At TechEd 2025, SAP showed how AI is becoming part of everyday enterprise software development. The company is weaving AI tools into its platforms to help developers work faster, make better use of data, and connect what they build more closely to business goals.
SAP’s latest updates focus on giving developers more flexibility in how they build, automate, and scale AI-driven development. The SAP Build platform now works with tools that many teams already use, like Visual Studio Code. New Model Context Protocol Servers let developers connect to SAP frameworks from inside their preferred coding environments, rather than switching between systems. The updates make AI integration smoother and more consistent in enterprise development pipelines.
The company also introduced Joule Studio, which lets developers build and customise “agents” – small AI-powered programmes that act on SAP business data. The agents can track changes, flag issues, or trigger workflows automatically. For instance, a sales team could design an agent that predicts order delays and sends alerts before problems escalate.
“SAP’s announcements today give developers the tools they need to deliver at the speed of AI,” said Muhammad Alam, member of the Executive Board of SAP SE. “Innovations in SAP’s unique flywheel of applications, data and AI put developers in the drivers’ seat – where they belong.”
This kind of AI-supported development is gaining traction in enterprise technology. Vendors from Microsoft to IBM are exploring ways for AI to act more independently in business systems. For enterprises, the appeal lies in reducing manual work while improving collaboration between data, development, and decision-making.
Turning data into a strategic asset
The success of AI in enterprise development depends on the quality and accessibility of data. SAP is expanding its Business Data Cloud so developers can connect directly to platforms like Snowflake, Databricks, and Google Cloud. The integrations help enterprises share, analyse, and govern data more efficiently while maintaining business context.
A new Data Product Studio lets teams turn raw information into reusable “data products” that can feed analytics, AI models, or new business apps. Meanwhile, updates to SAP HANA Cloud’s knowledge graph automatically map relationships between different data sources. This helps developers and analysts understand how datasets interact and where insights can be found – an essential part of effective AI-driven development.
For a manufacturer or logistics company, these improvements could streamline how AI models are trained to predict delays, improve supply chain visibility, and optimise operations.
From AI insight to business action
SAP also unveiled SAP-RPT-1, a new AI model designed for enterprise prediction. Unlike large language models that generate text, SAP-RPT-1 analyses structured business data to forecast outcomes like payment risk or delivery delays. Developers can experiment with it in a sandbox environment before deploying it in live development projects.
New Joule AI assistants can manage multiple agents in departments, linking finance, HR, and operations workflows. Assistants move AI from insight to execution – identifying inefficiencies, recommending process improvements, and coordinating repetitive tasks in teams.
SAP’s broader direction is clear: integrate AI directly into enterprise systems and development workflows rather than treat it as a separate layer. For CIOs, this signals a shift toward embedding intelligence in the data and applications that already power the business.
Investing in AI-ready talent
Technology adoption depends on people, not just platforms. SAP has pledged to train 12 million people in AI and development skills by 2030 through its expanded partnership with Coursera. The training includes hands-on courses that teach how to use AI tools, manage data pipelines, and build automation safely.
The commitment reflects a growing need for AI-ready professionals who understand both software development and data ethics. Developers, analysts, and business users will need shared knowledge to apply AI responsibly in enterprise contexts.
SAP’s TechEd 2025 updates show how enterprise software development is becoming more intelligent, connected, and data-driven. For business leaders, the takeaway is clear: success with AI will depend on aligning smart tools, trusted data, and skilled people in every stage of development.
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