Scaling AI successfully is rarely just about the technology itself. In my work supporting APAC organisations, the biggest hurdles almost always trace back to foundational gaps such as fragmented systems, inconsistent data, and teams that aren’t yet ready.
Many companies are still stuck between pilot projects and genuine enterprise rollout. Global data confirms the gap – findings from a recent McKinsey survey show that while 88 percent of organisations now use AI regularly in at least one function, nearly two-thirds have yet to scale it enterprise-wide. Those that deliberately strengthen their digital base first will be the winners.
Build strong digital and data foundations at the start
Disconnected infrastructure is the most frequent barrier. Sales, finance, procurement and operations often run on separate platforms that simply do not talk to each other. Over time, customer records, financials, operational logs and internal documents end up scattered across silos.
AI models thrive on clean, connected data. When information is trapped in departmental systems or paper-based workflows, outputs lose reliability and trust. That’s why I advise companies to treat AI adoption as the next logical step in digital transformation, not a standalone project.
We see this most clearly in document-heavy processes. For example, our Bill One platform lets organisations digitise invoices through streamlined submission channels – by using a dedicated email or PDF upload – rather than requiring their vendors to change internal processes. This approach centralises fragmented data while keeping operations running as usual, making it easier to apply AI to improve accuracy, visibility, and decision-making.
Digitising document-heavy workflows, linking core enterprise systems, standardising data formats, and moving to modern cloud infrastructure are prerequisites that make AI deliver real value. In Southeast Asia these foundations matter more than ever. The ASEAN Digital Masterplan 2025 sets out three essential conditions for the region to become a leading digital community and economic bloc: high-quality ubiquitous connectivity across ASEAN, safe and trusted digital services backed by strong cybersecurity and data governance, and the removal of barriers so businesses and people can participate fully in the digital economy.
Start with use cases that solve real problems
A common mistake I observe is attempting large-scale AI initiatives before clearly identifying the specific operational challenges they aim to solve. This results in slow progress and frustrated teams.
The smarter path, which is most likely to deliver the quickest returns in APAC, is beginning with focused applications: automating document processing, generating customer insights, optimising workflows, or building internal knowledge bases. These use cases produce measurable productivity gains, let teams build confidence, and create internal champions for broader rollout.
- Kazunori Fukuda, Managing Director of Sansan Global, Thailand.
Our experiences working with enterprise clients show that embedding AI deeply into workflows and everyday employee tasks accelerates adoption far more effectively than ambitious overhauls that risk replacing people.
Prepare your workforce and embed governance early Technology adoption ultimately depends on people. Across Southeast Asia, demand for AI engineers, data scientists and cloud specialists far outstrips supply. Organisations that link technology rollout directly to workforce transformation see the best outcomes.
This approach aligns with national-level recommendations in the ASEAN Guide on AI Governance and Ethics, which stress nurturing AI talent and upskilling the workforce through close public-private collaboration. Business users across functions need practical understanding of how AI can support decision-making and routine work.
When teams feel confident rather than threatened, adoption spreads quickly. Reflecting a broad global cross-section, McKinsey’s 2025 survey of nearly 2,000 senior professionals across senior levels found that almost a third of those at AI-using organisations expect total workforce reductions in the coming year. With 43 percent anticipating no change, and 13 percent expecting growth, the data highlights that targeted reskilling remains essential.
At the same time, governance cannot be an afterthought. Clear policies on data privacy, algorithmic transparency, risk management and human oversight must be in place from day one.
Move from experimentation to make a real impact
The APAC region remains one of the most exciting arenas for digital innovation, fuelled by rapid economic growth, vibrant entrepreneurship and rising infrastructure investment. Yet the winners in the AI era will not simply be the fastest adopters. They are quietly but deliberately building the right foundations first.
APAC enterprises can move confidently from experimentation to enterprise-wide value by strengthening digital and data infrastructure, starting with practical use cases, investing seriously in workforce readiness, and locking in responsible governance. Technology deployment, naturally, is at the core, but AI scaling is really about creating the systems, processes and capabilities that let innovation thrive.
Kazunori Fukuda is Managing Director of Sansan Global (Thailand).
