The integration of AI and ML to cloud ERP technologies mean that finance professionals can decrease the number of manual transactions posted and reduce the cost of regulatory compliance.
FREMONT, CA: Finance teams are integral to the sleek running of any business. Their role is beginning to increase in capacity and the professionals are beginning to be concerned about what they cannot see or control. Therefore, there is a strategic business necessity to adopt and adapt to new technologies like Artificial Intelligence (AI). It is for this reason that AI and Machine Learning (ML) is already taking off in customer service, healthcare, energy, manufacturing, and other industries.
Technology up to expectations
Today, people are used to a variety of virtual assistant options, which guides them through everyday tasks. Anything from booking hotels, online banking, looking for jobs to finding the cheapest airfares can be done by asking the virtual assistants. Consequently, the expectations for technology are exceptionally high and that expectation transfers into the business lives; employees, clients, customers, and business partners are hoping for more than clunky, slow, obsolete legacy systems.
The foundational technologies like ERP software need to be agile and flexible so that emerging technologies such as AI and ML can be embedded into the fundamentals. The approach is why the cloud is essential: in the most modern Cloud ERP systems, machine learning and AI are already rooted, creating the daintiest possible system for the business, and a cloud infrastructure fit for the future. Additionally, the approach is getting a step ahead with emerging technology like the Internet of Things, blockchain, and cybersecurity being built into cloud ERP systems.
So, how are these technologies benefitting finance? The integration of AI and ML to cloud ERP technologies mean that finance professionals can decrease the number of manual transactions posted and reduce the cost of regulatory compliance. With these tasks taken care of, they are free to work on more strategic projects for their firm. Often, the outputs from more strategic work are stronger, and being strategic implies making use of data; data that machine learning capabilities can gather, analyze and spot anomalies and patterns within faster and more accurate rates than humans ever could.
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