It is not known to everyone that artificial intelligence is a concept existing in the public space (science, fiction - SF literature) more or less since the mid-20th century, i.e. since the moment when the first computers appeared. AI does not actually have a unified, commonly accepted definition; in my opinion, its nature is best captured by the following statements:
The first AI solutions - advisory systems - appeared in the 70s, when cognitive and brain science methods began to be introduced to artificial intelligence research. In the 1980s, AI solutions became more common in industrial installations and household appliances/RTVs, using neural network or fuzzy logic technologies. This was also due to the rapid increase in calculation power of computers at the time.
Nowadays, researchers are developing general artificial intelligence with a view to creating machines with intelligence superior to that of humans, and more practical and specialised technology that manifests only a narrow aspect of intelligence, e.g. playing chess, recognising images, translating text or producing a summary of it.
How can AI support business? When answering this question, one should consider what solutions are most commonly used. Of course, it is necessary at this point to mention ERP (Enterprise Resource Planning) systems, used to manage the enterprise.
The ERP system has a number of integrated modules sharing a common database. These include:
These solutions are constantly evolving and can be supplemented with new modules such as E-commerce, WMS - Warehouse Management System - high storage warehouse, BPM - Business Process Management - a tool for managing business processes or BI - Business Intelligence.
ERP systems consist of many modules, so in this section I will try to discuss the use of AI in some of them.
Purchases and liabilities
Purchase invoice processing is the area where automation with artificial intelligence is most frequently implemented. AI learns to recognise different types of invoices, their appropriate assignment to the client, cost type or MPK, but most often the decision to accept the allocation and accounting is made by a human. Artificial intelligence also helps to optimise the purchasing process according to information about previous levels of raw material and material usage, complex sales orders, delivery deadlines, minimum and maximum warehouse limits, packaging types and possible delivery batches. There is still great potential for automation in this area which is related to the digitisation of invoicing and purchasing and the integration of solutions from multiple ERP system providers.
The area of warehouse and inventory management is also heavily supported by artificial intelligence. There are already many fully automated warehouses being implemented in which the processes of putting away, picking goods and picking deliveries have been automated. AI supports these solutions when selecting the appropriate storage location in the warehouse (depending on the turnover rate of the goods), choosing optimal routes for the trucks when picking deliveries, keeping an eye on minimum and maximum stock levels by suggesting purchase orders or production orders. This area still has great potential for automation as the whole supply chain is developing dynamically and the JIT (Just In Time) approach to business is becoming more widespread.
Sales and receivables
This area is largely automated as the process is simple. The difficulty is that new legal requirements appearing with great frequency (e.g. JPK - GTU codes) and may limit the increase in the process efficiency. However, there is still potential for artificial intelligence to support the field.
This area is strongly supported by artificial intelligence especially when it comes to recording bank statements. The system learns as it adds the customer's bank account number and, using the transfer description, tries to account for and appropriately mark the invoices to which the payment relates. Furthermore, on the basis of bank transaction numbers, it appropriately marks the types of debits generated by the bank. There is still a great potential for optimisation in this area - enterprises often have accounts in many banks, and besides, the process of outsourcing accounting is becoming more common, and in such enterprises (CUW - Shared Services Centres) AI will certainly be of great support.
Artificial intelligence is used by ERP systems, but the level of its use is still low. This is often due to a lack of end-user awareness and their approach to the way they do their job. If someone is able to perform his/her duties without much difficulty, he/she does not strive to find ways to optimise and automate processes.
In the era of digitisation, rapid development of technology and the desire for continuous improvement of business process efficiency, artificial intelligence will constitute an essential part of progress. Analysing processes, optimising them and looking for areas that will be suitable for AI implementation, these are trends from which there is no turning back. AI will not replace humans, but it can certainly facilitate their work. Employees will then be responsible for more complex tasks or for supervising algorithms or processes implemented by artificial intelligence.
Contact our expert