Today, in addition to the well-established factors of successful business process management, such as building a process architecture, defining key business processes and KPIs, appointing process owners, and allocating areas of responsibility, one of the key factors is the degree of process automation. Along with the rapid development of information technology, in particular artificial intelligence, the owners of companies increasingly need to reengineer their business processes using advanced technologies. In this article, we will figure out how to automate business processes using artificial intelligence.
The ability to automate BPO processes using AI in HR management is important for the company due to the following factors:
- ability to analyze personnel data (CV analysis, performance assessment);
- analysis of the need for specialists;
- selection of candidates for a vacancy;
- conducting cognitive computing (without additional research, AI can calculate, according to the given parameters, which of the employees can effectively manage, and who is going to quit soon).
The HR bot will use clarifying questions to find out how competent the future employee is. In addition, modern AI systems, using cognitive modeling technology, will understand if the interlocutor is lying about his skills.
Interaction with Clients
Today, contact centers are increasingly interacting with customers not only by phone but also through social media, instant messaging, video conferencing, and web chats. Constantly increasing the number of employees is often not the most effective way. Therefore, many companies are considering an alternative path: the introduction of automated solutions with elements of artificial intelligence instead of full-fledged contact centers.
Already, text chatbots are changing workflows in contact centers. Virtual voice assistants are emerging that can respond to simple speech requests and conduct a fairly natural dialogue with the user. Other automated self-service systems are being improved.
Audit and Accounting
Machine learning auditing solutions address critical issues such as audit completeness, better exploration of reports, and ensuring best practices during internal audits. The use of machine learning in auditing enhances audit functions by allowing routine work without compromising quality.
Artificial intelligence solutions help to automatically identify risks and other key factors within audit documentation, help to graph knowledge of multiple relationships between entities, making it more complete and accurate in accounting. Companies use artificial intelligence in accounting to segment risk reports with high similarity, this solution is integrated with a machine learning model that trains itself to identify areas of possible audit effectiveness
Unlike outsourcing tasks, which involve outsourcing individual projects with limited timelines and budgets, business process outsourcing may not have time constraints and a fixed budget. As part of BPO, an organization transfers to an outsourcer not just individual tasks, but a closed functional area within its business. In this context, the use of solutions based on artificial intelligence helps to reduce costs and increase the efficiency of all necessary business processes.