Today, most of the industries are trying to figure out how to increase efficiency through the use of automation. This includes the use of tools such as artificial intelligence (AI) and Machine Learning (ML). One of their most important applications is in the field of enterprise technology such as enterprise resource planning (ERP). Leveraging AI in ERP would help organizations understand the plethora of information or data that they already have. To give a real-life example, chatbots have been in vogue for various social media and marketing initiatives. However, AI-based chatbots could have a comprehensive role in the business.
Chatbots could be utilized in the form of a channel through which employees can access data or fill in queries. The AI-enabled system can provide them with relevant information from the ERP. AI can be made to learn how organizations and individuals interact and function and can therefore make recommendations on how to optimize the system. For instance, an ERP could create automatic actions, configure the software by itself to minimize manual intervention, or reconfigure the interface to be more appropriate for a user’s usage pattern. This can be done after an analysis of repeated patterns of use. AI-incorporated finance applications can report about exceptions, learn from them, and subsequently make recommendations to resolve issues that are similar in nature. This has the potential to eliminate delays and speed up the process.
According to Pradeep Agarwal, Senior Director, ERP Cloud, Oracle, AI as a technology has been in use outside business applications for quite some time. The concept was always there but was not really brought into business applications. Over the last few years, organizations have realized that AI and ML are tools that every business application needs.
It is true. Traditional systems were always designed for transaction processing, production, and compliance controls. However, they can’t provide intelligence based on situations to businesses or application users on a real-time basis. This is exactly what artificial intelligence is trying to do now. Apart from AI and ML being incorporated into business applications, there has been growth in the development of standalone tools too that can be used in conjunction with legacy applications. Agarwal says that such tools can only provide limited benefits as they are not homegrown applications. The reason for that is that these systems were designed with the primary objective of recording and not reporting.
“Though you can always use the external tools to automate some of the stuff already there in legacy applications but using these legacy applications to draw conclusions out and feed decisions back into the systems is quite difficult and that is why a lot of organizations including Oracle are coming up with newer age applications that are already AI enabled, with capabilities built in,” says Agarwal. Giving an example, Agarwal says that modern cloud based-systems from Oracle can give suggestions to the user community about payment solutions, liquidity, or even explore various ways of making payments to get the best discount and benefits.
“From legacy business applications, we have been able to derive limited benefits through the use of AI and ML as these systems are designed to capture the transaction system only. There’s only so much change you can do in a legacy application,” adds Agarwal.
But the moot question remains: are the technology decision-makers willing to experiment with these new-age tools that incorporate AI and ML? According to Agarwal, most of the CFOs and CXOs are aware of standard business process automation.
“CXOs know it very well. They have experienced it and have seen the benefits. They know the challenges in their organizations. Every CXO and CFO wants technology that can bring in more efficiency to the process and can support better decision making based on system information and making the finance office more influential based on the data that it has access to. That is why every single CFO is looking at how can the system can analyze past records and decisions, and eventually throw suggestions back at the user community. The outcomes of those suggestions can be recorded and fed in again into the system for better results in the future,” concludes Agarwal.
With most CXOs today focused on deriving more efficiency from the systems, AI and ML tools can be truly transformative. Such uses of emerging technologies can revolutionize enterprise decision making and can go a long way towards Industry 4.0.