In the breaking decade of technology, government agencies are quick to adopt new innovative measures. Automation and Artificial Intelligence (AI) are laying the path to achieve lofty productivity and decision-making.
‘High value’ work is the main focus of government agencies. For the purpose, robotic process automation and similar technologies are being embraced in order to decrease errors, improve compliance, and eliminate repetitive administration tasks.
Robot process automation (RPA) is an application of technology that partially or fully automates human activities that are manual, rule-based, and repetitive. However, RPA lacks in a part as it can only take simple decisions that allow agencies to eliminate low-value, mundane, and transactional work. The exploitation of RPA could be multiplied by adding AI to the equation. AI elevates RPA and accelerates it to complete multiple tasks. It is very helpful in analyzing large scale data and enabling decision-making.
The amalgamation of RPA and AI has unravelled more real and tangible results which could be applied to digital solutions for civilians and defense agencies. Either of the technologies can’t do the same job alone.
According to the RPA Program Playbook published by the Federal RPA community of practice, the current RPA program system reduces up to five-hours of employees’ workload. The RPA features make a massive transformation in government operations through software bots to automate high-volume, repeatable tasks within legacy processes and applications.
The Playbook further unfolds that RPA has the ability to reduce working time by 20-hour per employee which will eventually lead to government agencies gaining a net capacity of US$ 3 billion.
Deploying RPA in Government Agencies
Major functioning areas in the government including finance, acquisition, IT, human resource, security, and mission assurance are automating tasks with the help of RPA. Data entry, data reconciliation, spreadsheet manipulation, systems integration, automated data reporting, analytics, customer outreach, and communications are some of the features of RPA.
For instance, the Food and Drug Administration’s Centre for drug evaluation and research reported it had seven RPA projects in development. One of them automates drug intake forms and free up the pharmaceutical and medical staff for the agency’s core science mission in 2019. The same year, the Defense Logistics Agency made unattended bots to work full-time. The department saved more than 200,000 labor hours with the launch of 82 RPA bots.
If RPA is effectively deployed by government agencies in automation, then machine learning (ML) and intelligent automation will just be a few steps away. RPA establishes the building blocks for AI in terms of IT infrastructure and standardization according to the Playbook note.
Accelerating AI and ML in RPA for Financial Management
The application of Artificial Intelligence (AI) and machine learning (ML) enriches the already existing features of RPA. It can be widely utilized in financial management to acknowledge areas such as transaction matching, fraud prevention, and anomaly detection.
Large financial agencies generally stagger to resolve and match hundreds of thousands of their daily transactions. Many of the processes require heavy manual work and take hours to complete. However, RPA can automatically access data from various financial management systems. But it falls short in unmatched transactions when the data tolerance overdoes the matching data and documents. By adding AI and ML to the process, it accelerates the matching financial transactions or identifies fraud through handling and associated actions.
Machine learning trains models to rapidly examine the correlation between historical and current transactions. The move helps in minimizing error by identifying potential matching or irregular behavior based on the transaction.
People should get ready to accept AI innovations in human society. The misconception of AI taking over the world through its features needs to be buried for a better future. AI technologies are not designed to kill human labor and push us into unemployment. AI defers the working hours and minimizes it to use the human potential on something more important and meaningful. The mission of AI is to set an aligned work on the path.
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