The AI conversation in Indonesia today is still dominated by large company stories, McKinsey research reports, bank case studies, enterprise pilots with dedicated budgets. That makes sense, large companies have the technical resources and dedicated budgets to experiment first. But there's a number that rarely gets the spotlight it deserves, Indonesia has roughly 65 million micro, small, and medium enterprises, the backbone of the country's economy, and most of them haven't been touched by AI in any structured way.
Global adoption data shows a pattern worth paying attention to. Large enterprises still dominate current AI agent adoption, around 25%, largely thanks to the technical resources and dedicated AI budgets they carry. But when it comes to growth, mid-market companies and SMBs are actually posting higher year-over-year growth rates than enterprises. The momentum is shifting. What's holding MSMEs back isn't whether AI is relevant to them anymore, it's access and clarity on where to start.
One shift that's opening this door is a change in the AI platforms themselves. Low-code and no-code tools now let business owners, not just engineering teams, design and deploy AI agents aligned with real day-to-day operational needs. That changes the equation that has held MSMEs back for years, the assumption that AI is expensive, requires a large technical team, and only makes economic sense at large scale. That assumption no longer fully holds.
For MSMEs, the use cases with the most immediate impact usually aren't the most technically impressive ones. They're the most repetitive and time-consuming, daily transaction recording and cash reconciliation, fast customer responses outside business hours, inventory management that's still handled manually, and operational decisions that have historically relied purely on the owner's gut feeling with no data behind them. That's where the most time gets lost, and where a well-targeted AI system can automate the work without needing to build something complicated.
The opportunity in this segment is large precisely because it's still mostly empty. Large companies are already racing each other on who gets to production fastest with AI. Indonesian MSMEs haven't reached that stage yet, but the growth trajectory is clearly heading there. What they need isn't a scaled-down version of an enterprise AI system, it's one designed from the ground up for how MSMEs actually work and operate, simple to run, clear in its impact, and economically accessible.
That's also why XETUP keeps building product lines designed specifically for MSME scale, not a cheaper cut-down version of an enterprise system, but something built from the ground up for how small and medium businesses actually work.