SAP x AI: Opening doors to retail optimization

#1. Faster, safer, and simpler process optimization

Faster, simpler, and AI-driven process optimization is readily at hand for today’s retailers running SAP ERP systems. 

SAP has long been the backbone for securing end-to-end retail transactions, from customer orders to inventory management. SAP is trusted across the retail industry to ensure complete traceability and auditability. In the past, however, retailers had to swell their tech stacks with third-party best-of-breed solutions for process optimization or automation, because their ERP’s algorithmic capabilities could not match specialized tools.

That dynamic no longer exists. Embedded AI shifts the platform from a system of record to a system of intelligence, one that not only captures what happened but recommends what to do next, and what processes to optimize next. The impact of these capabilities is also multiplied by the use of GenAI-powered solutions such as SAP Signavio² – the business process-intelligence tool that is purpose-built to model, analyze, and optimize business processes.

For retailers, the bottom line is simple. Assortment, forecasting, and inventory management optimization decisions can now be made within the same system that manages the underlying transactions.

#2. Maximizing value from ‘invisible operations’

Retail is embracing AI at pace, and the opportunity to generate transformative returns lies not just in customer-facing tools, but in the ‘invisible’ back-office functions and processes that underpin the entire operation. For retailers utilizing SAP, this is where the most significant gains can be won. Globally, the AI in retail market is predicted to grow from $16.6 billion³ in 2026 to $71 billion by 2033. Maximizing returns on that investment means looking beyond the customer interface.

Perhaps understandably for such a customer-centric industry, much of the current AI focus is on consumer-facing applications. There is some justification for this: 41% of consumers now use AI assistants to research products, 33% to find reviews, and 31% to search for deals.⁴ Yet for retailers managing a huge volume of daily transactions and SKUs, applying AI to less visible but critical functions such as supply chain, order management, inventory, or demand forecasting is where transformation truly accelerates.

By operationalizing the data already housed in the SAP ERP with AI, retailers can fuel top-line sales growth by ensuring the right product assortments, optimizing pricing, and preventing stockouts. SAP estimates a 30% reduction in revenue loss can be achieved through improved product availability, a figure that has drawn iconic retailers such as Harrods and the COOP Group to adopt SAP’s AI-based inventory replenishment solutions.⁵ In terms of bottom line profitability, intelligent automation can reduce overstock and lower operational costs, including a potential 25% reduction in inventory costs.⁶

Together, these capabilities bridge the gap between back-office efficiency and front-end customer loyalty, turning complex transactional data into a distinct competitive advantage.

#3. Overcoming retailers’ AI scale-up headaches

Although retailers are eager to convert AI’s undoubted potential to tangible results, BearingPoint research suggests the sector is struggling to scale-up AI across their organizations. In fact, our data shows that as few as 7% of retail executives report having fully scaled their AI projects.⁷

However, there is good news at hand. The increasing sophistication and widespread deployment of AI within core SAP ERP systems will diminish these scale-up headaches for many retail users. It will happen organically, with AI-driven process optimization an integral component of the SAP platform offer.

A primary barrier to enterprise-wide AI deployment is the challenge retailers face in consistently rolling out AI technology across such large teams, diverse departments, and widespread locations. SAP systems, however, are built to scale. They are typically used business-wide, spanning multiple core functions and processes. This means embedded SAP AI has a relatively frictionless and immediate effect on a significant portion of a retailer’s operational footprint and workforce. Additionally, employees can access new AI functionality through familiar platforms and interfaces with minimal training, helping overcome individual resistance.

Furthermore, accessing and securing data is often a major roadblock for AI deployments, raising strict data protection and quality concerns. By using AI-embedded SAP, retailers eliminate these constraints because the AI operates directly on the existing SAP processes and proprietary data already secured within the system. Again, this is particularly critical for the retail sector, where the multiplication of massive sales transactions, numerous store locations, and extensive product lines creates a colossal volume of data. Embedded AI simplifies and automates the manipulation of this high-volume information without needing to risk external data transfers.

Finally, SAP’s embedded AI promotes wider user adoption through its ‘Joule’⁸ interface, which offers a guided, conversational experience. Instead of requiring technical knowledge to interrogate the ERP, retail personnel can communicate with the system to retrieve information, navigate applications, and complete tasks using everyday language. This makes the scale-up process faster and more intuitive across the enterprise. For instance, Hornbach is using SAP Order Management Services to connect digital and physical stores with visibility into day-to-day transactions and support omnichannel retail at scale. The same SAP capability set now includes Joule in SAP Order Management Services and an Order Reliability Agent designed to proactively mitigate issues such as stock discrepancies or process bottlenecks.⁹