SAP cuts travel and hiring to fund AI, even as its cloud targets slip

SAP is snapping its wallet shut on travel and hiring, then quietly redirecting that momentum into AI. In an internal email seen by Bloomberg, SAP said it will “exclusively focus new hiring on selected profiles only, mainly core AI roles, that are critical for our long-term success.” The same message also indicated travel unrelated to AI development would be put on hold.

SAP also spelled out the logic publicly. In a statement to The Register, an SAP spokesperson said the company “continually reviews its investments to ensure resources are focused on the areas that will drive long-term customer value and innovation,” adding that SAP is prioritizing “AI-related capabilities, talent, and technologies” while applying “greater discipline to hiring, external spending, and internal travel.” The spokesperson also emphasized that “Customer-facing activities and critical AI initiatives remain fully supported.” In other words: this is not a broad freeze. It is a reallocation.

For enterprise software executives, this is a familiar kind of trade-off, but with a more direct articulation than you usually see. SAP is in an intensely competitive enterprise application market where AI is rapidly moving from “nice-to-have” to table stakes. If your competitors are packaging AI into workflows, and customers start asking what is actually usable, leaders feel pressure to fund AI talent, platforms, and productization, not just pilots.

That helps explain why the company is taking a scalpel to costs that do not immediately create AI output. Hiring, business travel, and external supplier spending can be some of the easiest levers to pull quickly, particularly when internal teams can still deliver against customer-facing commitments and “critical AI initiatives.” SAP is effectively drawing a line between what management views as directly tied to AI delivery and what it considers optional or slower to impact. And because the internal message explicitly calls out “selected profiles” and “mainly core AI roles,” it signals that the AI workforce is the bottleneck SAP is trying to relieve.

Zoom out and you get another reason this matters: AI investment is happening under the shadow of cloud expectations. The source notes that SAP’s “big push for AI relevance comes despite SAP missing its earlier self-imposed targets to get users to the cloud and SaaS.” That is not a small footnote. In many enterprise software companies, cloud and SaaS transitions affect predictability of revenue, margin profile, and the operating cadence of product teams. SAP’s credibility with investors has likely been influenced by whether its transition is matching its own guidance.

The article provides a specific marker. In 2022, then-CFO Luka Mucic told investors that SAP expected support revenue to fall to €8.5 billion by 2025, down from around €11.5 billion in 2021, as users move from on-prem licenses and support to cloud subscriptions. Yet the 2025 full-year figure for on-prem software support is €10.5 billion, down 7 percent from 2024’s €11.29 billion and €2 billion off SAP’s target. That gap matters in the background because it can constrain how much latitude a company has to absorb missed expectations while still convincing the market it is steering the business correctly.

SAP’s AI push is not generic either. In May, the company introduced the Autonomous Enterprise concept, backed by a new SAP Business AI Platform for building and deploying enterprise AI grounded in “real business context” from its ERP, CRM, and HCM applications, and elsewhere in the enterprise. New products include Joule Studio 2.0, which helps developers create and manage AI agents. Agents created in Joule Studio are said to natively support Model Context Protocol and Agent2Agent to improve interoperability among AI agents, tools, and data sources. The article also notes agentic orchestration features designed to run across hybrid IT environments, and real-time data ingestion to support “context-aware processes” across SAP and third-party systems.

So where does the spending discipline fit? If SAP wants to scale enterprise AI grounded in its own business context, it needs both platform engineering and developer enablement. It also needs a workforce that can move quickly on agent building, orchestration, and integrations. Those are exactly the areas that typically demand specialized hires, and they are exactly the areas where reducing non-core spending can preserve budget without pausing shipping.

Second-order for the industry: SAP is showing a playbook other enterprise vendors will notice. When cloud transitions are behind schedule, companies often try to protect near-term differentiation with AI capabilities tied to existing customer data and workflows. That can buy time, but it also raises the stakes. Customers will expect AI to work in their environments, not just on demos, which means hybrid integration and interoperability are not “future work.” They are a current workstream.

In the end, the message from SAP is straightforward. Prioritize core AI roles. Pause travel not tied to AI development. Cut external and supplier spending. Keep customer-facing activity and critical AI initiatives fully supported. For decision-makers across the enterprise stack, the strategic question is whether your own investment plan is similarly calibrated, especially if you are trying to show AI momentum while still managing the financial optics of slower cloud progress.