Robotic Process Automation (RPA) has been touted as one of the potent technologies when deployed smartly, could lead to significant productivity enhancement and resultant reduction in costs. While RPA is yet another IT software, unlike the traditional tools which are deployed first and all exceptions are handled with human interventions, RPA has in-built Artificial Intelligence (AI) and machine learning capabilities. Thus the repetitive, labourious, ‘non value adding’ tasks in functions such as finance, customer relationship management, procurement or insurance could be taken over by RPA by triggering actions, manipulating data and communicating with other software systems. Inevitably this has led to an intense debate around whether RPA will eliminate jobs and what would happen to thousands of resources currently deployed both onshore as well as offshore.
The first reaction would be that in the back office and the middle office, all those roles which are currently handling repetitive tasks would become redundant. This would be the eventual outcome however, there would be several other situations and dimensions which need to be factored. Effective automation with the help of AI should create new roles and new opportunities hitherto not experienced.
Successful implementation of RPA would mean the system should be able to mimic the manual interventions accurately. In reality, initially, it would not be equipped to deal with all intricate steps automatically and would require iterative tuning to align with the transactions. Experts are required to structure the data, define how to deal with exceptions and intervene to train the tool to gradually handle all the steps involved.
Further some processes would also require to be reengineered or redefined as RPA would be able to handle the transactions differently and this in turn may impact the functioning of other related processes. Hence, organisations would exercise caution in the transition phase and would have a dual run until RPA is fully tested and is stabilised in a set of processes. This preparatory phase provides the organisation with the time to assess the new capabilities that could be created with the available talent pool and train them for higher roles calling for analytical capabilities.
Even if the requirement of resources is reduced in the short term as RPA stabilises, normal attrition rates should take care of the displaced resources. Those who currently possess traditional programming skills have to rapidly acquire new capabilities in machine learning, develop understanding of RPA and its integration with multiple systems. Unlike traditional IT applications, planning and implementation could be done in small patches in shorter span of time and therefore software developers have to reorient themselves.
For those entering into the workforce for the first time, there would be a demand for talent with traditional programming skills along with the skills for developing RPA frameworks or for customising the frameworks. For those entering the workforce for being part of the business process outsourcing functions, it would be important to develop capability in data interpretation and analysis as increasingly more recruitment at the entry level would be for such skills and not just for their communication or transaction handling skills.
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For the IT services industry, advent of RPA could remove from certain jobs boredom from repetitive actions and therefore enable HR managers to attract talent that looks forward to challenging work environment and this could possibly lead to higher retention too. Widespread impact of RPA, AI and machine learning would be realised over the next two decades as tools and capabilities mature. While the industry is designing methods to cope with the transition phase, it is critical to not just add RPA or AI as part of the curriculum but consider sharpening the underlying skills related to the ability to deal with data, expertise in mathematics, data modelling and understanding of processes in various domains so that the next generation of smart talent is geared to function in the world that would be directed by intelligent machines.
Uma Ganesh is CEO, Global Talent Track, a corporate training solutions company.