At SAP Sapphire 2026, Christian Klein opened the event with a question that quietly shaped almost every keynote, demo, and partnership announcement that followed:
“Will SAP actually be a software company in the future?”
It was a provocative question, especially coming from the CEO of one of the world’s largest enterprise software companies. But after three days of announcements around AI agents, orchestration, governance, runtime security, and autonomous workflows, the direction became much clearer.
SAP is no longer positioning itself simply as a provider of enterprise applications. Instead, it is positioning itself as the operational foundation for the “Autonomous Enterprise”.
And that distinction matters. Because Sapphire 2026 wasn’t about adding AI features into ERP screens, but to redefine how enterprise systems operate when AI agents become active business coworkers inside core processes.
And, as official partners, the Inclusion Cloud team was there taking notes of what’s coming for enterprise systems.
What Does SAP Mean by “Autonomous Enterprise”?
One of the core ideas repeated throughout SAP Sapphire 2026 was that generative AI alone is not enough for enterprise execution.
LLMs can generate text, summarize information, or assist users conversationally. But enterprise operations work under a completely different standard.
Financial closes cannot be “mostly correct.” Procurement approvals cannot ignore governance rules. Supply chain workflows cannot hallucinate inventory data or compliance requirements.
And, for SAP, this is the fundamental limitation of the current AI market.
Enterprise AI needs operational context. And that is why SAP’s Autonomous Enterprise vision is centered around a very specific idea: the ERP as the operational brain of the company.
For decades, SAP systems have accumulated deep business process knowledge across finance, procurement, supply chain, HR, manufacturing, and customer operations. They already contain the know-how that enterprises depend on every day.
So, the strategic challenge is now how to inject that operational knowledge into AI agents. And that’s why SAP introduced the Knowledge Graph as a critical component of the architecture, giving AI agents a semantic map of:
- Business entities.
- Workflows.
- Relationships.
- Dependencies.
- Organizational structures across SAP and non-SAP systems.
And, on top of that foundation is the SAP Autonomous Suite, which deploys +50 domain-specific Joule Assistants capable of orchestrating +200 specialized AI agents across finance, procurement, supply chain, HCM, and customer experience.
How SAP’s Strategic AI Partnerships Work
Now, one of the most important takeaways from Sapphire 2026 is that SAP is not building the autonomous enterprise alone.
But these strategic partnerships are not simple marketplace integrations or isolated AI announcements. Together, they reveal how to assemble the different layers required to operationalize enterprise AI safely at scale.
But let’s see what each one role inside SAP’s broader business AI architecture.
Anthropic: The Reasoning Layer
SAP’s partnership with Anthropic centers around bringing Claude into the SAP Business AI Platform as a core reasoning engine for Joule agents.
In practical terms, Claude helps power:
- Complex reasoning.
- Multi-step decision making.
- Contextual analysis.
- Agentic workflows across finance, HR, procurement, and supply chain.
But the important detail is that Claude does not operate independently from SAP systems. Its reasoning is grounded in SAP business data, workflows, governance rules, and operational context through the Business AI Platform.
This reflects SAP’s broader AI conception: LLMs provide intelligence, but ERP systems provide trusted business context.
NVIDIA: The Secure Runtime Layer
The collaboration with NVIDIA focuses on one of the biggest enterprise AI concerns: trusted execution.
Through NVIDIA OpenShell, SAP is helping co-develop secure runtime environments for autonomous AI agents operating inside enterprise systems, introducing:
- Sandboxed execution.
- Policy enforcement.
- Runtime isolation.
- Governance controls.
In simple terms, this is the infrastructure that helps enterprises trust AI agents operating inside sensitive business workflows.
SAP’s role is especially important here because it brings enterprise-grade governance requirements into the runtime itself, including identity management, auditability, policy semantics, and compliance alignment.
Palantir & Accenture: The Transformation Layer
SAP’s expanded collaboration with Palantir and Accenture focuses on AI-assisted ERP modernization.
The partnership combines SAP’s migration assistants, Palantir AIP, and Accenture’s transformation services to accelerate SAP Cloud ERP migrations using AI-driven analysis, remediation, testing, and impact assessment.
The strategic implication is significant: SAP is positioning AI not only as an operational layer for the future, but also as a mechanism for accelerating the transition away from fragmented legacy landscapes.
n8n: The Workflow Orchestration Layer
The partnership with n8n introduces visual AI workflow orchestration directly inside Joule Studio.
This gives enterprise teams a low-code environment to:
- Orchestrate AI agents.
- Connect SAP and non-SAP systems.
- Automate workflows.
- Build integrations visually.
Because n8n supports +1,000 integrations, the partnership expands SAP’s ability to operate across broader enterprise ecosystems instead of remaining limited to SAP-native environments.
This is especially relevant for organizations trying to operationalize AI across fragmented technology stacks.
Parloa: The Customer Interaction Layer
SAP’s partnership with Parloa extends agentic AI into customer-facing operations.
Parloa’s conversational AI agents integrate directly with SAP Service Cloud, allowing customer interactions to connect in real time with enterprise workflows, operational data, and service processes.
The goal is to move beyond isolated chatbots toward AI-driven customer experiences grounded in actual business operations. This creates continuity between customer conversations, enterprise workflows, service operations, and business data.
What Each SAP AI Layer Actually Does
One challenge many enterprises now face is understanding how SAP’s growing AI portfolio fits together operationally. And the Sapphire 2026 helped clarify that architecture:
- SAP BTP: acts as the integration and application layer connecting APIs, workflows, services, and enterprise systems.
- SAP Business Data Cloud: functions as the governed enterprise data layer that contextualizes AI using operational business information.
- SAP Business AI Platform: becomes the intelligence layer powering AI assistants, agents, automation, and reasoning across SAP applications.
- SAP Knowledge Graph: provides the semantic relationship layer mapping workflows, dependencies, approvals, and organizational context.
- Joule 2.0: acts as the conversational orchestration layer connecting users, workflows, agents, and enterprise actions.
- Joule Studio: becomes the development environment for building enterprise agents and agentic workflows using no-code, pro-code, and AI-native approaches.
So, Will SAP Still Be a Software Company in the Near Future?
By the end of Sapphire 2026, the answer to Christian Klein’s opening question became much clearer.
So no, SAP is no longer positioning itself as a “traditional” software company. It is positioning itself as a Business AI company. And while that may sound like branding language at first glance, the implications for organizations are very profound.
Enterprise software is moving toward systems capable of participating directly in operational decision-making. And that changes how organizations will approach ERP strategy over the next years.
The conversation is no longer only about migrating infrastructure or modernizing interfaces. It is increasingly about preparing enterprise environments where AI agents can operate safely across business processes, data models, workflows, approvals, and organizational rules.
And that creates a much larger operational challenge than simply deploying new features.
Organizations need to think about:
- Whether their current process architecture is structured enough for autonomous execution.
- Whether their data landscape is governed enough to support contextual AI reasoning.
- Whether their integrations, approvals, and operational policies can support agents acting across SAP and non-SAP systems in real time.
And, as official SAP partners, at Inclusion Cloud we are helping organizations navigate through this transition. We help companies modernize SAP landscapes, integrate enterprise ecosystems, operationalize AI workflows, and prepare their business processes for the next generation of enterprise execution.
Because ultimately, the biggest takeaway from Sapphire 2026 may not be that SAP is becoming an AI company. It is that enterprise AI is finally becoming operational.
So, if your organization is evaluating their AI strategy, book a discovery call.
