For many years, investments in digital infrastructure, mobile applications, data, and cloud computing were considered crucial for competitive advantage. Technology leaders often established significant market gaps.

However, the evolution of cloud computing, foundational AI models, and open technology ecosystems is altering this dynamic. As technology becomes more accessible, the gap in technological capabilities among businesses rapidly shrinks. What once took years to achieve a technological advantage can now be accomplished in mere months.

According to Jens Lottner, chief executive officer of Techcombank, in this new landscape, long-term competitive advantage no longer hinges on which technology a business owns, but rather on how it organizes data, operates systems, and makes decisions.

"The distinction is no longer about whether a business uses AI, but its ability to operate AI effectively at scale. That is the true demarcation between organizations that merely experiment and those that can transform AI into a genuine competitive edge," he stated.

Jens Lottner, chief executive officer of Techcombank, speaking at the AWS Summit Singapore 2026. *Photo: Techcombank*

To build a sustainable competitive advantage, Techcombank has adopted an architectural approach: separating data and AI-driven decision intelligence systems from operational systems. Under this model, analysis, risk assessment, and action recommendations are processed at a central layer before being sent to execution systems. This design allows AI to scale without over-complicating the system, while ensuring control.

This model is underpinned by a platform Techcombank has built over the past 5 years, based on three pillars: digitalization, data, and talent. Data is considered a strategic asset. Currently, Techcombank processes approximately 8 billion data points daily, builds customer profiles with around 12,000 attributes, and operates 55 AI models serving various business objectives. This data scale provides the foundation for the bank to apply AI across activities ranging from risk management and operations to product development and customer care.

However, Jens Lottner noted that the greatest challenge lies not in technology or data, but in the human element, particularly teams capable of bridging business problems with technological capabilities.

"Technology can be acquired, but training individuals who understand operations, customers, and risk management, while also being proficient with data and technology, typically requires more time," he added.

The synergy of digital infrastructure, data, and skilled human resources is enabling AI to become integral to the bank's operations and decision-making. One application Techcombank has implemented is expanding services for household businesses. This sector plays a vital role in the economy but often lacks standardized financial data, limiting traditional credit assessment methods.

To gain a comprehensive view of customer risk and repayment capacity, the bank incorporates diverse new data sources, including store images, customer traffic, business activity levels, and other related indicators. As a result, AI not only enhances operational efficiency but also extends credit access to customer segments previously difficult to serve.

According to Techcombank's leadership, the greatest value of AI lies not in the technology itself, but in its ability to combine data, operating models, and appropriate human resources to elevate decision quality. With over 60% of its infrastructure migrated to the cloud and a large-scale data platform, the bank is progressively integrating AI into its core architecture, moving towards an operating model where decisions are made faster, more accurately, and with the capacity to serve customers at a larger scale.

Minh Ngoc