Artificial intelligence is used in many applications and services today without users always knowing about it. For example, it is an excellent means of further automating processes. This makes AI the ideal technology for ERP systems, one of whose core tasks is to increase the effectiveness and efficiency of the company through automation. This allows companies to focus their usually scarce resources on tasks that generate real added value. This makes enterprise resource planning and artificial intelligence a powerful duo. AI technologies such as natural language processing, RPA, chatbots and machine learning make ERP systems more efficient.

Communicate with ERP software via voice and text

The first applications have already proven their worth. For example, some ERP providers such as IFS have equipped their systems with AI chatbots that allow users to communicate with the software via voice and text input. Users obtain information from the ERP system or carry out transactions by speaking to the software or exchanging information with it via text chat. The integration of bots into popular communication tools even makes it possible to do this directly via Skype, Skype for Business or Facebook Messenger. This allows occasional users to quickly and easily submit a vacation request, search for a specific item in the company software or call up sales statistics in real time. They no longer have to deal with the systematics of the ERP system at all.

Voice communication also makes it possible to interact with the ERP in situations without access to a keyboard. For example, car journeys or waiting times in traffic jams can be used productively by operating the software via the hands-free system. Service technicians or engineers can use a mobile device to quickly query technical data directly at a system or report back on work that has been carried out.

ERP chatbots not only increase the automation rate internally, but also externally. When customers call a company's call center, the bots answer simple questions and thus relieve the burden on employees, for example with questions about opening hours or the estimated arrival time of a technician. They also pave the way for helpful self-services that enable end customers to perform simple routine tasks, such as rescheduling an appointment or planning a meeting, without using a keyboard. AI chatbots therefore not only save companies time and money. They are also an effective tool to combat the notorious shortage of skilled workers.

Smart maintenance and servicing

In the future, artificial intelligence will be used in many other ERP areas. These include maintenance and servicing, for example. AI can also be a valuable aid in sectors such as the manufacturing industry and energy supply, which have to deal with numerous machines and systems. These machines and systems are equipped with sensors that monitor critical wear parts and generate IoT data. This creates a wealth of information that can be analyzed automatically with the help of AI. Machine learning algorithms that learn from IoT historical data enable highly efficient predictive maintenance that reliably anticipates failures and assigns a service technician in good time. In this way, expensive downtimes can be almost completely avoided.

For example, if too high temperatures or strong vibrations in a certain machine part have repeatedly led to malfunctions in the past, AI can use this experience to automatically trigger a work order in the company software when the critical temperature limit is reached and send technicians to rectify the problem. Manual assignment by an employee is then no longer necessary. AI can also optimize the entire deployment planning of technicians by taking into account current availability, equipment, existing expertise and the current location in order to keep travel distances as short as possible.

With self-optimizing algorithms, artificial intelligence in ERP systems can also further automate decisions. Currently, simple decisions such as the approval of travel expenses are still semi-automated using code and rules engines based on business rules and decision trees. However, these rules can only keep pace with great complexity and high change dynamics to a limited extent. In future, machine learning algorithms will therefore evaluate the historical data, recognize the behavioural patterns of decision-makers and apply them to new scenarios. This will automate approval processes effectively and efficiently, freeing up decision-makers for more demanding tasks.

Personalized surfaces

Another example of the fruitful interaction between AI and ERP is the personalization of user interfaces. Users of online stores such as Amazon and streaming services such as Netflix are now used to only being shown offers that are precisely tailored to their personal interests. In their role as employees, they increasingly expect the same from their business software. They no longer want to have to laboriously click together the information relevant to their tasks, but ideally have it presented directly on their home screen. This also saves time and money and conserves personnel resources.

The author Peter Schulz is Team Manager Presales at IFS in Erlangen. © IFS

With the help of defined roles, the user interfaces of ERP systems can already be controlled today in such a way that they show each user exactly the content that is relevant to their user group - for example, key performance indicators for managing directors, the capacity utilization of production lines for production managers or the current status of systems for service technicians. However, machine learning processes will make it possible to personalize interfaces even more in the future. They will enable ERP systems to learn from the actions of individual users, automatically derive their personal preferences and then - just like Amazon or Netflix - provide them with truly personalized interfaces.

Peter Schulz, Team Manager Presales at IFS / am