With the introduction of the SAP Business AI Platform at SAP Sapphire 2026, SAP has placed a much stronger focus on Enterprise AI, AI agents and increasingly autonomous business processes within its platform strategy. At the same time, SAP Business Technology Platform, or SAP BTP, continues to exist as both a product and technology platform. This raises a central question for many SAP decision-makers: Is the SAP Business AI Platform the successor to SAP BTP, simply a new name, or a broader platform architecture?
The short answer is: SAP BTP is not simply being replaced by the SAP Business AI Platform. SAP now describes the capabilities of SAP Business Technology Platform as a core component of the SAP Business AI Platform. The new platform combines this technical core with business data, process context, AI models, agents and overarching governance.
The relationship can therefore be summarised as follows: SAP BTP remains the technical foundation for development, integration, extensions and automation, while the SAP Business AI Platform provides the broader strategic and technological framework for Enterprise AI.
In this article, you will learn what SAP Business AI Platform means, how SAP Business AI Platform and BTP are connected, which functions SAP BTP continues to provide and which additional components are introduced for data context, Agentic AI and AI Governance. We also explain what actually changes for existing BTP customers and which platform is relevant for which type of use case.
Key Facts About SAP Business AI Platform vs. BTP
The SAP Business AI Platform was introduced at SAP Sapphire in May 2026. SAP positions it as the technological foundation for Enterprise AI. It brings together AI, enterprise data, process context and governance so that organisations can develop, integrate, scale and operate AI agents, applications and workflows in a controlled manner.
The following points are particularly important when comparing SAP Business AI Platform vs. BTP:
- SAP BTP continues to exist and remains relevant for integration, application development, extensions, automation and technical platform services.
- The capabilities of SAP BTP form a core part of the SAP Business AI Platform.
- The SAP Business AI Platform extends this technical layer with enterprise-wide business context, SAP Business Data Cloud, SAP Knowledge Graph, AI models, Joule Studio and functions for governance and agent lifecycle management.
- SAP structures the platform around the three areas Build, Contextualize and Reason, and Govern.
- The renaming of the SAP BTP partner competency to “SAP Business AI Platform Competency” on 30 June 2026 does not mean that the SAP BTP product itself has been completely renamed.
- Existing BTP customers therefore do not need to start over technologically. Instead, their existing BTP strategy can be extended with data context, Agentic AI and AI Governance.
The key takeaway is:
SAP BTP provides essential technical platform capabilities. The SAP Business AI Platform combines these capabilities with AI, business data, process knowledge, agents and enterprise-wide governance.
Table of Contents
- What Does SAP Business AI Platform Mean?
- What Is SAP BTP?
- SAP Business AI Platform vs. SAP BTP: What Is the Difference?
- Does the SAP Business AI Platform Replace SAP BTP?
- Why Did the Impression Arise That SAP BTP Was Being Renamed?
- How Are SAP Business AI Platform and BTP Connected?
- Which SAP BTP Functions Are Part of the SAP Business AI Platform?
- What Additional Functions Does the SAP Business AI Platform Provide Compared with SAP BTP?
- What Role Does SAP Business Data Cloud Play?
- What Roles Do SAP Signavio and SAP LeanIX Play?
- What Does Agentic AI Mean Within the SAP Business AI Platform?
- What Roles Do Joule and Joule Studio Play?
- SAP Business AI Platform vs. BTP: When Should Companies Use Which Platform?
- Practical Example: AI-Supported Processing of a Supplier Enquiry
- What Changes for Existing SAP BTP Customers?
- Benefits of the SAP Business AI Platform BTP Architecture
- What Challenges Arise?
- Best Practices for SAP Business AI Platform vs. BTP
- Do's & Don'ts When Implementing the Platform
- Step by Step to the SAP Business AI Platform
- SAP Business AI Platform vs. BTP and Clean Core
- Conclusion – SAP Business AI Platform vs. SAP BTP Is Not an Either-Or Decision
- Frequently Asked Questions About the SAP Business AI Platform
- Would You Like to Assess Your SAP BTP and Business AI Strategy?
What Does SAP Business AI Platform Mean?
Anyone searching for “What does SAP Business AI Platform mean?” should first distinguish between SAP Business AI and the new SAP Business AI Platform.
SAP Business AI describes the broader AI strategy and AI functionality within SAP’s portfolio. The SAP Business AI Platform, by contrast, provides the technological foundation through which organisations can develop, integrate and operate their own AI agents, AI applications and intelligent workflows in a controlled manner.
SAP currently defines the platform as an Enterprise AI foundation that brings together AI, data, process context and governance. The focus is on AI that not only understands an individual prompt, but also understands the business context in which a request or action takes place.
At SAP Sapphire 2026, SAP described the new architecture as bringing together SAP Business Technology Platform, SAP Business Data Cloud and SAP Business AI within a unified and governed environment. A central component of this architecture is the SAP Knowledge Graph, which is designed to semantically represent relationships between business data, processes and business objects.
This shifts the focus compared with traditional AI projects. Instead of allowing an isolated chatbot to access individual data points, AI should be able to understand, for example:
which customer belongs to an order, which process status applies, which corporate policy is relevant, which permissions a user or agent has, and which downstream action is permitted from a business perspective.
This business context is one of the key differences between a general AI platform and the SAP Business AI Platform.
Further information: SAP Business AI
What Is SAP BTP?
SAP Business Technology Platform is SAP’s established technology platform for developing, extending, integrating, automating and operating modern enterprise applications.
SAP currently describes SAP BTP as a platform for integrating, automating, extending and developing AI-supported business applications and processes. At the same time, SAP explicitly states that the capabilities of SAP BTP now form the core of the SAP Business AI Platform.
SAP BTP continues to provide fundamental capabilities such as connecting SAP and non-SAP systems, developing extensions outside the ERP core, providing runtime environments, automating workflows and delivering identity, security and platform services.
Typical BTP components include:
SAP Integration Suite for integrations, APIs and events, SAP Build for applications and process automation, Cloud Foundry and Kyma as runtime environments, the SAP BTP ABAP Environment, as well as AI-related services and development tools.
For companies assessing their existing BTP architecture, SAP BTP therefore remains an independent and relevant technical concept.
Further information: SAP Business Technology Platform
SAP Business AI Platform vs. SAP BTP: What Is the Difference?
The comparison SAP Business AI Platform vs. SAP BTP becomes easier to understand when the two are not viewed as competing products.
| Criterion | SAP Business Technology Platform | SAP Business AI Platform |
|---|---|---|
| Abbreviation | SAP BTP | SAP Business AI Platform / BAIP |
| Primary purpose | Development, integration, extension and automation | Developing, contextualising, governing and scaling Enterprise AI |
| Classification | Technology platform and technical core | Overarching Enterprise AI foundation |
| Applications | Application development and extension | Uses BTP capabilities for AI-powered apps and agents |
| Integration | SAP Integration Suite, APIs, events, connectivity | Connects agents, applications, data and processes |
| Data | Platform and data services plus connected sources | SAP Business Data Cloud and semantic business context |
| AI | AI Foundation and additional AI services | Unified framework for Enterprise AI and Agentic AI |
| Process context | Through integrations and applications | Deeper business context across data, processes and relationships |
| Governance | Platform, security and service governance | Additional governance for agents, models and the AI lifecycle |
| Target architecture | Modern SAP platform architecture | Scalable and governed Enterprise AI architecture |
The table shows why SAP Business AI Platform vs. BTP is not a traditional product comparison.
The SAP Business AI Platform BTP relationship is better understood as an architectural model: Many technical capabilities continue to come from SAP BTP. The Business AI Platform adds to and orchestrates these capabilities within a broader AI strategy.
Does the SAP Business AI Platform Replace SAP BTP?
No.
SAP BTP continues to exist. SAP now explicitly describes BTP capabilities as the core of the SAP Business AI Platform.
Existing integrations, SAP Build solutions, cloud applications and side-by-side extensions therefore do not suddenly need to be replaced by an entirely new platform.
Instead, the introduction of the SAP Business AI Platform changes the perspective.
With SAP BTP, the typical question has traditionally been:
“How do we connect, develop and extend our enterprise applications?”
With the SAP Business AI Platform, another question is added:
“How do we enable AI agents to understand business data and processes and act on them within defined rules?”
The existing platform logic is therefore extended by a more comprehensive Enterprise AI layer.
Why Did the Impression Arise That SAP BTP Was Being Renamed?
One major reason is the SAP partner programme.
On 30 June 2026, the previous “SAP Business Technology Platform Competency” was renamed “SAP Business AI Platform Competency”. Existing partners with the corresponding BTP competency were automatically transferred. At the time of the change, the existing competency requirements were not fundamentally altered.
Understandably, this change led to search queries such as “new name for SAP BTP”, “SAP BTP successor” or SAP Business AI Platform vs. BTP.
However, the distinction is important:
The partner competency was renamed.
The SAP Business Technology Platform product continues to exist.
The fact that SAP still explicitly uses the term “SAP Business Technology Platform” on its current product pages while simultaneously describing BTP capabilities as the core of the SAP Business AI Platform supports exactly this interpretation.
How Are SAP Business AI Platform and BTP Connected?
SAP BTP provides a large part of the technical infrastructure required to integrate applications, agents and automations into enterprise landscapes in a productive way.
The SAP Business AI Platform extends this technical foundation, particularly through a more unified AI, data and context layer.
SAP currently structures the concept around three main areas:
1. Build
Organisations should be able to develop AI agents, applications and workflows and connect them to their existing systems.
Joule Studio and SAP Integration Suite, for example, play central roles here. SAP positions Joule Studio as an AI-first development environment for agents, apps and workflows. Integration Suite, in turn, connects agents, applications, data and systems.
This makes the importance of the SAP Business AI Platform BTP relationship particularly clear: The development, integration and runtime functions familiar from BTP remain essential.
2. Contextualize and Reason
An AI agent needs more than isolated data fields.
It must understand what information means within the organisation and how individual pieces of information are related.
SAP highlights SAP Business Data Cloud and SAP Knowledge Graph in this context. The Knowledge Graph provides a semantic layer that connects data, processes and relationships. SAP Business Data Cloud, meanwhile, is intended to make SAP and third-party data available for AI and analytics within a more consistent business context.
3. Govern
The third area focuses on governance, security and lifecycle management.
When AI agents do more than provide information and begin executing actions, the requirements for control increase significantly. Organisations need to understand which agents exist, what data they can access, which actions they are permitted to perform and how their performance and lifecycle are managed.
For this purpose, SAP includes elements such as the AI Agent Hub and a managed Joule Studio runtime within the SAP Business AI Platform.
Which SAP BTP Functions Are Part of the SAP Business AI Platform?
The term “part of” should not be interpreted as a simple list of products bundled together. SAP states instead that the capabilities of SAP BTP form the core of the new Business AI Platform.
Several BTP functional areas therefore remain fundamental to Enterprise AI.
Application Development and Extensions
Even in an agent-based world, organisations still need to develop traditional applications and extensions.
BTP-based development environments and SAP Build can provide the user interface, application logic and extension logic.
AI therefore does not replace traditional application development. Instead, applications can increasingly interact with AI agents and generative AI.
Integration
Integration becomes even more important for Agentic AI.
An agent can only act across systems if it has controlled access to the relevant applications, APIs, events and processes.
SAP Integration Suite connects SAP and non-SAP systems and supports API-based, event-driven and traditional integration scenarios. Within the SAP Business AI Platform, SAP describes Integration Suite as the layer that connects AI agents, applications, data and systems.
Further information: SAP Invoice Management
Process Automation
SAP Build Process Automation remains relevant for workflows, business rules and automated processes.
Within an AI architecture, such deterministic workflows can increasingly be combined with AI-supported interpretation or agent-based activities.
An organisation does not need to hand every process over to an autonomous agent. In many cases, a combination is more suitable: AI analyses or recommends, a defined workflow manages approvals, and the actual execution takes place through controlled system logic.
AI Services
Extensive AI functionality already existed on SAP BTP before the Business AI Platform was introduced.
Examples include AI Foundation and related AI services as well as the Generative AI Hub.
Within the SAP Business AI Platform, these capabilities are more closely connected with business context, agent development and overarching governance.
Platform Operations and Security
Accounts, permissions, connectivity, technical runtimes and monitoring also remain essential.
In fact, the more deeply agents interact with productive business processes, the more important robust technical platform services become.
What Additional Functions Does the SAP Business AI Platform Provide Compared with SAP BTP?
When comparing SAP Business AI Platform vs. BTP, the key difference is not that all existing BTP capabilities have been recreated.
Instead, the major change lies in the stronger combination of overarching AI functions and business context.
Enterprise-Wide Data Context
The SAP Business AI Platform is designed not only to provide agents with data, but also to help them understand the business meaning of that data.
SAP Business Data Cloud and SAP Knowledge Graph play central roles here.
Agentic AI
The platform is explicitly designed for developing and governing AI agents.
Agents should not merely answer questions. They should be able to pursue defined tasks and execute actions within their permission boundaries.
Overarching AI Governance
As the number of internal and external AI agents increases, organisations need to establish control over models, agents, identities, policies and lifecycles.
This governance aspect is a central pillar of the new platform.
Process and Transformation Knowledge
SAP’s Business Transformation Management solutions also play an important role in the overall vision. SAP describes Business Transformation Management as providing the SAP Business AI Platform with enterprise and transformation knowledge, particularly information about business processes and enterprise architecture.
What Role Does SAP Business Data Cloud Play?
SAP Business Data Cloud, or SAP BDC, is an important component of the new platform strategy.
SAP describes Business Data Cloud as the data foundation of the SAP Business AI Platform. Its purpose is to provide a trusted foundation through which applications and agents can access consistent business context.
This is essential for Agentic AI.
For example, an agent assessing a delivery delay needs more than a status value. It may also need to understand:
which customer is affected, which purchase order is involved, which supplier is responsible, what priority applies, which contractual conditions exist and which downstream processes may be triggered.
This context distinguishes Enterprise AI from simple prompt-based AI applications.
Further information: SAP Business Data Cloud
What Roles Do SAP Signavio and SAP LeanIX Play?
The SAP Business AI Platform is not aimed exclusively at developers.
To decide where AI can actually deliver business value, organisations also need transparency into business processes, systems and dependencies.
SAP Signavio provides process information and process analytics. SAP LeanIX creates transparency across applications and enterprise architecture.
This helps organisations answer questions such as:
Where are manual process steps located? Which applications are involved in a process? Which interfaces are required? Where could an agent provide meaningful support? Which dependencies and risks exist?
SAP therefore describes Business Transformation Management as an important contribution to the foundation of the Autonomous Enterprise and the SAP Business AI Platform.
What Does Agentic AI Mean Within the SAP Business AI Platform?
Agentic AI refers to AI systems that do not merely generate content or answer an individual question, but can pursue tasks and coordinate actions within defined boundaries.
For example, an AI agent could:
check a process status, retrieve information from SAP S/4HANA, enrich it with data from a third-party system, consider a corporate policy, generate a recommended action and then trigger an approved workflow.
The key point is controlled action.
Organisations need to define which actions an agent may execute independently and when a human must make or approve a decision.
SAP’s current Autonomous Enterprise strategy is designed around precisely this interaction between humans, assistants and agents. The SAP Business AI Platform provides the foundation for developing, contextualising and governing these AI systems.
What Roles Do Joule and Joule Studio Play?
Joule remains the central AI access point within SAP’s strategy, while Joule Studio is increasingly focused on developing custom agents, applications and workflows.
SAP describes Joule Studio as an AI-first development environment. Developers should be able to use it to build custom agents, apps and workflows based on enterprise data and business context.
In simplified terms:
Joule supports users when working with SAP applications and AI functionality.
Joule Agents perform defined tasks and process steps.
Joule Studio is used to develop and extend custom agents, applications and workflows.
The SAP Business AI Platform provides the shared technical and governance foundation.
SAP Business AI Platform vs. BTP: When Should Companies Use Which Platform?
The question should not be:
SAP Business AI Platform or SAP BTP?
Instead, the focus should be on the objective of the individual initiative.
| Requirement | Primary Focus |
|---|---|
| Integrate SAP and non-SAP systems | SAP BTP / Integration Suite |
| Provide and manage APIs | SAP BTP |
| Develop Clean Core extensions | SAP BTP |
| Develop cloud applications | SAP BTP |
| Automate workflows | SAP BTP / SAP Build |
| Use individual AI services | BTP-related AI services |
| Develop custom AI agents | SAP Business AI Platform |
| Connect AI with business context | SAP Business AI Platform |
| Unify SAP and non-SAP data for AI | SAP Business AI Platform / SAP BDC |
| Govern agents across the enterprise | SAP Business AI Platform |
| Establish AI Governance | SAP Business AI Platform |
| Scale Agentic AI across business units | SAP Business AI Platform |
In practice, many projects will combine both perspectives.
Practical Example: AI-Supported Processing of a Supplier Enquiry
A company wants to process supplier enquiries more efficiently.
Today, for example, an enquiry arrives via a portal or email. Employees then need to search for information across different systems, check supplier data and determine the appropriate next action.
Tasks Performed by SAP BTP
SAP BTP can provide the technical foundation in this scenario.
The communication channel can be integrated, SAP S/4HANA connected, the required APIs made available, a workflow modelled and user and authorisation checks implemented.
Extension Through the SAP Business AI Platform
The SAP Business AI Platform adds the AI layer to the scenario.
An agent could interpret the supplier enquiry, place relevant supplier and procurement information into context, consider corporate policies and propose an appropriate action.
A defined workflow could then be triggered. Depending on the risk and process rules, either an automated action or a human-in-the-loop approval would follow.
This example illustrates SAP Business AI Platform vs. BTP particularly well:
SAP BTP connects and automates the technical process components.
The SAP Business AI Platform adds Business Context, Reasoning, agents and AI Governance.
What Changes for Existing SAP BTP Customers?
At first, considerably less than the new platform name might suggest.
Existing organisations do not need to replace their SAP BTP landscape solely because of the introduction of the SAP Business AI Platform.
Existing integrations, SAP Build applications, process automations, extensions and platform services remain relevant.
What changes is the strategic planning.
Organisations should extend their existing BTP roadmap with additional questions:
Which processes are suitable for AI agents? Which enterprise data do these agents need? How can consistent Business Context be created? Which actions may agents execute autonomously? Where are human approvals required? How are agents, models and permissions monitored?
The existing SAP BTP strategy therefore does not become obsolete.
On the contrary: A well-designed BTP architecture for integration, APIs, extensions and governance can be an important prerequisite for using the SAP Business AI Platform in a controlled manner in the future.
Benefits of the SAP Business AI Platform BTP Architecture
The main benefit results from combining established platform capabilities with a broader AI architecture.
Reuse of Existing SAP BTP Investments
Organisations do not need to rebuild existing integrations and extensions from scratch.
Better Business Context for AI
AI can be aligned more closely with processes, data models, relationships and corporate policies.
Governed Agentic AI
Agents are not operated in isolation, but embedded within an architecture for security, lifecycle management and governance.
SAP and Non-SAP Integration
Integration Suite and Business Data Cloud can also incorporate systems and data outside the SAP environment.
Scalability
Consistent platform, data and governance principles make it easier to move from isolated AI pilots to multiple productive use cases.
What Challenges Arise?
The SAP Business AI Platform does not automatically solve existing data, process or architecture problems.
Poor master data, missing process standards or unclear responsibilities can become particularly problematic for Agentic AI.
An AI agent that accesses contradictory information cannot become reliable simply by using a more capable language model.
Additional challenges include integrating heterogeneous system landscapes, identity and authorisation concepts, data protection, cost management and determining which tasks should be automated at all.
Another common mistake is starting with an AI tool before the business process has been clarified.
The central question should therefore not be:
“Which agent can we build?”
Instead:
“Which specific process problem should the SAP Business AI Platform solve, and what prerequisites does this process require?”
Best Practices for SAP Business AI Platform vs. BTP
Process Before Technology
Start with a specific business problem rather than an AI model.
Inventory the Existing BTP Landscape
Document integrations, SAP Build solutions, APIs, extensions and existing AI services.
Consider Data Context Early
Evaluate not only data availability, but also data quality, semantics and relationships between business objects.
Clearly Limit Agent Permissions
Define at an early stage which actions may be executed autonomously and when human approval is required.
Treat Integration as a Prerequisite
Agents can only act across systems if the relevant systems are connected in a controlled manner.
Establish Governance Before Scaling
A successful pilot should not immediately be rolled out across additional departments without control. Roles, monitoring and lifecycle processes must scale with the solution.
Do’s & Don’ts When Implementing the Platform
Do
Continue using existing SAP BTP capabilities, develop a clear target architecture for data and integration, and select a measurable AI use case. Involve business departments, IT, security and data protection teams early and define human-in-the-loop rules.
Don’t
Do not treat the SAP Business AI Platform as merely a renamed version of SAP BTP. Do not equate Agentic AI with a traditional chatbot, and do not start with autonomous actions while permissions, data quality and governance remain unclear.
Step by Step to the SAP Business AI Platform
Step 1 – Analyse Business Processes
Identify processes involving high manual effort, numerous exceptions, complex decisions or large volumes of information.
Step 2 – Prioritise Use Cases
Assess business value, feasibility, risk and data availability.
Step 3 – Assess the Existing SAP BTP Architecture
Review Integration Suite, SAP Build, APIs, extensions, runtime environments and existing AI services.
Step 4 – Evaluate Data and Business Context
Analyse relevant SAP and non-SAP data as well as its business semantics.
Step 5 – Define Governance
Establish authorisations, data protection requirements, security requirements, responsibilities and approval limits.
Step 6 – Implement a Pilot
Start with a limited, measurable process and a controlled user group.
Step 7 – Measure Results
Suitable KPIs may include processing time, degree of automation, error rate, number of manual handovers or quality of recommendations.
Step 8 – Scale in a Controlled Manner
Only after successful evaluation should additional agents, processes and business areas be introduced.
SAP Business AI Platform vs. BTP and Clean Core
SAP BTP remains relevant in the context of Clean Core.
Clean Core does not mean that custom functionality can no longer be developed. Instead, the objective is to decouple customer-specific extensions from the ERP core in a controlled way and use standardised interfaces wherever possible.
SAP BTP has supported these side-by-side extensions for many years.
The SAP Business AI Platform now adds another layer: AI agents and AI-supported applications should likewise not be embedded deep within the ERP core in an uncontrolled manner.
APIs, events, Integration Suite and clearly defined business services can serve as controlled connections between agents and core processes.
Clean Core and SAP BTP therefore remain central prerequisites for many future Enterprise AI scenarios.
Conclusion – SAP Business AI Platform vs. SAP BTP Is Not an Either-Or Decision
The most important conclusion is: SAP Business AI Platform and SAP BTP are not competing platforms.
SAP BTP remains the established technology platform for development, integration, extension, automation and central technical platform services.
The SAP Business AI Platform provides the broader Enterprise AI framework. It combines BTP capabilities with SAP Business Data Cloud, business context, SAP Knowledge Graph, AI models, Joule Studio, agents and overarching governance. SAP itself now explicitly describes BTP as the core of this new platform.
Organisations that already have a robust BTP strategy therefore do not need to start again.
Instead, they should extend their architecture across three perspectives:
Build: How do we develop and integrate AI agents, applications and workflows?
Contextualize and Reason: Which data, relationships and business rules must AI understand?
Govern: How do we control and monitor agents, models, permissions and lifecycles?
The discussion around SAP Business AI Platform vs. BTP is therefore increasingly becoming an architectural question.
SAP BTP continues to provide a large part of the technical foundation.
The SAP Business AI Platform turns this into a broader foundation for Enterprise AI and Agentic AI.
Frequently Asked Questions About the SAP Business AI Platform
What Is the Difference Between SAP Business AI Platform and SAP BTP?
SAP BTP is the technology platform for integration, development, extensions and automation. The SAP Business AI Platform is the broader Enterprise AI framework that combines these capabilities with data context, AI models, agents and governance.
Does the SAP Business AI Platform Replace SAP BTP?
No. SAP BTP remains in place. SAP explicitly describes BTP capabilities as a core component of the SAP Business AI Platform.
How Are SAP Business AI Platform and BTP Connected?
SAP BTP provides development, integration, automation and platform capabilities. The SAP Business AI Platform uses these capabilities and extends them with an overarching Enterprise AI architecture.
Which SAP BTP Functions Are Part of the SAP Business AI Platform?
Particularly relevant are SAP Integration Suite, SAP Build, BTP-based runtime and development capabilities and AI-related services. SAP now groups these capabilities as the core of the new platform.
What Additional Functions Does SAP Business AI Platform Offer Compared with SAP BTP?
Key additions include a more unified business context, SAP Business Data Cloud, SAP Knowledge Graph, agent-based development through Joule Studio and expanded governance and lifecycle functionality.
When Should Companies Use SAP Business AI Platform and When SAP BTP?
For classic integration, application development, extensions and workflow automation, SAP BTP remains the direct technical platform. If organisations want to connect AI agents with enterprise data and processes across the organisation and scale them in a controlled way, the SAP Business AI Platform should be viewed as the overarching target architecture.
What Role Does SAP BTP Play Within the SAP Business AI Platform?
SAP BTP provides core technical capabilities through which agents and AI applications can be developed, integrated and operated. It is therefore not a parallel platform, but an essential technical core.
What Changes for Existing SAP BTP Customers?
Existing BTP applications and integrations do not need to be replaced solely because of the SAP Business AI Platform. However, organisations should extend their BTP roadmap to include data context, AI Governance, Agentic AI and new AI development tools.
Would You Like to Assess Your SAP BTP and Business AI Strategy?
The introduction of the SAP Business AI Platform does not mean that existing platform strategies need to be discarded. Instead, SAP BTP, data, integration, business processes and AI should increasingly be viewed as a connected architecture.
Fink IT-Solutions supports you in analysing existing SAP BTP landscapes, identifying suitable AI use cases and establishing the technical foundations for Business AI and Agentic AI.
Key questions include:
Which BTP services are already in use? Which systems and data need to be integrated? Which business processes are suitable for AI agents? How can security, governance and Clean Core be combined? And how can an initial pilot project evolve into a scalable Enterprise AI architecture?