When we talk about technology leadership, it’s easy to get caught up in visions of bold breakthroughs — the kinds of inventions that promise to change everything overnight. But the history of business tells a quieter, often overlooked story: Winning doesn’t always require inventing the future. It often involves perfecting the present, even when the work seems boring and unsexy.

Jeffrey Ding’s Technology and the Rise of Great Powers offers one framework for understanding this dynamic. Ding argues that in geopolitics, diffusion and adaption often matter more than invention itself in the rise and fall of great powers. While he focuses on international history, the underlying insight extends much further. In business and investing, too, success often doesn’t come from being the first to invent, but from being the first to scale practical adoption across sectors, habits, and daily life. Three sharp examples, across mobile payments, retail, and AI, illustrate this principle in action.

Alipay Tap! vs. Apple Pay

The mobile payments sector offers a vivid example of how diffusion — not invention — drives success. Ant Group’s Alipay Tap! didn’t invent anything fundamentally new. It layered near-field communication technology onto China’s already dominant QR code payment system. The result was simple but powerful: A cheap NFC sticker called “the Tap! Tag” — instead of new hardware — cut transaction times to less than two seconds, down from five to 10 seconds for QR scanning. Context did the rest, with a population already habituated to mobile payments and a regulatory environment pushing for a cashless economy. In just 11 months, Alipay Tap! crossed 100 million users.

Meanwhile, Apple Pay followed a different path. It engineered a tightly integrated NFC system tied to a secure element chip and biometric authentication. Technologically, it was a clean-sheet design — sleek and secure. But adoption was slower and more expensive: Merchants needed NFC-enabled point-of-sale terminals, which can cost up to $850 each, depending on features. Consumer habits in the U.S. also proved sticky, with many continuing to use physical cards or cash.

Apple Pay bet on elegance, privacy, and vertical control. Alipay Tap! bet on speed, low cost, and cross-platform accessibility. Both succeeded — but one scaled explosively, by aligning with behavioral norms and existing infrastructure. It’s small tweaks grounded in real-world behavior, like those adopted for Alipay Tap!, that are delivering outsize impact through rapid, broad-based application.

Amazon Go vs. Walmart Self-Checkout

Retail offers another vivid case in which diffusion made the difference. Amazon Go launched in 2018 with futuristic ambitions: a cashier-less shopping experience powered by computer vision, sensor fusion, and deep-learning AI. Shoppers would scan their Amazon apps at the entry, pick up items, and simply walk out, with the system automatically charging their Amazon accounts. Early projections were lofty: Amazon was reported to target 3,000 stores by 2021.

Reality proved more challenging: As of 2023, Amazon Go had expanded to just 43 locations. Consumer awareness remained limited; only 28 percent of U.S. consumers had ever visited an Amazon Go store, according to Piplsay surveys. Recently, Amazon pivoted to licensing its “Just Walk Out” technology instead of adding more Go stores directly.

Meanwhile, Walmart pursued a far less glamorous approach, scaling already established technology — self-checkout kiosks — across thousands of stores. By 2021, 30 percent of U.S. grocery transactions ran through self-checkout lanes, with Walmart as a clear leader.

However, scaling self-checkout wasn’t without costs. Walmart’s estimated $3 billion in annual losses due to theft are partially attributed to self-checkout. Walmart didn’t reinvent retail; it optimized an existing process at scale, delivering quiet but consequential improvements that mattered while also surfacing new challenges.

AI and Enterprise Software

The diffusion principle reshapes investment strategy as well. Robert F. Smith, founder and CEO of private equity firm Vista Equity Partners, recently offered a compelling view of how AI’s profits will ultimately be captured. Speaking at the CAIS Alternative Investment Summit in the fall, Smith argued that enterprise software companies would be the ultimate beneficiaries of AI’s transformation. Importantly, Smith emphasized that it simply isn’t enough for enterprise software companies to deploy AI tools. Instead, they must integrate AI incrementally into their workflows, such as by enhancing code generation, customer support, and contract analysis.

Vista’s portfolio shows this strategy at work: 80 percent of its 85-plus companies deployed generative AI tools by late last year. Vista’s $20 billion Fund VIII focuses on scaling AI adoption, not speculative moonshots.

The ultimate advantage, Smith argues, lies with firms that own and control their data sets, allowing AI integration to compound customer loyalty and operational efficiency over time. Smith’s framing for firms echoes Ding’s insight for geopolitics: The big winners aren’t the first to invent; they’re the first to diffuse technology effectively across entire business ecosystems.

Three Strategic Takeaways

Execution Beats Invention

Breakthroughs capture headlines, but market leadership accrues to those who execute practical adoption relentlessly. Where can you optimize real-world behaviors faster than competitors?

Context Over Product Purity

Technological excellence matters, but alignment with infrastructure, habits, and friction points matters more. Are you building for how the world actually works — or how you wish it worked?

Seemingly Boring, Subtly Transformative

From NFC stickers to self-checkout kiosks to AI chatbots embedded into back-office software, real competitive advantages often emerge from the unglamorous work of refining the familiar. Where are the practical improvements that can quietly reshape your market?

 

Andy Mok WG02 is a former Hong Kong–based VC/PE investor currently based in Beijing, where he writes and speaks on the intersection of technology, finance, and the shifting global political landscape. He appears regularly on international TV and briefs global financial institutions on the implications of China’s innovation strategies and global positioning. In addition to his Wharton MBA, he holds an MA in China Studies from Johns Hopkins SAIS. He is a past president of the Wharton Club of Beijing.