The Role of RPA in Hyperautomation: What It Actually Does (and Doesn't Do)

What RPA really is (stripped of the marketing hype)

Robotic Process Automation (RPA) sounds futuristic, but it's actually straightforward: software that mimics human actions in digital systems.

Think of it as a digital assistant that can:

• Log into applications

• Copy data between systems

• Fill out forms

• Send emails

• Extract information from documents

• Click buttons in the right sequence

RPA automates repetitive tasks like data entry, invoice processing, and email parsing without changing your existing systems. That's its superpower: it works with legacy software that can't be easily integrated any other way.

But here's what most vendors won't tell you: RPA alone isn't hyperautomation. It's one ingredient in a much bigger recipe.

The numbers: Why RPA exploded (and why it's not enough)

The RPA market has grown explosively:

• Valued at $28.31 billion in 2024

• Expected to reach $211.06 billion by 2034

• Growing at 25% annually

Why? Because 53% of businesses have already implemented RPA, and another 19% plan to adopt it in the next two years. The ROI is undeniable: 85% of respondents report that RPA met or exceeded their expectations.

But here's the problem: 64% of RPA implementations are now part of strategic, enterprise-wide initiatives, not standalone projects. In other words, companies realized that RPA bots without orchestration create chaos.

Why RPA alone isn't enough (and never was)

RPA shines in rule-based, structured scenarios. But business processes rarely operate in isolation.

The limitations:

• Brittle: Change your invoice template, and your bot breaks

• Narrow: Bots handle specific tasks, not end-to-end processes

• Dumb: They can't adapt to exceptions or make decisions

• Fragmented: Without orchestration, you end up with hundreds of disconnected bots

Think of it this way: You can train a bot to copy data from emails into a spreadsheet. Great. But what happens when:

• The email format changes?

• The data needs validation before entry?

• An exception requires human judgment?

• Three other systems need to be updated simultaneously?

RPA can't handle these situations. That's where hyperautomation comes in.

Hyperautomation: RPA with context and intelligence

Hyperautomation expands automation from individual tasks to end-to-end business processes by combining:

• RPA to handle repetitive actions

• AI to interpret unstructured data and make decisions

• Process orchestration to connect tasks into workflows

• Analytics to optimize and improve over time

• Low-code/no-code tools to build and adjust applications rapidly

Gartner expects organizations combining hyperautomation with redesigned processes to lower operational costs by 30%. That's not from RPA alone. It's from RPA working within an intelligent system.

How RPA fits into modern workflow automation platforms

Modern platforms like Kissflow are built for scalability, governance, and usability. When RPA integrates into these platforms:

• Process owners can orchestrate complex workflows without writing code

• CIOs gain visibility and control across automation pipelines

• IT teams reduce backlog by using RPA bots as building blocks for broader solutions

In Kissflow's architecture, RPA bots aren't siloed tools, they're components within larger workflows. They handle tedious steps while decision-making and exception-handling remain contextual within the platform.

The key advantage: The global low-code development platform market is growing at 32.2% CAGR, reaching $264.40 billion by 2032. Why? Because companies want platforms where RPA is one tool among many, not the entire strategy.

Real example: RPA in a procure-to-pay workflow

Let me show you how this works in practice.

The old way (RPA only)

Step 1: RPA bot extracts data from incoming invoice
Step 2: Bot populates ERP fields
Step 3: Bot... gets stuck because there's a discrepancy
Result: Process stalls. Human manually investigates. Bot sits idle.

The hyperautomation way (RPA + workflow platform)

Step 1: RPA bot extracts invoice data
Step 2: Data flows into Kissflow workflow
Step 3: Approval process runs through low-code workflow logic
Step 4: AI flags potential fraud based on historical patterns
Step 5: Exceptions automatically route to human approvers
Step 6: Once approved, bot completes ERP data entry
Step 7: Analytics track cycle time and flag bottlenecks

See the difference? The bot handles data extraction and entry. The platform handles orchestration, decisions, exceptions, and continuous improvement.

This unified approach delivers both speed and resilience, qualities RPA alone cannot provide.

Why Kissflow is built for RPA-enabled hyperautomation

Kissflow's no-code environment lets process owners build workflows and integrate RPA without IT dependency.

Here's what that means practically:

For business users:

• Build the workflow in Kissflow's visual designer

• Add RPA bots at specific steps where needed

• Test and deploy without writing code

For IT teams:

• Maintain governance and security

• Manage bot credentials and permissions

• Monitor performance across all automations

For CIOs:

• Clear internal app backlogs without massive IT investments

• Enable departments to solve problems while maintaining oversight

• Scale automation without proportionally scaling IT staff

With 41% of businesses already running citizen development programs and nearly 60% of custom apps now built outside IT departments, this model isn't experimental; it's essential.

The ROI reality: What you can actually expect

Let's talk numbers, because that's what your CFO cares about.

RPA ROI (standalone):

• Expected ROI ranges from 30% to 200% in the first year

• Potential long-term ROI of up to 300%

• 52% of financial services organizations saved at least $100,000 annually

Hyperautomation ROI (RPA + platform):

• Organizations can lower operational costs by 30% when combining technologies

• Some implementations achieve ROI as high as 2,560%

• 72% of organizations strongly support intelligent automation strategies

The difference? RPA gives you efficiency gains. Hyperautomation gives you efficiency gains plus business agility, continuous improvement, and scalability.

Common RPA mistakes (and how to avoid them)

After working with hundreds of companies, I've seen the same mistakes repeatedly:

Mistake #1: Bot sprawl without governance

Companies deploy 50, 100, 200 bots without central management. Nobody knows what breaks when systems change.

Solution: Use a platform like Kissflow that provides centralized governance for all automations.

Mistake #2: Automating bad processes

Just because you can automate something doesn't mean you should. Automating a poorly designed process just gives you faster bad outcomes.

Solution: Organizations combining hyperautomation with redesigned processes see 30% cost reductions. Fix the process first.

Mistake #3: RPA-only thinking

Treating RPA as the entire automation strategy instead of one component.

Solution: Adopt a platform approach where RPA is integrated with workflow orchestration, AI, and analytics.

Mistake #4: Underestimating maintenance

63% of organizations say their expectations for time to implement RPA were not met. Bots require ongoing maintenance as systems change.

Solution: Plan for maintenance from day one, and use platforms that make bot management easier.

Mistake #5: Ignoring the human element

Only 17% of respondents faced employee resistance when piloting RPA, but that drops to 3% with proper implementation. Still, change management matters.

Solution: Communicate clearly that RPA eliminates tedious work, not jobs. Position it as giving employees time for meaningful work.

Where RPA creates the biggest impact by industry

Different industries use RPA differently:

Banking & Finance:

• 80% of finance leaders have implemented or plan to implement RPA

• Key uses: Regulatory reporting, balance sheet reconciliation, KYC processes

Manufacturing:

• 35% adoption rate, highest among all industries

• Key uses: Invoice processing, inventory management, quality control documentation

Healthcare:

• Growing rapidly for claims processing and patient record management

• The healthcare segment is expected to grow at the highest CAGR in intelligent automation

Retail:

• Returns processing, inventory updates, order fulfillment

• Essential during high-volume periods like holidays

The future: RPA gets smarter

The RPA of tomorrow won't just follow rules—it'll understand context.

What's coming:

• AI-enhanced RPA that handles unstructured data

• Self-healing bots that adapt when UI elements change

• Predictive RPA that anticipates issues before they occur

• Conversational RPA that takes natural language instructions

With 65% of organizations already introducing AI capabilities like ML and NLP into their automation, this future is closer than you think.

The bottom line: RPA is the ignition, not the destination

RPA kickstarts automation initiatives. It delivers quick wins. It integrates legacy systems. But it's not the end game.

Hyperautomation begins with RPA but scales through platform strategy. Organizations using RPA in isolation risk:

• Short-term wins followed by long-term fragmentation
• Bot sprawl without governance
• Automation that doesn't evolve with the business

Those using platforms like Kissflow unlock:

• Scalability without chaos

• Agility to adapt processes quickly

• Measurable ROI that grows over time

• Governance that protects as you scale

The choice isn't between RPA and hyperautomation. It's between using RPA as a tactical tool or as part of a strategic platform.