SAP AI and Data Licensing Strategies After the July 2025 Changes

SAP AI & Data Licensing (Joule, SAP Business AI, Datasphere)

Executive Summary:
SAP’s July 2025 licensing changes unbundled key AI and data tools from core ERP packages.

SAP AI and data licensing now require separate contracts for generative AI services like Joule (SAP’s AI copilot) and analytics tools like SAP Datasphere. These offerings utilize consumption-based pricing, where enterprises pay based on actual usage (measured in AI “Units” or data capacity).

This article explains how these AI services and data tools are licensed, how usage is measured, and how to negotiate favorable terms (such as bundling AI credits into RISE or BTP deals) to manage costs.

Major 2025 Licensing Changes for SAP AI and Data Tools

In mid-2025, SAP revamped its cloud ERP packages and unbundled its AI and sustainability features. It retired the old “Premium Plus” tier of RISE with SAP (which had included advanced AI and analytics) and made tools like the Joule AI assistant and SAP Datasphere optional add-ons. In short, generative AI and data warehouse capabilities are no longer included by default – customers must license them separately.

SAP refers to this change as “flexibility” (you pay only for what you use), but it also introduces new cost lines for IT and finance to manage. For example, a year ago, a top-tier SAP subscription might have included some Datasphere capacity and AI functionality.

Now those won’t appear in your contract unless you add them, so budgets must explicitly cover these services. Companies that assumed these tools were built-in could be caught off guard with unplanned costs under the new model.

This shift is part of a broader move toward modular, pay-as-you-go licensing. CIOs and CFOs must adjust their planning to include costs associated with AI and data services.

The upside is you avoid paying for AI or analytics if you won’t use them. However, if you do need SAP’s new AI or data capabilities, it’s critical to negotiate terms upfront to lock in predictable pricing and avoid surprises down the road.

Licensing SAP’s AI Services (Joule and SAP Business AI)

SAP’s AI capabilities – including the Joule generative AI copilot and various SAP Business AI features embedded in applications – are offered on a consumption-based model, rather than an unlimited-use model.

Enterprises can access these AI services in three main ways:

1. Included basic usage: Some AI features come with your SAP software license and include a small free allowance. For example, S/4HANA Cloud may include some predictive analytics or alerts at no additional cost to help you get started.
2. AI Units (credit purchase): To use advanced AI (like extensive generative queries or large-scale AI automation), customers purchase AI Units – a currency for SAP’s AI services. You buy a block of units (e.g., 100 AI Units per year minimum), and consumption of AI features draws down this pool. Each AI action (an invoice auto-matched by AI, a chatbot query answered, etc.) consumes a fraction of an AI Unit based on SAP’s conversion rules.
3. BTP cloud credits: If you build or run AI solutions on the SAP Business Technology Platform, you can pay with your BTP cloud credits. In this case, your prepaid BTP credit balance covers the usage (for example, using an AI document processing service will consume credits). This pay-per-use method is common for custom AI scenarios or extensions.

Measuring AI usage:

Every SAP AI service has a defined usage metric (such as transactions or documents) and a conversion rate to AI Units. SAP tracks consumption annually, and unused AI Units expire at year-end (no rollover). Tools like an AI usage dashboard and estimator help monitor how fast you’re consuming units.

What does it cost?

SAP aims to make starting with AI affordable, but heavy use can become costly. One AI Unit is roughly a few euros at list price. SAP often sets minimum purchase quantities (for instance, 100 units). A starter pack might have a list price of around €500–€1000 for 100 units (before discounts). Each unit could cover dozens or hundreds of AI transactions, depending on complexity. The key is to ensure the value exceeds the cost: if €1 of AI spend yields €5 in efficiency or insights, it’s worthwhile.

For example, a manufacturing company utilized Joule’s natural language queries to accelerate production order lookups by 50% and reduce downtime by 2%. Even if they consumed ~100 AI Units to power those queries, the cost was minor compared to the savings from improved productivity. The lesson is to track AI unit consumption alongside the business benefits it delivers, so you can confidently invest where it yields the most value.

How SAP Datasphere is Licensed

SAP Datasphere (formerly SAP Data Warehouse Cloud) is SAP’s cloud data warehouse solution, and its licensing is now separate from your core ERP subscription.

There are two primary ways to license Datasphere:

• Capacity subscription: Commit to a fixed capacity for a flat fee. For example, you might subscribe to a package of 128 GB of storage and associated compute per year. This provides cost predictability – you know your annual spend as long as you stay within that capacity. It’s ideal if you plan to use Datasphere heavily (e.g. large-scale BI reporting or consolidating enterprise-wide data regularly).
• Consumption via BTP credits: Use Datasphere on a pay-per-use basis by consuming BTP credits. In this model, every hour of database runtime and every gigabyte of data stored or processed deducts from your credit pool. This approach is flexible if your analytics usage is lighter or variable – you pay only for what you use, which is great for pilot projects or occasional data analysis needs.

In practical terms, the cost drivers for Datasphere are data volume and computational workload. A company streaming IoT sensor data into Datasphere 24/7 with complex analytics will incur far higher costs than one doing monthly reports on a few gigabytes of data.

With a subscription, you choose a tier to match your expected peak usage (and pay more to upgrade if needed). With consumption, you have flexibility, but you must watch for spikes in usage, as those directly drive up costs.

Many enterprises begin with consumption-based Datasphere usage to gauge their needs, then transition to a subscription model once they have established steady demand.

It’s worth asking SAP if they’ll include a small Datasphere trial or offer a discount in a large deal; otherwise, plan and budget for this as a separate line item.

Consumption-Based Pricing and Usage Metrics

SAP’s shift to consumption-based licensing means costs directly follow your usage.

Both AI services and Datasphere use this “pay for what you use” model, but their metrics differ.

The table below summarizes the licensing approach and usage measurements for each:

To avoid surprises, align your AI and data usage with clear business outcomes.

If an AI feature isn’t providing enough value to justify its cost, consider reducing its usage or exploring alternatives. Conversely, when an AI or analytics tool is delivering strong ROI, increasing usage (and thus cost) can be justified.

Negotiation Levers for SAP AI & Data Licensing

With SAP’s new add-on model for AI and Datasphere, negotiating smartly can make a big difference.

Consider these tactics as you plan your agreements:

• Bundle into major deals: In your main SAP contract negotiations (such as a RISE migration or S/4HANA renewal), request that a starter package of AI Units or some Datasphere capacity be included. If your previous SAP deal included these features, mention it to get equivalent value now. Even a limited free allotment for the first year can help jump-start your usage.
• Secure volume discounts & price locks: Push for better rates if your usage is expected to be high. For example, negotiate a lower price per AI Unit if you commit to a certain volume (say, 500 units or more over the term). Also, try to lock that unit price for the duration of the contract. This protects you from future price hikes and gives cost certainty.
• Pilot first, then scale: If you’re unsure about uptake, negotiate a pilot period for AI or Datasphere. For instance, request 6 months of Joule at low cost or a small Datasphere environment to trial. Define success criteria and agree that if they are met, you’ll expand usage (with a pre-negotiated discount for the larger rollout). This way, you prove the value before committing to a larger spend.
• Leverage existing spend: Utilize your broader SAP investment as a lever. If you’re already spending a significant amount with SAP, consider asking for concessions in return. For example, you might commit to a larger multi-year BTP or S/4HANA deal if SAP agrees to include a set amount of AI Units at no extra charge. Bundling your AI needs into a bigger deal can unlock better pricing than buying those services standalone.
• Maintain flexibility: Given the rapid evolution of AI technology and pricing, avoid multi-year lock-ins on these add-ons. Align any AI or Datasphere terms with your main contract end date, and ensure you have the right to adjust quantities annually. Negotiate exit clauses or the ability to scale down if the service isn’t meeting expectations. This flexibility puts pressure on SAP to keep delivering value and earning your business.

In short, treat SAP AI and data services as negotiable line items, just like core licenses.

By being proactive – asking the right questions and baking usage expectations into the contract – you can contain costs and maximize value from SAP’s AI and analytics innovations.

Recommendations

• Assess & forecast demand: Identify where you plan to utilize SAP’s AI and data tools, and estimate the associated requirements (e.g., number of AI-driven transactions per month, or GB of data for analytics). A realistic demand forecast is the foundation for sizing the right licenses.
• Bundle in major contracts: Leverage any big SAP deal (like a RISE contract or large renewal) to include some AI and Datasphere capacity. It’s often easier to acquire a bundle of AI Units or a Datasphere trial upfront than to add it later and pay the full price.
• Insist on transparency: Have SAP spell out how you’ll be charged. Ensure your contract lists the unit conversion metrics for AI and the pricing model for Datasphere. This transparency helps you budget and prevents misunderstandings later.
• Start small, then scale: Don’t over-commit initially. Begin with a minimal AI package or base data capacity to prove value. Then scale up in phases (preferably at a pre-negotiated rate) once you have evidence of the benefits. This phased approach reduces risk and upfront cost.
• Monitor and optimize usage: Once live, keep a close eye on consumption. Use SAP’s monitoring tools or your dashboards to track how quickly you’re using AI units or credits. Optimize processes – ensure AI is utilized where it has the highest impact, and archive or purge unnecessary data in Datasphere to manage storage costs effectively.
• Plan for flexibility: Structure agreements to allow for adjustments as needed. Set annual checkpoints to review and adjust your AI/Data entitlements as needed. Avoid rigid multi-year commitments on emerging technologies – retain the ability to renegotiate if better options or pricing become available.

Checklist: 5 Actions to Take

1. Inventory your needs: List the SAP AI features (e.g., Joule, document AI, predictive planning) and data services (Datasphere, Analytics Cloud) your organization expects to use in the next 1–2 years.
2. Estimate usage: For each item, project how much you’ll use it. Utilize available tools or historical data – e.g., estimate the number of AI queries or document processes per month, and the amount of gigabytes of data your analytics will store.
3. Review entitlements: Check your current SAP contracts for any included AI or BTP credits, as well as any existing data warehousing rights. Know what’s already paid for so you only negotiate for the additional capacity you need.
4. Engage with SAP early: Discuss your needs with SAP or your vendor well in advance of renewal time. Share your usage estimates and ask for their proposed licensing options (and pricing) for the AI and Datasphere components. Early dialogue can reveal promotions and prevent last-minute surprises.
5. Negotiate and document: When finalizing the contract, negotiate to include AI/Data services at favorable terms (such as discounted unit prices or some free usage). Get all terms in writing – the number of AI Units or amount of Datasphere capacity, the cost per unit/GB, any free allowances, and how overages will be handled. Clear documentation will protect you later.

FAQ

Q: Are any AI features included for free, or is everything extra now?
A: Some basic capabilities remain included (for example, simple predictive analytics built into S/4HANA). But advanced features like Joule or heavy AI use are now add-ons. You typically get a small built-in allowance; beyond that, you’ll need to license AI usage via AI Units or an extra subscription.

Q: How do AI Units translate to actual usage and cost?
A: AI Units are a prepaid currency for AI consumption. SAP defines how much of a given AI activity constitutes one unit (e.g., a certain number of chat queries or invoice matches equals 1 unit). While pricing varies, many enterprises report a list price of roughly €5–€10 per AI Unit, sold in bundles of ~100 units. Your negotiated price may be lower. The key is to determine how many units your expected AI processes will consume, then secure a sufficient block to avoid incurring high overage fees.

Q: Can we use our existing RISE or BTP credits to cover these new services?
A: Partially. If you have a BTP Enterprise Agreement with cloud credits, those credits can be spent on Datasphere or certain SAP AI services. And if your RISE subscription came with some included credits, those might help offset some of your AI usage. However, for any substantial AI or data consumption, plan to purchase dedicated add-ons or extra credits. It’s best to budget for these explicitly rather than assuming your general pool will cover everything.

Q: What’s the best way to control costs for SAP’s AI and Datasphere?
A: Start by using SAP’s tools to forecast usage accurately. Then monitor consumption closely once you’re live. Set up alerts when you reach, say, 75% of your AI Unit allotment or data capacity. Control usage by avoiding unnecessary runs (for example, don’t execute expensive AI analyses on data that hasn’t changed) and by cleaning up stale data to reduce storage. If usage trends higher than expected, talk to a SAP proactively about adjusting your plan or pricing to avoid surprise charges.

Q: How can we justify the cost of these AI and data tools to our finance team?
A: Link the cost to business outcomes. For example, if Joule’s AI assistant saves your support team 500 hours per quarter, calculate the dollar value of that time versus the cost of the AI units used. Often, the productivity gains or efficiency improvements will far outweigh the fees. Also, consider that using SAP’s built-in AI and analytics can be more cost-effective than integrating third-party tools – an argument that these costs are part of optimizing your overall SAP investment.

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