HubSpot research shows that while AI adoption in Singapore has moved beyond experimentation, businesses are hitting a plateau in their transformation journey.
The research, which surveyed more than 700 Singapore business leaders, shows that while nearly two-thirds (64%) are applying AI consistently across daily workflows, progression into more advanced AI use remains limited, with only 18% using fully autonomous AI agents capable of making decisions and executing tasks end-to-end.
Yet, the data reveals something more specific than a general adoption challenge. The businesses hitting the hardest walls aren’t the ones lagging behind on AI, but the ones who’ve gone furthest.
Moving into more advanced AI use does not reduce complexity, it increases it. As AI use cases mature, challenges around data integration, legacy systems, and skills become more pronounced.
This suggests that scaling AI is not just about adopting the right tools, but about whether businesses have the connected data and integrated systems that give AI the context it needs to act reliably.
“The key challenge among Singapore businesses is no longer whether they are using AI. It is whether they have the knowledge of customers, market trends, and operations needed to scale the business reliably,” said Megan Hughes, Managing Director & Vice President, JAPAC, HubSpot.
“Only by powering AI with customer data and process understanding can businesses consistently transform generic outputs into tangible results. The most successful businesses will be those with a context advantage, combining leading-edge AI models with deep context to deliver highly impactful outcomes and create reliable digital teammates for sustained growth.”
The real bottleneck is foundations, not ambition
Data quality and integration challenges (37%) rank among the top two barriers to scaling AI deployments, just behind trust and reliability (43%).
These challenges become more visible, not less, as organisations scale AI. Among businesses already using fully autonomous agents, data integration challenges rise to 41%, legacy system limitations to 42%, and skills gaps to 39%.
This reflects a critical shift: the limiting factor is no longer access to AI tools, but the ability to operationalise them across the business — connecting data, systems, and business knowledge so AI can act reliably.
Solving for data quality and integration doesn’t just reduce technical friction, but also builds the organisational confidence that moves businesses from cautious experimentation to larger-scale AI adoption.
High quality, unified data ensures AI outputs are grounded in reality, which will address trust and reliability concerns that rank as business leaders’ top barrier.
Appetite is strong but proof is the tipping point
Indeed, the research findings show that interest in agentic AI remains high despite foundational challenges.
Businesses are not just looking for more AI output, they are looking for output they can rely on to drive measurable results. Leaders say the most important factors for AI agents to operate effectively are accuracy and reliability (66%), system integration (56%), governance (53%), and access to relevant business context and data (48%).
More than two in five leaders (43%) expect AI agents to become highly important to their operations within the next 12 to 24 months. Just 2% of respondents said they have no intentions to invest in AI agents.
More than a quarter (28%) are already investing, while the rest remain in a wait-and-see phase. What will move more businesses from interest to investment is clear: about a third (30%) say clearly demonstrated business results would most increase their willingness to invest further.
“With Singapore’s National AI Council and the Champions of AI programme, the government is making a clear commitment to building the conditions for AI to thrive, and businesses are responding,” added Hughes.
“Our previous Singapore State of Business Growth 2025 research found that organisations with fully integrated systems are ten times more likely to outperform their peers. That level of integration is now the entry point, not the edge. Now, this context combined with AI is how a digitally advanced nation turns ambition into outcomes.”