### AI@FRE Blog Series:
AI@FRE (Part 1) – Enabling Enterprise AI Adoption through the BTP FRE Engagement Model
AI@FRE (Part 2) – Accelerating Business AI Transformation with the FRE Value Framework
AI@FRE (Part 3) – Guardrails for Enterprise AI Adoption
AI@FRE (PART 4) – Guardrail Enterprise AI Adoption – AI Architecture Guardrails
###
Scaling enterprise AI is no longer optional; it’s essential for organizations looking to remain competitive. However, achieving this requires robust architecture and tool standardization to enable scalable, secure, and efficient AI deployment. Standardizing key areas in an organization, from security to automation, digital experiences, core, data, and AI architecture, sets a strong foundation for streamlined processes, enhanced agility, and a simplified landscape.
The Importance of Standardizing Architecture and Tools for AI at Scale
Building a scalable AI infrastructure hinges on standardizing architecture and tools, which enables enterprises to measure key outcomes like:
Business Agility & Flexibility: Achieve XX-month reduction in time-to-market for new AI initiatives. Execution Speed: Drive XX-day reduction in project execution. Simplified Landscape: Foster streamlined architecture that minimizes redundancies and supports easy upgrades and scalability.
Each area of standardization brings unique benefits and helps ensure consistent integration across SAP solutions, as we’ll explore below.
Standardize Security Architecture
With AI adoption, ensuring security at every layer of the architecture is critical. A standardized security architecture enables cohesive, scalable, and adaptive access management.
User Access Management (IPS): Enforces access control, minimizing security risks by managing permissions and restricting access to sensitive data. Single Sign-On (IAS): Unifies login experiences across SAP solutions, enabling employees to access tools seamlessly. Automated, Adaptive Access Management: Automates access protocols to ensure compliance, adaptive access control, and lifecycle management. Event-Driven Identity Lifecycle Management: Automates identity management processes in response to organizational events, streamlining updates to user access and permissions.
Business Benefits:
Unified Access: Simplifies security management by centralizing access across SAP environments. Secure Remote Work: Provides reliable access for remote employees without compromising security. Enhanced Employee Experience: Eliminates repetitive logins, allowing employees to focus on tasks. Productivity and Collaboration: Reduces friction in accessing necessary tools, fostering productivity. Digital Transformation: Lays the security groundwork for digital transformation efforts across the organization.
Enabling of single-sign-on and identity provisioning throughout your application landscape
Standardize Enterprise Automation
Automating workflows and processes is essential for scaling AI-driven enterprise operations. Standardized automation supports consistent, efficient, and error-free processes. De Agostini Publishing S.p.A leveraged SAP BTP to automate vendor invoice management, enhancing accuracy, efficiency, and data reliability across new markets. Another example is from Colsubsidio’s SAP BTP implementation, which enables them efficient, independent analytics for strategic, data-driven decision-making.
Automate Visually: Utilize intuitive, drag-and-drop interfaces and AI to simplify automation. Integrate Seamlessly: Speed up development with pre-built workflows, bots, and connectors for both SAP and non-SAP systems. Collaborate Securely: Empower cross-functional teams with secure, agile development tools.
Automation Examples:
Generative AI for Interactive Modeling: Supports modeling through natural language inputs with proactive validation. Document Information Extraction: Automates data capture from structured documents like invoices. Action Process AI (SAP Signavio): Combines large process models with SAP expertise to improve accuracy and effectiveness.
Key Benefits:
Reduced manual effort and error rates. Increased speed and quality of automation. Empowered cross-functional teams with collaboration capabilities.
Process AI at SAP Signavio
Standardize Digital Experience Architecture for Conversational Experience
To create a seamless digital experience, the architecture must support modularity and scalability, allowing for a unified user interface across devices and applications.
Conversational UX: Enable conversational interfaces across desktop and mobile, enhancing the user experience with intuitive, end-to-end interactions. SAP Start for Cloud Solutions: A modular homepage offers a single point of entry with pre-configured access to cloud solutions like SAP SuccessFactors and S/4HANA Cloud. Joule in SAP Applications: SAP’s digital assistant, Joule, is embedded in applications to enhance user experience, starting with SAP Start and SAP SuccessFactors.
AI-powered Talent Intelligence:
Talent Optimization: Use AI to generate job descriptions and interview questions tailored to organizational needs, streamlining HR processes. Skills-Based Matching: Empower skills-based organizations with talent intelligence to identify and promote internal talent efficiently.
Standardize UX Architecture – The SAP UX Story
Standardize Core – Building a Lean Core
A lean core structure is essential to keep AI-enabled systems agile and cloud-compliant, enhancing scalability and reducing potential disruptions.
Avoid Custom Extensions: Minimize customizations to ensure compatibility with SAP’s upgrade cycles. Separate Extensions with APIs: Ensure extensions do not interfere with upgrades by leveraging APIs. Cloud-Compliant Extensions: Develop with cloud compatibility in mind, aligning with a three-tier architectural model.
Business Impact:
Smooth upgrades, minimal disruptions. Scalable, cloud-ready architecture. Enhanced reliability in deployments.
Standardize Data Architecture
Data architecture standardization is vital for ensuring seamless data sharing, comprehensive analytics, and powerful AI model training across the enterprise.
Business Data Fabric: An architecture that delivers contextually rich data to every user, preserving business context and logic. Intelligent Data Applications: Enable developers to create apps that are AI-driven, context-aware, and seamlessly connected to core business data. Extended Planning and Analysis: Unify planning functions for finance, HR, and operations within a single, data-rich ecosystem. Data Sharing & Products: Facilitate data-sharing with data products that provide both abstraction and usability layers without introducing new artifacts.
Example Use Case:
Business Decision Simulator: Simulate complex scenarios to predict potential disruptions and make data-informed adjustments.
Core Benefits:
Holistic data access across departments. Stronger alignment between operational and strategic planning. Enhanced data-driven decision-making.
Standardize AI Architecture
The AI architecture must support diverse AI capabilities, from natural language processing to generative AI, ensuring seamless integration and adaptability across SAP applications.
Joule in All Apps: SAP’s digital assistant Joule, embedded in SAP applications, offers users insights and support while automating routine tasks. It allows users to directly access services like SAP SuccessFactors and S/4HANA Cloud. Generative AI Hub in SAP AI Core: The GenAI Hub provides a central location for generative AI models, enabling SAP applications to draw upon AI capabilities like text generation, summarization, and process modeling in real time. SAP-Hosted Foundation Models: By hosting foundational AI models, SAP AI Core offers scalability and reliability, reducing dependency on external AI solutions and ensuring secure data handling.
Benefits:
Scalability: Supports consistent deployment across all SAP applications, reducing the need for fragmented, custom AI solutions. Data Security: Centralizes model hosting within SAP’s secure environment. Enhanced Process Intelligence: Infuses advanced process and data understanding across SAP systems, allowing companies to optimize AI-driven workflows effectively.
Conclusion
Standardizing architecture and tools across these six key areas creates a solid foundation for scalable, secure, and efficient AI adoption in enterprise settings. This standardization empowers organizations to move faster, adapt more readily to changes, and achieve a simplified and agile landscape that supports continued innovation and growth.
Curious on a structured customer engagement model to set up standardized Cloud Architecture for Business AI Adoption? Connect with our Global BTP Customer Engagement Team at BTPFRE@sap.com.
### AI@FRE Blog Series:AI@FRE (Part 1) – Enabling Enterprise AI Adoption through the BTP FRE Engagement ModelAI@FRE (Part 2) – Accelerating Business AI Transformation with the FRE Value FrameworkAI@FRE (Part 3) – Guardrails for Enterprise AI AdoptionAI@FRE (PART 4) – Guardrail Enterprise AI Adoption – AI Architecture Guardrails ###Scaling enterprise AI is no longer optional; it’s essential for organizations looking to remain competitive. However, achieving this requires robust architecture and tool standardization to enable scalable, secure, and efficient AI deployment. Standardizing key areas in an organization, from security to automation, digital experiences, core, data, and AI architecture, sets a strong foundation for streamlined processes, enhanced agility, and a simplified landscape. The Importance of Standardizing Architecture and Tools for AI at Scale Building a scalable AI infrastructure hinges on standardizing architecture and tools, which enables enterprises to measure key outcomes like: Business Agility & Flexibility: Achieve XX-month reduction in time-to-market for new AI initiatives. Execution Speed: Drive XX-day reduction in project execution. Simplified Landscape: Foster streamlined architecture that minimizes redundancies and supports easy upgrades and scalability. Each area of standardization brings unique benefits and helps ensure consistent integration across SAP solutions, as we’ll explore below. Standardize Security Architecture With AI adoption, ensuring security at every layer of the architecture is critical. A standardized security architecture enables cohesive, scalable, and adaptive access management. User Access Management (IPS): Enforces access control, minimizing security risks by managing permissions and restricting access to sensitive data. Single Sign-On (IAS): Unifies login experiences across SAP solutions, enabling employees to access tools seamlessly. Automated, Adaptive Access Management: Automates access protocols to ensure compliance, adaptive access control, and lifecycle management. Event-Driven Identity Lifecycle Management: Automates identity management processes in response to organizational events, streamlining updates to user access and permissions. Business Benefits: Unified Access: Simplifies security management by centralizing access across SAP environments. Secure Remote Work: Provides reliable access for remote employees without compromising security. Enhanced Employee Experience: Eliminates repetitive logins, allowing employees to focus on tasks. Productivity and Collaboration: Reduces friction in accessing necessary tools, fostering productivity. Digital Transformation: Lays the security groundwork for digital transformation efforts across the organization. Enabling of single-sign-on and identity provisioning throughout your application landscape Standardize Enterprise Automation Automating workflows and processes is essential for scaling AI-driven enterprise operations. Standardized automation supports consistent, efficient, and error-free processes. De Agostini Publishing S.p.A leveraged SAP BTP to automate vendor invoice management, enhancing accuracy, efficiency, and data reliability across new markets. Another example is from Colsubsidio’s SAP BTP implementation, which enables them efficient, independent analytics for strategic, data-driven decision-making. Automate Visually: Utilize intuitive, drag-and-drop interfaces and AI to simplify automation. Integrate Seamlessly: Speed up development with pre-built workflows, bots, and connectors for both SAP and non-SAP systems. Collaborate Securely: Empower cross-functional teams with secure, agile development tools. Automation Examples: Generative AI for Interactive Modeling: Supports modeling through natural language inputs with proactive validation. Document Information Extraction: Automates data capture from structured documents like invoices. Action Process AI (SAP Signavio): Combines large process models with SAP expertise to improve accuracy and effectiveness. Key Benefits: Reduced manual effort and error rates. Increased speed and quality of automation. Empowered cross-functional teams with collaboration capabilities. Process AI at SAP Signavio Standardize Digital Experience Architecture for Conversational Experience To create a seamless digital experience, the architecture must support modularity and scalability, allowing for a unified user interface across devices and applications. Conversational UX: Enable conversational interfaces across desktop and mobile, enhancing the user experience with intuitive, end-to-end interactions. SAP Start for Cloud Solutions: A modular homepage offers a single point of entry with pre-configured access to cloud solutions like SAP SuccessFactors and S/4HANA Cloud. Joule in SAP Applications: SAP’s digital assistant, Joule, is embedded in applications to enhance user experience, starting with SAP Start and SAP SuccessFactors. AI-powered Talent Intelligence: Talent Optimization: Use AI to generate job descriptions and interview questions tailored to organizational needs, streamlining HR processes. Skills-Based Matching: Empower skills-based organizations with talent intelligence to identify and promote internal talent efficiently. Standardize UX Architecture – The SAP UX Story Standardize Core – Building a Lean Core A lean core structure is essential to keep AI-enabled systems agile and cloud-compliant, enhancing scalability and reducing potential disruptions. Avoid Custom Extensions: Minimize customizations to ensure compatibility with SAP’s upgrade cycles. Separate Extensions with APIs: Ensure extensions do not interfere with upgrades by leveraging APIs. Cloud-Compliant Extensions: Develop with cloud compatibility in mind, aligning with a three-tier architectural model. Business Impact: Smooth upgrades, minimal disruptions. Scalable, cloud-ready architecture. Enhanced reliability in deployments. Standardize Data Architecture Data architecture standardization is vital for ensuring seamless data sharing, comprehensive analytics, and powerful AI model training across the enterprise. Business Data Fabric: An architecture that delivers contextually rich data to every user, preserving business context and logic. Intelligent Data Applications: Enable developers to create apps that are AI-driven, context-aware, and seamlessly connected to core business data. Extended Planning and Analysis: Unify planning functions for finance, HR, and operations within a single, data-rich ecosystem. Data Sharing & Products: Facilitate data-sharing with data products that provide both abstraction and usability layers without introducing new artifacts. Example Use Case: Business Decision Simulator: Simulate complex scenarios to predict potential disruptions and make data-informed adjustments. Core Benefits: Holistic data access across departments. Stronger alignment between operational and strategic planning. Enhanced data-driven decision-making. Standardize AI Architecture The AI architecture must support diverse AI capabilities, from natural language processing to generative AI, ensuring seamless integration and adaptability across SAP applications. Joule in All Apps: SAP’s digital assistant Joule, embedded in SAP applications, offers users insights and support while automating routine tasks. It allows users to directly access services like SAP SuccessFactors and S/4HANA Cloud. Generative AI Hub in SAP AI Core: The GenAI Hub provides a central location for generative AI models, enabling SAP applications to draw upon AI capabilities like text generation, summarization, and process modeling in real time. SAP-Hosted Foundation Models: By hosting foundational AI models, SAP AI Core offers scalability and reliability, reducing dependency on external AI solutions and ensuring secure data handling. Benefits: Scalability: Supports consistent deployment across all SAP applications, reducing the need for fragmented, custom AI solutions. Data Security: Centralizes model hosting within SAP’s secure environment. Enhanced Process Intelligence: Infuses advanced process and data understanding across SAP systems, allowing companies to optimize AI-driven workflows effectively. Conclusion Standardizing architecture and tools across these six key areas creates a solid foundation for scalable, secure, and efficient AI adoption in enterprise settings. This standardization empowers organizations to move faster, adapt more readily to changes, and achieve a simplified and agile landscape that supports continued innovation and growth. Curious on a structured customer engagement model to set up standardized Cloud Architecture for Business AI Adoption? Connect with our Global BTP Customer Engagement Team at BTPFRE@sap.com. Read More Technology Blogs by SAP articles
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