The automation conversation in most enterprises has fragmented into separate camps: RPA advocates pushing bot-driven process automation, low-code proponents championing visual application development, and traditional IT defending custom-coded solutions. Meanwhile, business processes remain partially automated, with human handoffs creating bottlenecks that neither approach alone can eliminate.
The real opportunity lies in combining these capabilities. The worldwide RPA software market grew to $3.2 billion in 2023 from $2.6 billion in 2022, growing at 22.1 percent faster than the overall application infrastructure market. Simultaneously, the low-code market continues to experience explosive growth, with Gartner forecasting that 70 percent of new enterprise applications will use low-code or no-code technologies by 2025. The question is not RPA or low-code but how to combine them effectively.
RPA excels at automating interactions with existing applications, particularly legacy systems that lack APIs or modern integration capabilities. Bots can navigate user interfaces, extract data from screens, populate forms, and execute transactions just as human users would, without requiring changes to underlying systems.
No-code platform excel at creating new workflows, applications, and user experiences. They enable organizations to build custom solutions, design approval processes, create data collection interfaces, and orchestrate work across teams. These platforms handle the "new build" requirements that RPA does not address.
The limitations of each approach reveal why combination makes sense. RPA bots perform specific tasks but do not create new processes or user interfaces. No-code platforms build new experiences but cannot easily automate interactions with legacy systems that lack integration APIs. Together, they cover the full automation spectrum.
Many organizations run critical processes on legacy systems that predate modern integration standards. Extracting data from these systems for use in new workflows traditionally required expensive custom development or manual rekeying.
Hybrid automation addresses this challenge. RPA bots extract data from legacy systems through UI automation. That data feeds into no-code workflows that handle routing, approvals, notifications, and business logic. The combination delivers end-to-end automation without requiring changes to legacy systems.
Business processes rarely stay within a single system. Employee onboarding touches HR systems, IT provisioning, facilities management, finance, and department-specific applications. Customer orders flow through CRM, inventory, shipping, and billing systems.
No-code platforms orchestrate the overall process flow, managing approvals, routing exceptions, and coordinating activities. RPA bots handle interactions with systems that lack native integration capabilities. The combination creates unified processes across fragmented system landscapes.
Pure RPA implementations often struggle with exceptions. When processes deviate from expected patterns, bots require human intervention. No-code workflows can manage these exceptions by routing unusual cases to the appropriate reviewers, capturing decisions, and triggering corrective bot actions. This pattern addresses one of RPA's persistent challenges. Deloitte research found that 53 percent of businesses have implemented RPA, but scaling from pilot to enterprise-wide deployment often stalls due to exception handling complexity. Integrated no-code workflows provide the flexibility that pure bot implementations lack.
Industry analysts describe this convergence as "hyperautomation," the disciplined approach to rapidly identifying, vetting, and automating as many processes as possible. The global robotic process automation market is projected to reach $211.06 billion by 2034, growing at 25.01 percent annually. This growth reflects enterprise commitment to automation at scale.
Gartner predicts that through 2024, organizations will drive toward hyperautomation, adopting at least three out of twenty process-agnostic types of software that enable comprehensive automation. The convergence of RPA, low-code, process mining, and AI represents this hyperautomation vision in practice.
Process analysis first. Before selecting tools, map the end-to-end processes. Identify which steps require UI automation (RPA territory), which need new workflows or interfaces (no-code territory), and which benefit from both.
Integration architecture. Plan how RPA outputs will feed no-code workflows and vice versa. APIs, file exchanges, and database triggers all have roles. Document integration patterns for reuse across initiatives.
Governance coordination. RPA and no-code programs often report to different organizational owners. Coordinate governance to ensure consistent standards, avoid duplication, and enable integrated solutions.
Skill development. Teams need competency in both approaches. Cross-training enables better solution design and reduces dependency on narrow specialists.
The financial case for combined automation is compelling. Research indicates that 98 percent of IT leaders believe automation is essential for financial gains. The expected ROI from RPA adoption ranges from 30 percent to 200 percent in the first year, with potential long-term ROI reaching 300 percent.
By 2024, organizations combining hyperautomation technologies with redesigned operational processes can expect to lower operational costs by 30 percent according to Gartner projections. The cost savings emerge from reduced manual effort, faster processing, fewer errors, and improved compliance.
The market is consolidating around platforms that offer both capabilities. Gartner notes that by 2025, 90 percent of RPA vendors will offer generative-AI-assisted automation, reflecting the technology convergence underway. RPA vendors are adding workflow capabilities; workflow platforms are adding automation features.
For enterprise buyers, this convergence simplifies procurement but complicates evaluation. The key question becomes: which platform offers the best combination of capabilities for your specific process landscape? Organizations with extensive legacy systems may prioritize RPA strength. Those building new digital processes may weigh no-code capabilities more heavily.
The debate between RPA and no-code misses the point. McKinsey research indicates that 45 percent of business tasks can be automated with existing technologies. Realizing that potential requires combining approaches strategically, using each where it delivers the greatest value.
The organizations achieving the greatest automation returns are not committed to a single technology. They are committed to process outcomes, selecting and combining tools based on what each process requires. That pragmatic approach delivers results that ideological commitments to specific technologies cannot match.
Kissflow's no-code platform provides the workflow orchestration layer that complements RPA implementations. With visual process builders, approval workflows, and integration capabilities, Kissflow enables organizations to create end-to-end automated processes that span multiple systems and technologies. Whether you are managing exceptions from bot-driven processes, orchestrating multi-system workflows, or building new digital experiences, Kissflow provides the flexibility to design solutions that match your specific automation requirements.
Related topics: