Last month, I watched a VP of Operations at a logistics company in Ho Chi Minh City realize something that made him visibly uncomfortable: his team's data entry process—the one they'd been optimizing for 15 years—could be entirely automated in about six weeks with RPA. Not eliminated. Just... gone. He'd spent a decade building processes around it, training people on it, measuring their productivity on it. Suddenly, it was all pointless busywork.
This is where we are with RPA in 2026. It's not science fiction anymore. It's not even particularly expensive. And yet, most Vietnamese businesses haven't seriously experimented with it.
What RPA Actually Is (And What It Isn't)
Let me be direct: RPA isn't artificial intelligence in the way people use that term. It's not making smart decisions. It's not learning from exceptions. It's a very sophisticated bot that clicks buttons, fills in forms, copies data from one place to another, and follows if-then logic. Think of it as a digital worker who's extremely fast, never gets tired, never forgets a step, and has the intelligence of a particularly focused golden retriever.
UiPath, Blue Prism, and Automation Anywhere dominate the enterprise market globally, but the category has exploded into dozens of competitors. Some are cloud-native. Some run on-premise. Some are so visual that a business analyst can build processes without touching code. Others? You need a developer.
The honest reality: RPA excels at structured, repetitive processes with clear rules. Insurance claims processing. Payroll. Invoice matching. Benefits enrollment. The moment your process requires judgment calls, context, or pattern recognition beyond basic matching, you're either building something too complex or you're fooling yourself about what the bot can do.
The Vietnam Opportunity Nobody's Talking About
Here's a statistic that bothers me: Vietnamese enterprises spend roughly $4-5 billion annually on labor costs for administrative and operational work. In the banking sector alone, back-office operations employ roughly 180,000 people. A significant portion of that work is structured, repetitive, and automatable right now.
Yet RPA adoption in Vietnam is maybe 2-3% of what it is in Singapore or South Korea. Why?
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Partly it's visibility. The conversation around digital transformation in Vietnam focuses on ERP systems, cloud migration, and AI. RPA feels unglamorous by comparison. But here's what pragmatic finance directors should know: RPA typically pays for itself in 12-18 months. I've seen implementations where the ROI was under one year.
The other barrier is a myth: the belief that RPA requires expensive consultants and perfect process documentation. True at scale, maybe. But for a regional bank's loan disbursement process? A logistics company's shipment tracking? A retail chain's inventory reconciliation? You can pilot an RPA solution in 3-4 weeks with a team of two people.
What Makes RPA Implementations Actually Succeed
I've seen RPA projects fail spectacularly, and it's rarely because the technology didn't work. It's because organizations treated it like a software implementation instead of a process automation project.
The successful ones I've observed share three things:
First, they pick the right process. Not the most visible one, not the most complex, not the one the CEO thinks should be automated. They pick something that's stable, high-volume, and has clear rules. A finance team reconciling daily sales reports? Perfect. A customer service team routing tickets based on content? Much harder.
Second, they involve the people doing the work. Not just in interviews at the start, but throughout. The people executing a process know about the 37 edge cases that don't appear in the documented procedure. If you automate without capturing those, your bot fails. More importantly, if you don't bring operators into the design, you'll meet resistance. People aren't threatened by RPA when they helped design it.
Third—and this is where so many projects stumble—they build in human oversight, not human handoff. The bot doesn't replace the person; it eliminates the repetitive parts so the person can focus on exceptions and judgment. A loan processor spends 80% of their day on data entry and validation. Automation removes that. They spend their time now on applications with missing documents or unusual circumstances. Their job is better. They're not threatened.
The Uncomfortable Realities
RPA isn't a set-and-forget solution. Process changes break bots. If you restructure your invoice approval process, your automation needs adjustment. If a vendor changes their invoice format, your bot notices and fails. These aren't failures of the technology; they're features. You *want* to know when something changes.
Also: RPA scales differently than you'd think. Building a bot that processes 100 invoices daily is maybe 40% of the effort of building one that processes 10,000. The complexity compounds. Screen resolution changes break bots relying on UI coordinates. System updates require retesting. You need governance and monitoring, which means infrastructure and potentially dedicated resources.
And the dirty secret nobody mentions in sales conversations? Sometimes your process is so broken that automating it just makes you efficiently broken faster. I've watched organizations build RPA around processes that needed redesign first. Automating dysfunctional workflows is an expensive way to preserve bad habits.
Where This Actually Matters
In Vietnam's financial sector, RPA is beginning to move from pilot projects to production at tier-1 banks. Back-office work is getting redeployed to customer-facing roles. Processing times are dropping from days to hours.
Manufacturing companies are using RPA to sync data between legacy MRP systems and modern cloud platforms without building custom integrations. E-commerce logistics companies are automating shipment tracking across multiple carriers.
Where I see the most untapped opportunity: government-adjacent operations. Land registration, business licensing, permit processing—these are structured, repetitive, frustrating processes that could be dramatically improved with automation. A few provincial governments have piloted this quietly. The results are embarrassingly good.
The Honest Take
RPA is neither revolutionary nor trivial. It's a practical tool for a specific category of problems. It solves them better than hiring more people, better than custom software development, and in most cases, better than hoping the process will improve naturally.
The real value isn't in replacing humans. It's in freeing them from drudgery. It's in moving 50 thousand manual data entry hours per year into something that takes conscious thought. It's in the CFO who stops worrying about reconciliation errors because the bot hasn't missed one in seven months.
For organizations considering automation, the question isn't whether RPA is right for you. It's which of your high-volume, repetitive processes you should tackle first. Most companies I've worked with could identify $200K-500K in annual labor savings within their first three processes. That's not transformational. It's practical. It's real.
At Idflow Technology, we've been helping Vietnamese enterprises think through exactly these questions—which processes matter, where to start, how to measure success. The conversation is still early here, but it's happening.
