BAIP and SAP’s AI strategy
Recently, there has been a flurry of LinkedIn content discussing the evolution of SAP BTP (Business Technology Platform) into SAP BAIP (Business AI Platform).
As such, we thought it would be worthwhile to take a deeper dive into what SAP BAIP is and what it means for AI within the SAP ecosystem.
Is BTP Being Phased Out, Rebranded or Renamed?
The short answer is no.
Despite some of the more prominent commentary on LinkedIn, SAP BAIP is neither a rebranding nor a renaming of SAP BTP. Likewise, there is no indication that BTP is being phased out. In fact, it is likely to become even more important, as we will explore throughout the rest of this article.
As SAP made clear during its Sapphire 2026 announcement, BAIP will serve as SAP’s unified platform for building, running and governing AI across the enterprise.
BAIP will bring together and consolidate the following capabilities within a single architectural framework:
- SAP Business Technology Platform (BTP)
- SAP Business Data Cloud (BDC)
- SAP AI Foundation
In other words, BTP remains a core component of SAP’s technology strategy and will form a foundational element within the broader SAP BAIP architecture.
BAIP’s Three-Layer Architecture
A key feature of BAIP is its three-layer architecture, comprising the following components:
- Context Layer
This layer will largely be invisible to end users and will include capabilities such as Generative AI Hub, which provides access to external AI models, alongside SAP’s purpose-built models, SAP Business Data Cloud and the SAP Knowledge Graph.
The Context Layer will play a critical role in ensuring that AI agents understand the unique business processes, data and operating context of a specific organisation.
- Build Layer
The Build Layer will be centred around Joule Studio 2.0 and will be the environment in which agents, applications and workflows are created.
Its primary focus will be intent-based development, enabling users to describe a desired business outcome in natural language and allowing Joule Studio to generate the required solution. SAP will continue to support both low-code and pro-code development approaches, ensuring flexibility for a broad range of users and development teams.
The Build Layer will also leverage both SAP’s pre-built agents and customer-specific custom agents. This will include support for Agent-to-Agent communication protocols and Model Context Protocols (MCPs), helping to ensure that AI agents are not isolated solutions but can work collaboratively across systems and processes.
- Governance Layer
The Governance Layer will enable organisations to monitor, audit and control AI agents operating across their SAP landscape through the SAP AI Agent Hub.
This includes the ability to define and enforce controls relating to data access, system permissions and agent behaviour.
SAP envisages that this layer will help enterprises address one of the most significant barriers to AI adoption: establishing effective governance and oversight of AI tools and agents at scale.
Why Has SAP Introduced BAIP?
SAP is seeking to address several key challenges organisations face as they look to deploy AI tools and agents across their businesses, including:
- Disconnected AI tools and agents that cannot effectively communicate or collaborate with one another.
- Governance concerns, including controlling which data and systems individual agents can access.
- AI solutions that lack sufficient business-specific context to deliver meaningful outcomes.
By creating a unified platform that integrates AI capabilities across the enterprise, SAP is positioning AI at the heart of its future strategy, rather than treating it as an additional feature layered on top of existing technologies.
Ultimately, SAP BAIP represents an evolution of SAP’s platform strategy, bringing together data, application development, AI capabilities and governance into a single framework designed to support enterprise-wide AI adoption at scale.
What Does This Mean for Businesses?
Ultimately, SAP’s move towards BAIP should reinforce, rather than fundamentally alter, the transformation journeys that many businesses are already undertaking.
For example, the emphasis on maintaining a clean core becomes even more important in a BAIP-driven future. The Context Layer will depend heavily on standardised processes, well-structured data, and consistent system design. Organisations with extensive customisation may find it more difficult to realise the full value of future AI capabilities.
Similarly, many organisations are already embracing low-code development approaches where appropriate. The shift towards intent-based development is a natural extension of this trend and is likely to accelerate the adoption of business-led innovation.
Governance remains another critical consideration. Many businesses have already established, or are developing, frameworks to govern the use of AI technologies. BAIP’s Governance Layer provides an opportunity to embed these controls directly within the SAP environment, delivering greater visibility, accountability, and control over how AI solutions access data and interact with enterprise systems.
Conclusion
Rather than signalling the end of BTP, SAP BAIP represents an expansion of SAP’s AI strategy. By bringing together BTP, BDC, and AI Foundation capabilities under a unified framework, SAP is creating a platform designed to support scalable, context-aware, and well-governed AI across the enterprise.
For SAP customers, the key priorities remain largely unchanged: maintain a clean core, establish robust governance practices, and continue investing in modern development approaches. Organisations that are already progressing in these areas will be best positioned to take advantage of the opportunities that BAIP is intended to unlock.