AI in 2026 – What It Means for SAP Customers

AI is shifting from labs and pilots to the fundament of everyday enterprise operations. In 2026, AI will not be an add-on to your technology portfolio; rather, it will start to shape how enterprise systems are designed, governed, licensed and secured, including those like SAP.

From JNC’s point of view, as a vendor-agnostic SAP licensing, commercial, and security expert, this is mostly good news. AI provides real possibilities for increased efficiency, better decision making and deeper company relationships.

This article outlines five defining AI themes for 2026 and what they mean for SAP customers. The first theme is:

SAP value will be unlocked through specialized AI models:

The next wave of enterprise AI will be powered by domain-specific foundation models, which are trained on organized business data that SAP system generate in large quantities. This is a big opportunity for SAP users, because it makes AI no longer a theoretical experiment but rather a real-life, high-value use case that can be executed.

In SAP environments, these models will perform the following tasks:

More accurate forecasting across finance, manufacturing, and supply chain
Earlier detection of anomalies, risks, and inefficiencies
Better optimization of inventory, production, and logistics

This shift aligns well with SAP’s strengths in transactional data. However, as AI models interact more deeply with SAP data, organizations must be mindful of how data is accessed and consumed.

SAP landscapes will move toward AI-native architecture:

In 2026, many SAP environments will shift toward AI-native architectures, where AI features are built into underlying applications instead of being added onto them. This enables more adaptive, intent-driven processes and reduces reliance on rigid, transaction-based workflows.

Area	Potential Benefits	Additional Complexity
Process Design	More adaptive, intent-driven processes embedded directly within SAP applications	More complex system design compared to traditional transaction-based workflows
Automation	Greater end-to-end automation across business processes	Increased dependency on AI models and underlying data quality
User Experience	Improved productivity through AI-assisted insights and decision-making	More nuanced access management for AI-driven actions and recommendations
Innovation Model	Faster innovation without continuous custom development or enhancements	Greater governance requirements to control AI behavior and outcomes
Security & Governance	More consistent use of AI across standard SAP functionality	Expanded scope for authorization, monitoring, and compliance controls

Agent-based automation will require stronger governance:

AI-based agents who can plan, reason, and execute multi-step tasks will interoperate with human SAP users even more. They can help drive efficiency by taking the cognitive load of labour-intensive processes that needed manual involvement in the past.

‬ From the optimistic perspective, AI agents ‪can:

Reduce operational workload.
Improve consistency in process execution.
Support faster decision-making across SAP functions.

However, as the number of agents grows, governance becomes critical.

SAP consumption will be reshaped by intent-driven ERP:

Generative interfaces and intent-driven ERP experiences represent a major usability improvement for SAP customers. Instead of navigating multiple transactions and applications, users will increasingly express outcomes and let SAP systems and AI agents handle the execution.

This shift can:

Improve user adoption of SAP.
Reduce training requirements.
Increase overall productivity.

At the same time, abstracting user interaction from traditional transactions complicates measuring SAP usage.

Sovereign AI and data residency are reshaping SAP’s strategy:

Data residency requirements and sovereign AI are influencing how companies make their SAP platforms. Overall, this trend is a positive one: it encourages stronger data governance and transparency to thoughtful architectural choices related to AI and cloud services.

Area	Potential Benefits	Key Trade-Offs
Data Control	Greater autonomy over storage, processing, and access to business-critical SAP data	Reduced flexibility compared to fully global cloud platforms
Regulatory Compliance	Improved alignment with regulatory, industry, and government requirements	Higher costs driven by region-specific infrastructure and compliance controls
Use of AI in SAP	Increased confidence applying AI to sensitive finance, HR, supply chain, and public sector workloads	Additional architectural and operational complexity
Operational Resilience	Stronger operating models during geopolitical and regulatory uncertainty	More complex coordination across multinational SAP landscapes
Commercial & Licensing Impact	Clearer governance for data sovereignty and AI usage decisions	Greater need for detailed SAP contract, cloud, and licensing reviews

Preparing your SAP environment for AI in 2026

By 2026, AI will be a core capability within SAP environments. Organizations that benefit most will be those that approach AI adoption strategically, embracing innovation while maintaining control.

From JNC’s perspective, preparation should focus on:

Proactive SAP license governance and optimization
Aligning AI-driven usage with SAP contract terms
Strengthening SAP security, user management, and GRC controls
Designing SAP architectures that support AI without increasing risk
Maintaining audit readiness in increasingly automated landscapes

AI creates a significant opportunity for SAP clients – but that must be balanced. Organizations with strong governance, commercial clarity, and proper security capabilities for AI deployment will be confident about its deployment, protecting themselves against preventable risk.

Source: AI in 2026

This article was written by Valeria Pulbere.
Connect with Valeria on LinkedIn to stay informed on SAP licensing, commercial strategy and security best practices.