Digital transformation naturally leads to automation—not only for operational efficiency but also to optimize processes, reduce errors, and allow human resources to focus on less repetitive, routine tasks.
In recent years, thanks to extraordinary technological advancements, the concept of hyperautomation has emerged alongside traditional automation, establishing itself as a key trend in the enterprise world. Let’s explore what hyperautomation is and, more importantly, how to implement it in any organization successfully.
Traditional automation and Robotic Process Automation (RPA)
To understand hyperautomation, some context is needed. Automation is inherently part of digital transformation. Businesses have historically focused on the most repetitive, rule-based, and (almost) immutable phases of processes, regardless of their complexity. In other words, traditional automation is rule-based.
From a technological standpoint, for over a decade, IT departments have prioritized Robotic Process Automation (RPA). RPA replicates human actions on systems and applications, enabling companies to automate actions and processes across various systems (e.g., email, Excel, ERP, CRM) without long and costly system integration projects. However, RPA is limited to predictable and routine scenarios, of which many organizations still have an abundance.
Automation becomes smarter
In recent years, the concept of intelligent automation has gained traction. This evolution stems from advances in data science and artificial intelligence techniques (particularly Machine Learning), which give machines decision-making capabilities beyond executing predefined rules.
While professionals remain central to decision-making, modern AI-based systems can influence decisions and even make autonomous ones, albeit within parameters set by human expertise. A prime example is cybersecurity, where cutting-edge solutions provide professionals with probability scores for potential attacks, leaving final decisions to human judgment when in doubt.
Another example of intelligent automation involves managing international invoicing processes—especially for accounts payable. Since each country has its own rules, formats, and models, professionals often perform manual tasks like data extraction, compliance verification, and system input. Here, AI can automate information extraction from documents, recognize country-specific formats, and ensure compliance with local regulations. These tasks are automated but typically supervised.
Hyperautomation: approach, not technology
Gartner coined the term hyperautomation in this context, describing it as a “business-driven approach that organizations use to rapidly identify, evaluate, and automate as many business and IT processes as possible.”
Hyperautomation is an approach, not a technology. It highlights how technologies like machine learning, robotic process automation, integration platforms (iPaaS), intelligent business process management suites (iBPMS), and others can work together to “rapidly and intelligently automate as many business processes as possible.” Adding low-code or no-code tools further democratizes hyperautomation, making it accessible to small and medium-sized enterprises (SMEs).
Starting with larger, more structured organizations, hyperautomation has attracted significant investments, with the market expected to grow at a compound annual growth rate of 16.5% through 2030.
Five essential steps to start with hyperautomation
While the concept may seem straightforward, adopting hyperautomation in an organization is far from simple. It’s not a turnkey system but a mindset requiring a solid strategic vision. Companies must analyze existing processes, identify the most critical ones, redesign them, and develop tailored solutions leveraging the best technological tools—from RPA to AI—while integrating as-a-service platforms for greater efficiency and faster time-to-market.
Given the rapid evolution of the technologies underpinning hyperautomation, dedicated expertise is essential. Cross-functional teams should be involved, and hyperautomation must be integrated into the company’s strategy with a flexible IT architecture that can adapt to future needs and opportunities. Partnering with a specialist familiar with the client’s processes, competitive landscape, and regulatory environment—as well as the underlying technology ecosystem—can make a significant difference.
Here’s a five-phase roadmap to guide organizations in the effective and gradual implementation of this modern paradigm. This approach considers the complexity of processes and the organizational change brought by advanced automation.
As-is process analysis
The first step involves thoroughly mapping business processes to identify bottlenecks, inefficiencies, and highly repetitive tasks. Traditional workflow analysis methods and advanced technologies like process mining can be used to gain a detailed, often surprising, understanding of actual processes.
Business Process Reengineering (BPR)
Before implementing automation, existing processes must be optimized. Reengineering simplifies workflows and establishes a solid foundation for automation, avoiding the automation of existing inefficiencies.
Hyperautomation solution development
This phase involves designing and developing a tailored solution by leveraging a wide range of technologies, including RPA and the broader AI ecosystem. The goal is to create synergy between technologies to achieve scalable, intelligent, and fully integrated workflows.
Implementation and integration
A gradual implementation approach is recommended, starting with pilot projects. Subsequent phases involve integrating automated processes with existing systems to ensure seamless communication without adding complexity.
Change management
Adopting hyperautomation (and its solutions) can transform how people work. It’s crucial to involve teams early, provide training and ongoing support, and address resistance to change. Only by fostering a shared and sustainable vision can advanced automation become a successful organizational opportunity.
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