1 Why many AI programmes stall at pilot stage
The explanation lies in the way AI is currently being approached. Across many organisations, AI adoption remains fragmented, with individual use cases developed in isolation from core business priorities. These efforts often deliver incremental gains, efficiency improvements, faster processing, better insights in specific functions, but rarely scale to transform how the business operates.
At the same time, the market is beginning to draw a sharper distinction between those who are succeeding and those who are not. PwC’s 2026 AI Performance Study finds that approximately 20% of organisations are capturing nearly 74% of AI-driven value, creating a widening gap between a small group of leaders and a much larger group that remains stuck in experimentation mode. This divergence reflects not a technology gap, but an execution gap.
For those that can scale AI effectively, the difference is substantial: Our research shows that the most “AI‑fit” companies deliver AI‑driven financial performance more than seven times higher than their peers, underlining how quickly advantage can compound once AI is embedded across the business.
Many organisations have essentially optimised for experimentation rather than transformation. As a result, AI remains adjacent to the business, rather than integral to it. The challenge is therefore not one of innovation, but one of integration.
PwC’s AI performance study
What makes a company AI-fit?
AI fitness measures how deeply an organisation embeds artificial intelligence into its strategy, operations, and workforce. True AI fitness focuses strictly on revenue growth, rather than just operational efficiency.
AI-fit companies refuse to treat technology as a series of isolated experiments or narrow automation tasks. Instead, they position AI as a core engine for reinvention. They integrate technology at scale and embed it directly into daily workflows alongside human expertise.
What are the nine factors of AI fitness?
AI fitness is six foundational capabilities and three measures of AI use.
- AI foundations: strategy, investment, workforce, data and technology, governance, and innovation
- AI use: breadth and depth, sophistication, and capturing value from industry convergence
2 From experimentation to reinvention
By contrast, organisations that are realising meaningful returns from AI are shifting from incremental improvement to business reinvention. They are not treating AI as a set of tools layered onto existing processes, but as a catalyst for rethinking how those processes should work in the first place.
Our research highlights this distinction clearly. Leading organisations are significantly more likely to use AI to drive growth, redesign workflows and pursue new revenue opportunities, rather than focusing solely on productivity gains. This is consistent with PwC’s broader concept of the “AI-native enterprise”, in which AI becomes part of core operations rather than a collection of standalone initiatives.
The implications are profound. When AI is embedded in this way, it does not merely accelerate existing processes; it reshapes them. It changes how decisions are made, how customers are served, and how organisations compete. It also creates the conditions for sustained advantage, rather than one-off gains.
3 What Vietnamese businesses must do next
For Vietnam, the opportunity is immense. Encouragingly, leaders in Vietnam are already demonstrating a strong understanding of AI’s role in shaping business outcomes, particularly in areas such as growth, customer experience and operational efficiency. The next phase of the journey must therefore shift from exploration to execution.
This transition cannot be delivered through technology alone. Enterprise-wide value requires reliable data, clear governance and a deliberate effort to build AI fluency across the workforce.
Data
Data needs to be viewed as a strategic asset rather than a technical input. Scaling AI depends not only on the volume of data available, but on how consistently it is structured, shared and used across the organisation. As AI moves closer to decision-making, the ability to connect data across functions becomes a defining advantage.
Governance
Governance is evolving from a compliance requirement into an enabler of scale. As AI becomes embedded in business processes, organisations that establish clear ownership, decision frameworks and risk boundaries early can move faster with greater confidence. In this context, governance supports progress rather than slowing it down.
Way of working
Organisations that are seeing sustained impact are not simply introducing new tools but embedding AI into everyday workflows and decision-making. This requires moving beyond pockets of expertise and ensuring that teams across the business can use AI effectively and consistently as part of their roles.
AI will not transform organisations simply because they adopt it. It will transform those that embed it at the core of how they operate and compete. For Vietnamese businesses, in this next phase, success will depend not just on how quickly organisations adopt AI, but on how effectively they build the foundations that allow it to scale with trust and consistency.
In the end, AI is not just a technology story. It is an enterprise transformation and leadership story. And those who treat it as such will define the next era of growth.
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