Robotic Process Automation (RPA) is a groundbreaking technology that enables a fast return on investment (ROI) and can save companies hundreds of hours across thousands of transactions. However, as with any technology with transformative potential, the implementation process is critical. The methods and objectives set during implementation determine an organisation’s future performance with RPA.

History has shown that a controlled and well-planned implementation is often more challenging than it initially seems. A significant percentage of RPA programs fail right from the start. So, how can companies avoid setbacks, obstacles, and mistakes that prevent them from benefiting from RPA as quickly as possible?

Like any other system within an organisation, RPA bots need operational and technological management. Robots should be treated as virtual employees, and when processes and rules change, a structured change management strategy must ensure that employees are informed and adequately trained – just as they would be with human colleagues. RPA initiatives require continuous maintenance, especially considering that more than 70% of bots need reconfiguration within 18 months of deployment. Additional approaches must be tested, and management must remain aware of potential new challenges. These are the hidden costs of automation, comparable to retraining human employees.

RPA is just one part of the equation for intelligent automation. Many mistakenly believe that RPA is a comprehensive platform for automation, but in reality, you cannot build a digital transformation on a “patchwork” system. Enterprise ecosystems are complex. RPA was not designed to simplify and automate intricate, long-term processes that involve internal and external systems, machine and human labour, custom software, and third-party applications. Additionally, RPA is not an artificial intelligence (AI) platform. Despite often being referred to as “a form of AI,” RPA merely automates interactions with legacy user interfaces when no API is available.

RPA is most effective when applied to tasks that meet all three of these criteria:

1. High volume
2. Low complexity
3. Rule-based processes

Many business leaders discover that their companies have fewer processes that meet all three criteria than initially expected.

Automation eliminates repetitive and monotonous tasks, often linked to high employee turnover. This shift gives employees more time and opportunities to engage in meaningful, value-added work. For example, an RPA bot has been developed to capture student data and enter it into an enrolment system, eliminating manual data entry and saving valuable work hours. However, any RPA strategy must align both technological and workforce strategies. Without this balance, organisations may face delays in training, job transfers, and team development.

RPA is part of a broader automation continuum. It begins with simple, localised tasks and expands into enterprise-wide intelligent automation powered by machine learning, analytics, and AI. As more companies explore RPA adoption, they can learn from others’ experiences and avoid repeating common mistakes.

For successful implementation, companies must:

• Set realistic expectations and plans before deployment
• Establish strong RPA governance across the organisation
• Ensure continuous monitoring, maintenance, and optimisation

Organisations that have successfully integrated RPA have improved their business performance without adding unnecessary complexity.