SAP AI Agents in 2026: Joule Studio features & case studies (original) (raw)

SAP predicts that AI agents could support up to 80% of the most-used business tasks in SAP. 1 We evaluated SAP’s AI agent portfolio, related case studies, and supporting infrastructure and identified three shifts shaping SAP’s AI agent strategy:

From assistants to execution: Agents are embedded into core business processes rather than acting as standalone copilots.
Interoperability standards: Protocols such as MCP and Agent-to-Agent (A2A) point to a move beyond vendor-specific agent stacks.
Platform-driven orchestration: Agent creation, runtime, and execution are consolidated within SAP’s ERP and cloud ecosystem.

The table shows some other enterprise AI agent builder providers that can be an alternative to SAP AI agent Joule:

Explore these SAP AI agents capabilities and real-life use cases:

What are SAP AI agents?

SAP AI Agents, powered by the Joule AI copilot framework, act as domain experts across finance, HR, supply chain, and IT.

These agents are built on SAP’s Business Technology Platform (BTP) to autonomously manage multi-step business workflows and make data-driven decisions using context from SAP’s Knowledge Graph.

What is the name of the AI agent in SAP?

SAP AI agent refers to SAP AI Copilot, autonomous AI agent capabilities under SAP Joule Studio that can streamline operations and deliver business insights. Here is how AI agents in SAP have been integrated:

In Q1 2026, SAP Joule Studio agent builder has become generally available (GA). Enterprises can design custom Joule agents and skills, using SAP’s built-in business knowledge and AI services.
In Q4 2025, SAP introduced role-based AI assistants within Joule to further streamline how users interact with these agents. Each assistant is tailored to a specific user role and automatically taps into the right Joule Agents for the job. For example, a finance manager forecasting cash flow or an HR professional addressing headcount can get the right insights and actions without guessing which agent to invoke with role-based assistants.
SAP also announced a “Deep Research” capability in Joule, which allows users to ask more complex, multi-domain questions. Joule can synthesize internal SAP data and external intelligence to deliver strategic analysis, recommendations, and context-aware insights within one conversational interface.
By Q1 2025, SAP expanded Joule’s development capabilities for developers and its NLP inquiry scope to use real-time data from SAP analytics solutions, enhancing its ability to provide up-to-date insights.
In Q4 2024, SAP released Joule Studio in SAP Build, providing a low-code/no-code environment for businesses to create, deploy, monitor, and manage custom Joule skills.

Integration across SAP ecosystem

With SAP integration suite, these agents connect across different systems, ensuring efficient workflow automation. Some of the SAP products that Joule, SAP AI agents, is embedded into:

SAP HANA Cloud, SAP LeanIX, SAP Sales Cloud, SAP Signavio, S/4HANA Cloud Public Edition by the end of 2024.
SAP Service Cloud and SAP Concur by early 2025.

As of late 2025, SAP reports having more than 400 AI-driven use cases embedded across its applications. For example, a new Receipt Analysis Agent in Concur Expense can automatically fill in missing expense details from receipt images.

Joule also operates across third-party applications, providing contextual assistance directly within users’ workflows. Its cross-application presence enables consistent, AI-driven support and improves overall employee productivity.

AI Agent Hub within SAP LeanIX

SAP is rolling out an AI Agent Hub within SAP LeanIX, allowing organizations to monitor, govern, and manage their portfolio of AI agents from a central dashboard. The hub will serve as a system of record for all agents, like SAP’s, custom-built ones, or even third-party implementations, and help ensure transparency across deployments.

The hub will also support recommendations of agent deployment (via its connection to process mining and architecture tools) and provide executive-level visibility into agent ROI and usage patterns.

Multi-agent collaboration

Without AI agents, Joule Studio could handle isolated tasks, such as retrieving data, extracting insights, and answering employee queries. With the introduction of collaborative AI agents specialized in distinct business functions, Joule can execute end-to-end processes, integrating actions across SAP systems and departments.

By linking actions across departments, Joule enables connected, cross-enterprise outcomes. This coordination allows business processes in finance, procurement, and supply chain to deliver measurable results together rather than in isolation.

For instance, resolving a payment dispute might involve multi-agent teamwork, such as collections, invoicing, and customer support agents working together.

Agent-to-Agent (A2A) interoperability protocol

At NRF 2026, SAP announced a Storefront Model Context Protocol (MCP) server for SAP Commerce Cloud (planned for Q2 2026). The MCP server allows AI agents to discover products and execute transactions autonomously, without traditional storefront interfaces.

supports emerging agent standards such as MCP and aligns with SAP’s work on an Agent-to-Agent (A2A) interoperability protocol. These servers also align with SAP’s Agent-to-Agent (A2A) interoperability. A2A enables Joule agents to collaborate with other SAP agents and third-party agents within standardized workflows.

Together, MCP and A2A signal SAP’s shift toward cross-agent, cross-vendor execution, where enterprise workflows are no longer confined to single assistants or closed ecosystems.

Checkout browser MCP benchmark to identify MCP server infrastructures that support web-enabled agents
Compare remote browsers environments and evaluate how agents interact with the open web.

Microsoft 365 Copilot Integration

Joule integrates with Microsoft 365 Copilot, allowing users to access shared skills and data across both ecosystems. This interoperability supports collaboration between enterprise AI platforms.

For example, a procurement agent might consult a logistics agent directly, or a finance agent might reach out to a forecasting agent, depending on the context. This design moves agent ecosystems toward a more connected, composable architecture.

Specialized agents in the business ecosystem

Instead of a single generalist agent, multi-agent networks divide tasks into specialized roles. Each AI agent specializes in a specific business function, enabling expertise-driven automation and collaboration across domains such as finance, supply chain, and service management.

SAP has been rapidly expanding its library of specialized Joule agents. At SAP Connect 2025, the company unveiled 14 new Joule Agents spanning finance, HR, procurement, supply chain, and industry-specific scenarios. Each agent is essentially a subject-matter expert. For example:

In finance, a Cash Management Agent can reason over daily bank statements and automate reconciliations, potentially saving up to 70% of the time finance teams spend on manual cash positioning tasks.
In procurement, a Bid Analysis Agent automatically compares complex supplier bids (factoring in unit prices, shipping costs, payment terms, etc.) and highlights the best options, eliminating manual spreadsheet analysis.
In the supply chain domain, a Production planning and Operations Agent checks material and capacity availability. In Q1 2026, this agent is expected to autonomously validate and release production orders when required conditions are met, accelerating order-to-delivery cycles.

By dividing work among such specialists, SAP’s multi-agent ecosystem can handle intricate end-to-end processes with expert precision in each area.

Figure 1: Joule SAP AI agents collaborating on a payment dispute.2

Human in the loop

AI agents are designed to work autonomously but operate within a framework where humans remain in control. SAP AI Copilot acts as a “conductor,” orchestrating the collaboration between SAP AI agents, while humans provide guidance as “composers” by defining tasks and objectives.

Despite human intervention is essential at this point, SAP envisions an era of autonomous enterprises where:

Businesses operate with minimal human intervention.
Streamline supply chains, automate transactions, and proactive error handling.
Reduce repetitive tasks, creating time for higher-value activities.

SAP knowledge graph

The SAP Knowledge Graph serves as the foundation for Joule’s advanced capabilities. With this capability, Joule provides insights at scale through natural language queries. Employees can access analytics and contextual data instantly, enabling faster, evidence-based decisions across functions.

Contextualized data: Organizes and connects data from SAP applications to provide meaningful insights.
Mapped business relationships: Links relationships between business entities (e.g., invoices, orders, and customers) to enhance decision-making and streamline processes.
Proactive problem-solving: Identifies emerging issues early, enabling timely interventions before they escalate.
Enabled innovation: Detects trends, uncovers patterns, and suggests innovative operational strategies that may not have been previously explored.

Top SAP AI Agent use cases with Joule

SAP AI agents can function both in interactive applications and in the background, handling routine tasks or responding to real-time events. Below are hypothetical use cases demonstrating the potential of Joule and its collaborative AI agents:

Figure 2: Joule SAP AI agents applications in different business departments.3

Check out SAP conversational AI for more use cases and real-life applications.

1. Dispute management

SAP AI agents can handle incorrect/missing invoices, unapplied credits, duplicate/denied payments, and dispute resolution. For example, Joule can detect a payment dispute, such as a duplicate payment or an invoice mismatch, through automated monitoring of financial data. Then, the agent can automatically:

Manage the exchange of emails and communications between relevant departments or external stakeholders, ensuring all necessary information is gathered.
Identify and correct errors in invoices, such as missing details or incorrect amounts.
Analyzes denied payments to determine the root cause, whether due to insufficient funds, incorrect account details, or mismatched references.
Provide actionable solutions, such as applying credits, issuing corrections, or escalating unresolved issues to human reviewers.

2. SAP finance automation

Administrative automation: Streamline billing processes, prepare ledger reports, and handle compliance documentation with minimal manual intervention.
Specialized financial recommendations: Offer strategic advice on budget allocation, portfolio management, and credit or insurance approvals.
Fraud detection: Monitor transactions in real time, flagging potential fraudulent activities and protecting enterprise assets.
Cash management agent: Reasons over daily bank statements to automate reconciliation tasks, detect surpluses/shortages, and suggest optimizations (planned GA in Q1 2026).
International trade classification agent: can analyze product data and trade regulations to recommend tariff codes and compliance classifications (beta in December 2025, GA beyond).

Figure 3: An example of SAP AI agents’ application in finance department.4

3. SAP HR AI agents

Talent acquisition: Automate job postings, generate candidate shortlists, and manage onboarding processes to streamline hiring.
Employee retention: Monitor employee performance, engagement, and feedback, delivering actionable insights to improve retention and foster team building.
HR process optimization: Handle administrative tasks, from updating employee records to managing payroll discrepancies, freeing HR professionals to focus on strategic initiatives.

Figure 4: An example of SAP AI agents’ application in HR department.5

4. Joule studio for IT

Coding assistance: Provide developers with tools to generate code and app logic using natural language, ensuring alignment with SAP programming models. A recent evaluation study compared SAP Joule’s generative capabilities in JavaScript code generation against 29 other models using the HumanEval-X benchmark. Joule achieved a strict accuracy of 80.49%, ranking as the fifth-best model in that test set.6
Cloud transformation Support: Offer on-demand guidance for best practices, streamlining cloud migration processes while maintaining consistency with organizational standards.
Project acceleration: Reduce manual coding efforts, enabling faster project delivery and minimizing timelines.
Cost efficiency: Lower development costs by automating repetitive tasks and improving accuracy.
Integration: Ensure smooth integration of SAP solutions into IT ecosystems for enhanced operational efficiency.

Figure 5: An example of SAP AI agents’ application in IT department.7

5. SAP Joule for marketing and customer support

Personalized campaigns: Analyze customer data to create tailored marketing strategies, personalized calls-to-action (CTAs), and engagement plans.
Market trend forecasting: Provide insights and recommendations for identifying growth opportunities and predicting market changes.
Enhanced customer relationship management (CRM): Utilize large language models (LLMs) to manage customer interactions, resolve disputes, handle transactions, and analyze feedback for improved customer satisfaction.
Content generation: Use generative AI to produce branded text and imagery, aligning with the company’s voice and values.

Figure 6: An example of SAP AI agents’ application in sales and marketing.8

6. SAP supply chain AI

Additional AI agent-driven workflows will be introduced to the supply chain portfolio by March 2025, further demonstrating the versatility of these agents.

Inventory management: Automate inventory tracking and trigger restocking orders to maintain optimal supply levels.
Delivery optimization: Customize delivery routes to reduce transportation costs and environmental impact while ensuring timely shipments.
Quality assurance: Simplify inspection processes, detect manufacturing errors, and ensure the integrity of goods during transportation and storage. Discover what is quality assurance (QA) and data QA.
Predictive maintenance: Monitor equipment performance and predict repairs or replacements before breakdowns occur, reducing downtime and costs. Explore more on predictive maintenance.

7. SAP retail AI

SAP AI agents are planned to be applied in retail workflows. Some of these include:

Demand and inventory planning: Retail Intelligence in SAP Business Data Cloud applies AI to analyze sales, inventory, and demand signals.
Order reliability agent: It is expected to detect fulfillment risks such as stock shortages, delivery delays, or execution issues and initiates corrective actions before orders are impacted (Q2, 2026).
Autonomous retail execution: Retail agents can increasingly coordinate actions across commerce, supply chain, and external systems rather than operating in isolated workflows.

Real-life examples of SAP AI agents

Here are some SAP Joule case studies gathered from SAP blogs9 , websites and third-party sources10

Other AI agent providers to SAP

Many large enterprises operate on heavily customized SAP environments, with on-premise deployments, tailored modules, and numerous add-ons. These complex setups often limit the effectiveness of SAP’s native AI agents, creating demand for third-party AI solutions that can bridge the gap.

Several independent providers now develop and deliver AI agents designed to integrate with customized SAP systems, improving automation, transparency, and decision-making across functions:

Hypatos delivers domain-specific AI agents that can integrate to SAP to automate document processing, handle complex data flows, and reduce manual errors.
SpendConsole provides a chatbot solution that integrates with SAP systems to digitize and streamline invoice processing to enhance productivity, compliance, and fraud protection.
Conduct is a new AI startup founded by former Palantir engineers that focuses on making legacy enterprise systems like SAP understandable and operable through AI. It builds an intelligent layer on top of customized SAP environments, helping organizations visualize, interpret, and optimize their systems more effectively.

There are also other tech giants that employ AI agents, like Oracle AI agents.

Yes, SAP offers multiple AI tools integrated into its ecosystem, such as:

The Generative AI Hub in SAP AI Core and SAP AI Launchpad that provides scalable management of AI artifacts, enabling custom AI solutions and application extensions.
The SAP Foundation Model which focuses on structured data analysis. SAP also introduced SAP-RPT-1, its first enterprise relational foundation model designed for structured business data.
- Unlike typical LLMs, SAP-RPT-I is optimized for tabular data prediction, forecasting, and relational business logic.
- Available in multiple configurations via SAP’s Generative AI Hub.
Joule that is a generative AI copilot, delivers code generation, data insights, and process automation with natural language interaction.
SAP AI Services that can enhance business processes with prediction models, document automation, and recommendation systems.
VectorEngine and KnowledgeGraph in SAP HANA Cloud that can help intelligent data applications and contextual AI insights for business operations.

Discover more on SAP Business AI applications, like SAP BTP Generative AI. SAP BTP automation can integrate these LLMs into other SAP-certified tools and apps (e.g Redwood and SAP), such as:

FAQs

What are agents in SAP?

SAP AI agents leverage AI capabilities like natural language processing, machine learning, and multi-agent systems to execute workflows, analyze data, and improve business processes.

SAP’s generative AI ecosystem, including tools like Joule, allows users to develop custom AI agents for specific roles. These agents can communicate naturally, design workflows, use software tools, and collaborate with humans or other agents. Their applications in SAP include procurement optimization, process automation, and integration with internal systems for tailored solutions.

Cite this research

Pick the format that matches where you're publishing. Pasting the link version into your CMS preserves the backlink.

Hazal Şimşek (2026) - "SAP AI Agents in 2026: Joule Studio features & case studies". Published online at AIMultiple.com. Retrieved June 11, 2026, from: https://aimultiple.com/sap-ai-agents [Online Resource]

Şimşek, H. (2026, June 11). SAP AI Agents in 2026: Joule Studio features & case studies. AIMultiple. https://aimultiple.com/sap-ai-agents

@misc{imek2026, author = {Şimşek, Hazal}, title = {{SAP AI Agents in 2026: Joule Studio features & case studies}}, year = {2026}, month = jun, howpublished = {\url{https://aimultiple.com/sap-ai-agents}}, note = {AIMultiple. Retrieved June 11, 2026} }

Hazal Şimşek

Industry Analyst

Hazal is an industry analyst at AIMultiple, focusing on process mining and IT automation.

View Full Profile