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AI in eCommerce refers to systems that analyse data from your business, identify patterns and, on that basis, take over tasks. Rather than fixed rules you maintain manually, they learn from your sales, stock and customer data and derive recommendations or concrete actions from it. The range extends from simple analysis (what is selling, where are bottlenecks looming) to agents that handle recurring tasks autonomously and only present you with the decisions that genuinely require one.

Commerce is becoming more complex: more channels, more products, more regulation, fiercer price pressure. AI shifts the work away from manually operating individual tools towards defining goals that systems then execute. Tasks such as price adjustment, inventory planning or standard customer enquiries run in an automated way, while you focus on growth and strategy. The data foundation is key: AI only delivers reliable results when stock levels, orders and customer data are consolidated cleanly across all channels.

Recurring, data-driven workflows are particularly well suited to automation. Typical examples in retail include customer service (automatically responding to standard enquiries such as shipment status or returns), pricing (adjusting prices to market conditions and margins based on data), stock and reorder management (identifying bottlenecks and excess stock early), reporting and business intelligence (analysing sales and stock and deriving recommendations for action), and shipping and returns communications. You decide what runs automatically and what is presented to you for approval.

An AI agent is software that takes over tasks autonomously: it assesses a situation based on data, decides which steps are needed in order to achieve a goal, and carries them out. Unlike a conventional programme that follows fixed rules, or a chatbot that only responds, an AI agent acts on its own initiative and can chain together multiple steps across different systems. In eCommerce, this means, for example: checking stock levels, generating a reorder suggestion and triggering it after your approval. You define the goal, the agent takes care of execution.

Juno is the agent layer above your JTL ecosystem and launches at JTL Connect on 2 October 2026. Juno understands the context of your business, proactively identifies what needs to be done and coordinates the appropriate steps across your products and processes. It starts with Proactive Inventory Management: the automated review of your stock levels with suitable reorder suggestions, available in an open beta. Business Intelligence and Customer Service will follow in the fourth quarter of 2026 in a closed beta. One principle applies throughout: Juno only acts after your approval – you always remain in control.

The AI features in the portfolio are individual functions within individual products – such as Pricing, Customer Service or Business Intelligence. Juno is the layer above them: rather than being yet another standalone function, Juno works across your entire value chain, connects these functions and coordinates tasks across products. In short: the AI features each solve one task within their area, while Juno orchestrates the interplay and keeps the bigger picture in view.

No. The AI features are part of your JTL edition and run via your existing access. You don’t need an additional account or any external services to use them.

Yes. The AI features run within your JTL environment and are GDPR-compliant. This is precisely one of the key differences from general, public AI services: your business and customer data remain protected without you sharing it with third parties. You don’t need to set up or secure anything extra – it works straight away.

No. The AI portfolio can also be used without a JTL ERP. However, if you do work with an ERP, you can get more out of it, because more data and processes feed directly into one another and the AI works from a broader foundation.