Unfortunately, the use of Artificial intelligence (AI) in business management and reporting is now rather limited. The challenge is in the quality of the available data.
A company can generate so much unstructured and different data that after cleaning and processing it occurs that it is not enough to build a good model for the original task. It turns out that the company needs to either accumulate fresh data arrays, considering the given structure, or totally rebuild business processes to generate absolutely new information.
Automation for accounting and business intelligence is the main tool for increasing efficiency. Most routine procedures can be transferred to the system and deal with really important tasks. However, the functionality of such programs is still quite narrow. We can mention in the list of achievements automatic unloading invoices, data entry, etc.
More complex robotic solutions have been introduced relatively recently. Among them are Robotic Process Automation and Intelligent Automation.
Robotic Process Automation or RPA-based solutions imitate human work and, in fact, perform a certain set of actions as an employee. So, utilizing RPA software, users can integrate databases of CRM and accounting systems, increase the speed of reconciliation, etc. However, RPA is good only at solving routine tasks which do not need any interpretation or classification of data.
Intelligent Automation (or IA) tools offer more advanced functionality through the use of artificial intelligence. IA's solutions are based on machine learning, computer vision and big data analytics. One example that well illustrates the use of IA technologies is the recognition of information on invoice scans and loading it into a corporate database.
However, the effective use of IA is a result of a long-run process of accumulating statistics and descriptions of parameters. So, if a specialist classifies information in a second, it will take several hundred hours to teach a machine to do the same.
