Control your ERP with AI: how shoe and fashion retailers operate their system in plain language
Query inventory across all locations, prepare reorders, create markdown lists, read reports: all in conversation with your system, not by clicking through menus. This is what an ERP system designed for shoe and fashion retail with AI looks like.
An AI-powered ERP system is an inventory management system you operate in plain language. Instead of clicking through screens and filters, you ask a question or give an instruction, and the system responds or completes the task after your approval. In the DezemberHub ERP, this AI is included in the monthly base price.
In shoe and fashion retail, a handful of styles quickly multiplies into thousands of variants: style times color times size. That sheer volume of data makes navigating traditional menus slow and cumbersome. A question like "Which sneakers in size 42 do we still have in the North store?" can be answered faster in plain language than by working through multiple filter levels.
This article explains what AI-driven control means in everyday use, how you can connect your own AI, where the limits lie, and why shoe and fashion retailers in particular stand to benefit.
What does it mean to control an ERP system with AI?
It means you talk to the system instead of navigating it. The AI assistant understands your question, retrieves the data from the ERP system, and responds in plain sentences. For tasks that make changes (setting prices, creating orders), it prepares the action and only executes it after your confirmation.
The difference in one sentence
With a traditional ERP system, you find the function and operate it yourself. With an AI-powered ERP system, you say what you need and the system finds the way there.
How does AI control work in everyday use?
It shows best through concrete tasks that come up daily in shoe and fashion retail:
Checking stock levels
"Do we still have this item in size 42 in brown, and at which store?" The AI reads stock levels across all locations and online channels and responds immediately. No switching between screens, no filter chains.
Preparing reorders
"Which styles have dropped below reorder level?" The AI proposes size-specific reorders by supplier. You review and approve before anything is ordered.
Planning markdowns
"Create a markdown list for summer shoes that have been sitting for more than 90 days." The AI creates the list. The new prices are only set after you confirm them.
Reading reports
"How were sales last week by store and product category?" The AI answers the question as a clear summary, without you having to build a report.
Recurring tasks can also be set up, such as a weekly reorder check. Learn more on the AI assistant page.
Connecting your own AI
DezemberHub does not require you to use a specific AI model. You can connect your own AI, whether from OpenAI, Anthropic, or a locally hosted model. This keeps you independent and gives you control over where your data is processed.
This is made possible by the system's architecture: every action in the ERP system is defined as a clearly specified capability. These capabilities can be invoked not only through the interface but also exposed as tools for an AI assistant via the Model Context Protocol (MCP). A connected assistant can then perform the same tasks you would carry out in the interface, always within the assigned user permissions.
What the Model Context Protocol (MCP) is
MCP is an open standard that allows AI assistants to communicate with external systems. Rather than building a proprietary solution tied to a single AI, DezemberHub exposes ERP functions as standardized tools, so the AI assistant of your choice can access them.
What the AI is and is not allowed to do
AI in retail is only useful when it remains transparent and predictable. That is why DezemberHub follows a clear rule: the AI can read freely, but can only make changes after approval.
- Reading without restriction: The AI can query and respond to stock levels, sales, orders, and reports at any time.
- Changes only after confirmation: Setting prices, triggering orders, or changing data only happens once you approve the prepared action.
- Within user permissions: The AI can only do what the respective user is authorized to do. Permission management applies equally to the interface and to the AI.
AI-powered vs. traditional ERP: a comparison
Many established ERP systems were developed before AI became widely available. They work reliably, but rely on navigation through screens and reports. The comparison below illustrates the two approaches and does not evaluate specific vendors:
Swipe to see all columns
| Task | Traditional approach | AI-powered approach |
|---|---|---|
| Check stock | Open screen, filter, read columns | Ask in plain language, get a direct answer |
| Create a report | Configure a report or build an export | Ask a question, receive a clear answer |
| Plan reorders | Go through lists manually | Size-specific suggestions per supplier, ready for approval |
| Operation by staff | Training on menus and screens required | Operated in plain language, shorter onboarding |
| Use your own AI | Typically not supported | Connect your own model via MCP |
Why shoe and fashion retailers benefit in particular
Shoe and fashion retail comes with exceptionally high variant complexity. From 500 styles with multiple colors and sizes, you quickly end up with several thousand individual items. This is exactly where AI control excels:
- Size-specific answers: The most common question at the sales counter is about a specific size and color. An AI query across all stores answers it in seconds.
- Seasonal management: Pre-orders, reorders, and end-of-season sales follow fixed rhythms. Markdown lists and order suggestions can be prepared on demand.
- Order sheets as PDF: Manufacturers often deliver orders as PDFs. The AI can read an order sheet and create base items, speeding up data entry.
- Less clicking per variant: The more variants an assortment has, the more time plain-language operation saves compared to clicking through screens.
Frequently asked questions about AI-powered ERP
What is an AI-powered ERP system?
An AI-powered ERP system is one you operate in plain language. You ask a question or give an instruction, and the system responds or prepares the task. Changes such as price adjustments are only carried out after your approval.
Can I connect my own AI to the ERP system?
Yes. DezemberHub does not require a specific model. You can connect an AI from OpenAI, Anthropic, or a locally hosted model. The ERP functions are made available as tools via the open Model Context Protocol (MCP).
Does the AI make independent decisions about prices or orders?
No. The AI can read data freely, but anything that makes a change, such as setting prices or triggering orders, only happens after your confirmation. In addition, user permissions apply: the AI can only do what the respective user is authorized to do.
Does the AI assistant cost extra?
The AI assistant is included in the monthly base price. You can try the DezemberHub ERP free for 30 days. All you need to get started is your email address, no payment details and no automatic renewal.
Is the AI-powered ERP particularly suited to shoe retail?
Yes. The DezemberHub ERP is built for shoe and fashion retail, with size grids, variants by style, color, and size, and seasonal workflows. It is precisely in this high variant complexity that plain-language operation saves the most time.