Machine learning, natural language processing, generative AI – where does the buzzword bingo end? Where does real added value begin? Everyone is talking about how AI is influencing more and more systems in companies . ERP software is no exception. But what are the benefits of AI in ERP?

The important thing is that the debate surrounding the use of AI should not be an emotional discussion, but should be conducted from a practical perspective – with a focus on concrete applications that will give your company a competitive advantage. Equally, it should not be about simply implementing the current situation with AI; rather, the aim is to identify and exploit untapped potential.

Why is the use of AI in ERP systems interesting?

AI makes ERP systems smarter, more flexible and more efficient. But why should you get to grips with it right now? The answer lies in the increasing complexity of business processes and the dynamics of the markets. AI helps to react more quickly to changes, make more precise decisions, reduce costs and thus significantly increase efficiency.  

The question is therefore not whether AI is generally useful in ERP (because yes, it is), but how companies can use this technology in a targeted manner as part of the digital transformation.

What kind of AI can be used in ERP software?

AI technologies affect almost all business processes, with the following types of AI being particularly relevant for ERP in SMEs:

• Machine Learning (ML): ML enables ERP systems to learn from data and make predictions. In practice, ML optimizes logistics and delivery routes in real time, for example, which reduces operating costs and increases customer satisfaction.
• Natural Language Processing (NLP): NLP enables the processing and understanding of human language, which improves user interaction with ERP systems. Chatbots and virtual assistants, for example, guide employees through ERP workflows or answer customer queries in real time.
• Robotic process automation (RPA): RPA technology digitizes processes and automates routine tasks. An ERP system can use it to automatically generate reports or distribute important personnel documents, for example.
• Generative AI (GenAI): GenAl generates new content or data based on learned patterns. In ERP systems, for example, it automates the creation of marketing materials, personalizes customer emails and generates comprehensive sales reports. 

3 practical use cases for AI in ERP systems

The integration of artificial intelligence into ERP systems opens up a wide range of opportunities for SMEs. Here are three use cases that show how AI is used in different areas:

1. automated invoice processing

AI-supported ERP systems use technologies such as Natural Language Processing (NLP) and Robotic Process Automation (RPA) to automatically extract, validate and post invoices.

Advantages:

• Reduction of manual errors during data processing
• Acceleration of invoice processing
• Improve liquidity planning through real-time insight into outstanding receivables

2. demand forecasting & inventory management

Machine learning algorithms analyze historical data and real-time information to predict future demand and optimize inventory levels.

Advantages:

• Avoidance of excess stock or stock-outs
• More efficient production planning thanks to accurate demand forecasts
• Cost savings through optimized warehousing

3. personalized customer management

AI in the ERP system can analyse customer data in order to offer personalized recommendations or services. This improves the customer experience and increases customer loyalty.

Advantages:

• Higher customer satisfaction through customized solutions
• Increased sales through targeted offers
• More efficient processing of customer inquiries thanks to chatbots

Added value and challenges of AI in ERP 

AI applications can offer real added value within your ERP if they are not simply “added on” but are strategically integrated into a digital transformation process in a meaningful way. The integration of AI into ERP systems can then offer you these benefits, among others

• Process automation: AI takes over recurring tasks such as data processing or reporting, allowing employees to focus on strategic tasks. 
• Data-based decision-making: By analyzing real-time data, AI recognizes patterns, makes predictions and provides informed recommendations for action.
• Dynamic resource planning: AI algorithms enable predictive planning that is based on real-time data and adapts dynamically to changing conditions.
• Cost reduction: Optimized processes, reduced error rates and more efficient resource allocation significantly reduce operating costs.

Challenges & solutions

Despite all the benefits, the integration of AI also poses challenges that companies need to overcome – especially if there is a lack of expertise and leadership:

• Data security & data protection: AI requires access to large amounts of data in order to be used as effectively as possible. This increases the risk of data leaks or breaches of data protection guidelines. 

Solution: Implement strict security measures and clean data protection guidelines 

• Data quality: The effectiveness of AI depends heavily on the quality of the data. Faulty data can distort results.

Solution: Introduction of a robust data governance model to ensure consistent and clean data

• Acceptance & change management: Employees can be skeptical about new technologies, especially if it changes the way they work. 

Solution: Training programs, AI workshops, clear communication of the benefits of AI and a gradual introduction of new processes

How should you proceed to effectively integrate ERP & AI?

Introducing AI into ERP systems is a crucial step in making your company fit for the future. But how should you go about it? The right approach depends heavily on your individual requirements, existing systems and available budget:

1. completely new ERP solution with integrated AI functions

Both the top dog and some SAP alternatives are equipped with AI functions from the ground up and offer solutions for automated processes, precise analyses and predictive planning. However, such an ERP system with AI is associated with high investment costs and requires comprehensive implementation and employee training.

2. expansion of existing systems with modules from the provider

Many ERP providers offer AI modules that extend existing systems. The advantage lies in the seamless integration into the existing system. However, these extensions can be expensive, especially if they need to be customized to meet your specific requirements.

3. hybrid solution: supplementation with established AI applications

A pragmatic and often cost-effective alternative is to integrate proven third-party AI solutions into existing ERP systems. This involves using standard market AI solutions or SaaS tools and integrating them specifically into workflows. This adds precisely the functions that are relevant for the company. 

Our recommendation: Strategic consulting as the first step

The introduction of AI in ERP systems is both a technical and a strategic decision: after all, mapping the current state in a computer system is not enough for a successful digital transformation. Rather, processes need to be optimized, systems need to be designed more efficiently and employees need to be actively involved. This is the only way to truly exploit unused potential. 

A professional AI consultancy helps you to analyze your needs and identify the right solution, while at the same time strengthening the digital competence in your company. Employees must not only understand how they can work with the new tools, but also recognize their strategic added value. Only then can acceptance be created and the digital transformation successfully driven forward.

More efficient, more intelligent, more flexible: AI for ERP systems

The integration of AI into ERP systems offers companies considerable advantages. Technologies such as machine learning, natural language processing and robotic process automation can optimize business processes, reduce costs and increase efficiency. At the same time, AI enables better adaptation to market changes and a personalized customer approach.

The challenges associated with the introduction of AI, such as data protection risks, data quality requirements and employee acceptance issues, can be overcome through targeted measures. Would you like to find out what artificial intelligence for your business can do ? Let’s find out together which solution best suits your company.