted in its people-first philosophy, "People-Service-Profit".
• The FedEx network isn't just about physical movement; it's about optimizing routes, reducing transit times, and making data-driven decisions to enhance efficiency.
• Supply chains have evolved significantly over the years, shifting from centralized, thick pipelines to agile, multi-dimensional networks.
• FedEx is embedding AI and digital tools across its entire value chain.
• As one of the largest logistics companies in the world, FedEx has made sustainability a core focus.
• APAC is the future of global trade.

Last-mile delivery has evolved into one of the most important and complex elements of modern commerce. As the final point of contact between a brand and its customer, it directly shapes satisfaction, loyalty, and perception. Today’s consumers expect speed, flexibility, and personalization—often driven by the convenience of same-day or even 10-minute deliveries.

In this episode of the Asia Tech Podcast, Gautam Kumar, co-Founder and CEO of FarEye, breaks down why last-mile delivery is no longer just a logistics function—it’s the final, critical touchpoint in customer experience.

Some of the topics that Gautam covered in detail:

• Last-mile delivery Is the real “storefront” of modern commerce. No matter how amazing your product is, the last-mile experience is what your customers remember.
• Generative AI Is transforming routing and real-time optimization.
• Data-driven delivery is about personalization and prediction. FarEye leverages historical data to optimize delivery attempts.
• Failed deliveries aren’t just costly, they’re environmentally harmful. Every failed delivery means more fuel, more emissions, and added pressure on the logistics system.
• Luxury deliveries will become a differentiator.
• Gen Z and Millennial consumers expect speed, transparency, and sustainability.

The rapid advancement of AI has sparked widespread excitement and speculation, but the real impact of AI goes beyond the initial hype. While AI tools have demonstrated impressive capabilities, the most successful applications come from combining AI with human expertise.

In this episode of the Asia Tech Podcast, we talk to Simon Quirk, co-Founder and CEO of Graceview AI, about what it really takes to build an AI startup in today’s rapidly changing landscape.

Some of the topics that Simon covered in detail include:

• While there may be some overhyped valuations in the AI sector, the long-term potential of AI is undeniable.
• For any startup, identifying a niche and going deep is crucial. This approach not only helps in product development but also in building credibility and trust with early customers.
• Graceview’s approach blends AI with human expertise, ensuring that while AI handles the heavy lifting, lawyers review and validate the output.
• Why being model-agnostic is an advantage. The ability to switch easily between AI models depending on what is best suited for a particular task.
• The importance of curating and validating data over time and building this into a corpus of valuable data.