At SAP Sapphire Orlando 2026, SAP set out its AI strategy in much greater detail.
The focus was on the ‘Autonomous Enterprise’, comprising the ‘SAP Business AI Platform’, ‘Autonomous Suite’ and ‘Joule Work’.
The aim is to use AI agents to orchestrate business processes more autonomously in future, prepare data-driven decisions and have routine tasks carried out.
For mid-market companies and large corporations, this raises a key question: what do these developments mean in concrete terms for existing SAP landscapes, cloud transformations and the use of SAP S/4HANA?
This article explains the most important innovations from Sapphire Orlando 2026, contextualises SAP’s strategy and answers the key questions currently on companies’ minds.
SAP uses the term ‘Autonomous Enterprise’ to describe its vision of a company in which AI systems increasingly support, coordinate and, in some cases, automatically execute business processes independently.
Unlike traditional automation or “AI-first” approaches, the new “AI-native” approach is not based on isolated application data, application-specific governance or a Software-as-a-Service delivery model, but on context-based decisions using AI.
The key point is this: context is the real competitive advantage in the AI era, not the model. Put simply: AI understands the interrelationships across system boundaries – in other words, what, why and how a company does something.
In the SAP environment, this means in concrete terms:
People remain a central part of the decision-making processes. SAP explicitly does not position the Autonomous Enterprise as a fully autonomous organisation, but rather as an AI-supported environment in which employees are relieved of some of their workload and processes are orchestrated more intelligently.
Specifically, the Autonomous Enterprise consists of:
This is a key component of SAP’s new strategy.
The solution enables SAP to equip existing business applications with AI agents. These AI agents can execute processes from start to finish. The aim is to provide seamless end-to-end support for business processes across various areas of the organisation.
SAP utilises domain-specific Joule assistants, which, with over 200 specialised agents, automate entire business processes in finance, supply chain, HR and customer experience – thereby, according to SAP, reducing the financial close from weeks to days, for example.
In addition, SAP has introduced SAP Industry AI and expanded its industry portfolio with seven autonomous solutions. These solutions enable end-to-end mapping of industry processes. They also integrate industry-specific process logic, data models and regulatory requirements.
At Sapphire Orlando 2026, the focus was particularly on the following innovations:
One thing became particularly clear: SAP is increasingly evolving from a traditional ERP provider into a platform provider for AI-powered business processes.
SAP Joule plays a key role within SAP’s new strategy. In future, Joule is set to serve as the central user interface for AI-powered interactions.
Employees describe a goal (intent-based navigation) and can use natural language to:
Unlike traditional chatbots, Joule accesses business data, process context and corporate rules. This is intended to enable significantly more precise and context-sensitive responses.
A key objective is that users will no longer have to switch between different SAP systems, but will instead be able to manage tasks via a unified AI interface.
RISE and GROW are being expanded. The aim is to facilitate and accelerate the transition to the cloud and the adoption of AI with the help of AI solutions. Through both RISE and GROW, customers gain access to the Joule Assistant portfolio:
New development: On-premises customers are also to be given access to selected AI scenarios – at least as a bridge to the cloud. Prerequisite: Customers must sign a RISE contract and commit to migrating the majority of their current system landscape to the SAP Cloud.
A term that came up particularly frequently at Sapphire was ‘Agentic AI’.
This is how SAP describes AI agents that can respond to, assist with, and even actively carry out tasks. These AI agents work in a goal-oriented manner and can independently coordinate multiple steps within a process.
Examples of this in business include:
The main difference from traditional automation is that Agentic AI can react flexibly to situations.
| Traditional automation | Agentic AI |
|---|---|
| Rule-based | Context-based |
| Rigid workflows | Dynamic decisions |
| Individual tasks | End-to-end processes |
| Predefined workflows | Adaptive systems |
| Reactive | Proactive |
Not every business process is equally suited to autonomous AI scenarios.
Standardised processes involving large volumes of data and recurring decisions are currently particularly relevant.
These include, amongst others:
In these areas in particular, SAP promises significant efficiency gains through AI-supported process automation.
For many organisations, the most important question is not which AI features SAP is introducing, but what prerequisites are required for them.
This is because autonomous processes only function reliably if certain foundations are in place.
These include, in particular:
Organisations with highly customised ERP landscapes face particular challenges. Many existing SAP systems have been extensively customised over the years and contain heterogeneous process structures.
This means that the path to autonomous operation often begins not with AI, but with process standardisation and data harmonisation.
SAP S/4HANA and the SAP Business Technology Platform form the technological foundation of the new AI strategy.
SAP makes it clear that many new AI features are being developed primarily for modern cloud environments.
The BTP plays a central role in:
For many organisations, this makes SAP BTP increasingly strategically relevant.
The market for enterprise software is currently undergoing massive change. Many providers are investing heavily in generative AI and autonomous process support.
SAP is pursuing a clear strategy in this regard:
The combination of business data, process knowledge and AI is intended to create a competitive advantage. The key difference compared to many generic AI solutions lies in the business context.
SAP systems already contain:
This information forms the basis for AI agents not only to generate content, but also to actually support business processes.
Despite technological advances, numerous challenges remain.
These include, in particular:
Data quality
AI systems only deliver reliable results if the underlying data is consistent and up to date.
Process complexity
Many companies have SAP landscapes that have evolved over time, featuring bespoke processes.
Governance and compliance
Autonomous decisions require clear rules, roles and responsibilities.
Change management
The introduction of AI-supported processes significantly alters working methods and responsibilities.
Integration
Many companies continue to work with hybrid landscapes comprising cloud and on-premise systems.
It is precisely these issues that determine how quickly companies can actually benefit from autonomous processes.
Medium-sized organisations will also be affected by this development — though not necessarily immediately by fully autonomous processes.
The more important questions to start with are:
For many companies, the first step is therefore likely to be:
The autonomous enterprise will thus emerge through evolution rather than revolution.
Sapphire Orlando 2026 demonstrated that SAP is significantly accelerating its AI strategy.
SAP is increasingly positioning itself as a platform provider for intelligent, AI-powered business processes.
The focus is not on individual AI features, but on the combination of:
For SMEs and large corporations, this means one thing above all: the technological foundation for AI is increasingly becoming a strategic competitive factor.
At the same time, however, it is also clear that successful AI projects must continue to be built on stable processes, good data quality and modern cloud architectures.
