What is WMS?

Today, AI is no longer just a trend but a tool from which companies expect measurable benefits. As a result, managers are no longer asking whether an ERP system includes AI features, but rather what type of AI capabilities it offers. In this article, we organize the market and highlight the differences that matter for decision-makers. Just 2–3 years ago, artificial intelligence in business systems was often treated as an “add-on” to sales presentations. Today – especially from the perspective of CFOs and IT managers – it is an area that is rigorously evaluated. This is also reflected in the findings of the “Cyfrowy Menedżer” report prepared by myERP, which clearly shows a shift toward a “prove it” mindset. AI is expected to deliver results only when a company has solid foundations in the form of high-quality data and clearly defined KPIs. How to Compare AI Solutions in ERP? The biggest trap in implementing AI within ERP systems is assuming that an LLM can compensate for disorganized data and processes. From a purchasing perspective, it is better to treat AI as a productivity layer. Artificial intelligence shortens working time, supports decision-making, and automates routine tasks – but it also requires high-quality input data. IT and finance departments should pay attention to three key aspects: Scope of process interventionSome AI solutions act only as informational assistants, providing summaries or insights from reports. Others can perform actual actions within the system – such as setting credit limits or issuing documents. Sources of generated responsesSome solutions rely exclusively on internal company data, reducing the risk of AI “hallucinations.” Others – especially generative AI tools – require users to define the sources the LLM can access. Costs and technical conditionsSome AI features are included in ERP systems at no additional cost. Others offer advanced capabilities available through paid options. AI Assistants in ERP Systems The most visible form of AI for users is conversational assistants. These solutions enable interaction with ERP systems using natural language, inspired by tools like ChatGPT or Gemini. They also help accelerate onboarding for new employees. ChatERP from Comarch ChatERP is a built-in chat assistant that allows users to interact with ERP in natural language. Ultimately, it is intended to cover both on-premise and cloud versions of all Comarch ERP systems. Currently, it is available in BETA. Its functionality includes: Access to company data available in the system Data analysis and reasoning Suggesting system features Executing tasks on user request A key aspect is the ability to perform business operations such as setting credit limits or issuing invoices. In practice, this requires strict permission and audit mechanisms. Without them, the risk of incorrect commands increases. Comarch ensures the protection of personal and sensitive data in ChatERP. Queries and responses may be processed by technology subcontractors, but the AI should not disclose business secrets. Still, companies with high security requirements should formally define data-sharing rules before implementation. Genius by Asseco Business Solutions In terms of declared functionality, Genius is closer to the concept of a digital coworker that monitors tasks, supports decisions, and suggests actions. According to Asseco BS, it notifies users about pending decisions and tasks, answers ERP-related questions, and supports processes such as orders, invoices, and warehouse documents. Additionally, based on user-provided context, the assistant can deliver actionable recommendations. This approach is enhanced by two important elements: Adaptive interface – AI analyzes user behavior and suggests changes to layout, menus, or screen elements, implemented only after user approval. Analytical layer – Genius provides intelligent insights based on real-time ERP data. MAiA in Monitor ERP System Monitor ERP includes its own AI assistant that “structures, compiles, and analyzes data.” Its main goal is to handle time-consuming tasks. MAiA is not just a chatbot – conversational mode is only one interface. It also works through automated summaries and analyses embedded directly in business processes, similar to how Gemini Pro summarizes documents in Google Drive. Importantly, Monitor’s AI relies exclusively on internal business data, ensuring data integrity and control. MAiA also supports text-related tasks – summarizing notes, translating emails, and refining communication tone. MAiA is available in two versions: Basic – included for all customers Pro – available with a monthly per-user fee The Pro version is initially offered as a free trial. Monitor ERP continues to develop AI features and actively collects user feedback via its Ideas Forum. AI Application Ecosystem Instead of a Single Feature An interesting approach comes from Proalpha, which in 2025 introduced its Industrial AI platform. This is a catalog of over 30 AI applications covering core processes – from procurement and production to service. The platform integrates AI solutions from Empolis and Nemo and is built in a SaaS architecture, enabling smooth integration with both Proalpha’s ecosystem and third-party systems. Nemo’s AI capabilities include: Identifying correlations and anomalies in processes Defining recommended actions Evaluating optimization potential in financial terms In this platform-based approach, AI becomes the “engine” of data integration and analytics. For decision-makers, two key implications stand out: Data processing approach – Industrial AI handles both structured (tables) and unstructured data (documents, notes), turning hidden knowledge into actionable insights Automated recommendations – which can be implemented based on diagnosis and trend forecasting The Microsoft Ecosystem and AI in ERP A unique position in the market is held by Microsoft Dynamics 365 – a scalable ERP/CRM platform deeply integrated with other Microsoft services. Implementations are delivered by multiple myERP partners, including companies such as Companial, Integris, MS POS Poland, xalution Group, IT.integro, and Solemis. Copilot Microsoft has embedded Microsoft Copilot in ERP systems in two ways: as a conversational assistant and as embedded functionality within system features. Key capabilities in Dynamics 365 Business Central include: Conversational guidance on system functionality Data analysis using filters and sorting Creation of sales documents (quotes, orders, invoices) Marketing content generation E-document mapping Bank reconciliation Document numbering automation Product substitution suggestions Order processing automation Power BI Many organizations want ERP data to be consumed in a self-service analytics model. In this context, Copilot in Microsoft Power BI provides significant value: Fast creation and modification of reports and visualizations Automatic report summaries Conversational interaction with data However, Copilot in Power BI is a paid feature (Fabric or Premium). Additionally, organizations must ensure high data quality for AI to function effectively. AI in ERP – What Should You Choose? There is no single “best AI” solution for all organizations. The right choice depends on the dominant challenge within the company – whether it is low user productivity, the need for stronger financial control, or real-time production optimization. Key takeaway:AI in ERP should not be treated as a standalone feature, but as a strategic layer that enhances how people work with data, processes, and decisions.