Artificial Intelligence in ERP Systems. Which AI Solution Should Businesses Choose?

How to Compare AI Solutions in ERP?
AI Assistants in ERP Systems

ChatERP from Comarch

Genius by Asseco Business Solutions

MAiA in Monitor ERP System

AI Application Ecosystem Instead of a Single Feature
The Microsoft Ecosystem and AI in ERP

Copilot

Power BI

AI in ERP – What Should You Choose?

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 intervention
Some 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 responses
Some 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 conditions
Some 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.

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E-Commerce

What is eCommerce?

To manage daily operations across multiple platforms and applications, an integrated system is essential to connect ERP, POS, eCommerce, sales channels, and other systems into a centralized database. This article will help you understand what integrated eCommerce is and why it is necessary for your business to grow like never before. What is eCommerce? An integrated eCommerce solution allows for the seamless use of all data from your ERP system and other systems to power your online store. Essentially, it directly connects the ERP system with your e-shop without third-party intervention. An integrated eCommerce solution is partially installed within the ERP system, making its operation seamless compared to other complex integrated solutions. Why is integrated eCommerce important for your business? An integrated eCommerce platform increases management efficiency and organizational productivity. It helps save time, manage manual labor, and automates back-office work. Integrated eCommerce enables error-free data updates using fast and consistent applications. Inventory Management and Rapid Updates The online retail space is dynamic and highly competitive. Millions of products are sold daily. If your prices are not adjusted based on competitor research or if products do not meet consumer trends, it becomes a major problem. Integrated solutions provide real-time information, preventing pricing or product disasters. For example, when a customer places an order on the front-end, the system automatically updates accounts and inventory on the back-end. On-Time Delivery Many companies struggle with delivery delays, leading to a loss of credibility. Integrated eCommerce software ensures that the order flow is smooth and error-free. The system is reliable and suggests possible delivery dates by analyzing data from the production floor and warehouse, ensuring that orders are not missed and deliveries are made on time. Better Customer Service A satisfied customer is an asset. Integrated eCommerce helps keep customers happy by providing real-time information on prices, stock, order tracking, and more. Furthermore, it enables integrated marketing through email, social media, and automation, helping you meet customer needs and build loyalty. Finance and Accounting Management Integrated eCommerce saves time and reduces errors by automating data transfers from the front-end store to the back-end financial system. This helps the finance team access sales revenue info, maintain accurate financial reporting, manage payroll, and handle transactions in real-time. Better Efficiency and Decision Making Retailers usually maintain separate databases for finance, products, and consumers. An integrated platform allows for the optimal use of these data resources. For instance, an automated sales process reduces time spent on administrative tasks, allowing the sales team to focus on building relationships with potential customers. Types of eCommerce eCommerce can be divided into four basic online sales models. They differ based on who is selling and who is the recipient of the offer. The most popular types of electronic commerce include: B2C (Business-to-Customer) – enables the sale of a product range or services to individual customers, which simultaneously allows for reaching a wide audience. B2B (Business-to-Business) – sales between two business entities, primarily characteristic of wholesale orders. C2C (Customer-to-Customer) – sales between two private individuals. This model is mainly characteristic of classifieds portals, auction sites, or marketplaces that allow for the listing of used items. C2B (Customer-to-Business) – a rarer, yet still encountered e-commerce model. It turns a private individual into the seller of a specific product or service, which is then provided to a particular enterprise. B2B vs. B2C eCommerce – Key Differences Electronic commerce is developing particularly within B2B and B2C. Although both models are based on online sales, they differ in terms of the purchasing process, customer expectations, and the way of building commercial relationships. Understanding these differences is key when matching the eCommerce development strategy. Purchasing process and length of decision In the B2C model, purchasing decisions are usually made quickly and often have an impulsive character. An individual customer is guided by price, product availability, reviews from other users, and convenience of purchase. Thus, they will be more inclined to take advantage of a quick promotion or a discount code. Meanwhile, the sales process within B2B is significantly longer and more complex. It involves commercial negotiations in which at least several decision-makers in the company participate. Order value and frequency B2C purchases usually have a lower unit value but may occur more frequently. Individual customers buy products for their own needs and in smaller quantities. In the B2B model, orders are usually larger – often wholesale and carried out cyclically. Companies treat eCommerce as a tool for supply optimization and automation of purchasing processes. Relationships and personalization of the offer B2C sales are based mainly on mass marketing. It takes various forms – from outdoor advertising to influencer and social media marketing. A key role is played by the store’s intuitiveness, speed of delivery, and customer service. In contrast, in B2B, long-term business relationships, individual price lists, and contract discounts are of significant importance. System integrations, e.g., with ERP, WMS, or EDI platforms, are also key. Functionalities of sales platforms B2C stores focus on the simplicity of the purchasing process, attractive product presentation, and optimization for mobile devices. Applications are also becoming increasingly popular, sometimes replacing browser-based shopping. B2B platforms require more advanced features, such as multi-level user accounts, credit limits, product configurators, automatic order repeats, or access to transaction history and commercial documents. In practice, more and more companies are developing a hybrid model, combining B2B and B2C sales in one eCommerce ecosystem to increase sales reach and better respond to the needs of different groups of customers. FAQ – Frequently Asked Questions How much does eCommerce implementation cost? Costs vary from a few thousand PLN for simple stores to hundreds of thousands for complex B2B projects. How long does it take to launch an online store? A simple store can be launched in a few weeks, though the average is about 3.5 months. Complex platforms with ERP/WMS integration take longer. Can eCommerce be integrated with ERP? Yes, this is very common and covers inventory, orders, invoices, and returns. Does eCommerce support omnichannel sales? Yes, the eCommerce platform often serves as the central hub for multi-channel sales, integrating online stores with physical locations and marketplaces.

MarekMac

09 April 2026