J
Jon Stojan Journalist
Guest
AI is making a strong transition from a technology of the future to a key element of enterprise technology strategy. With the increasing adoption of AI in various parts of the ERP system, cloud platforms, data environments, and business applications, enterprise architecture is playing a pivotal role in how these technologies can operate in a scalable, secure and sustainable way. However, for technology architect Trupti Raikar, the discussion on AI in enterprise architecture isn't just about the adoption of new AI capabilities, it's about finding the right way to fit it into existing technology infrastructure without sacrificing the core principles of the organisation's tech stack.
Raikar has been involved in SAP projects and enterprise technology for ~ 19 years, with deep expertise in AI/ML, SAP S/4HANA, Cloud transformations, SAP Business Technology Platform, Cloud platform integration and performance engineering & Enterprise Architecture. Her career has included experience on large-scale global technology programmes and linking technical architecture to business requirements. She also has a track record of having worked for organisations such as Apple, Rockwell Automation, QuidelOrtho, Lionsgate, Bio-Rad and infineum.
As AI is added to enterprise systems, architecture is becoming an additional challenge for organisations. For AI models to become a reality, they need high-quality data, integration methods, computational power, governance and user-facing applications. Meanwhile, enterprises have to account for the fact that AI-driven complexity does not add to the current enterprise complexity, and that the technology for AI must not be complicated or complex enough to break current enterprise systems.
This is especially true in ERP systems where stability, security, and auditability and scalability matter. Raikar has addressed this challenge in two of her work areas: clean-core architecture and integration of AI. Her research about clean core principles in SAP systems focuses on finding ways to implement the AI functionality in suitable architectures while keeping a reasonable amount of customisation outside the core of the ERP system.
There are also governance questions with the use of AI. Predictive accuracy is not the only metric an enterprise can use in assessing an AI solution. Explainability, data privacy, security, governance,latency, scalability, cost, data residency and lifecycle management are among the factors that could impact an enterprise's suitability for an AI capability.
This architectural equilibrium has been a special focus of Raikar's recent projects. She served as a keynote speaker at IEEE AIC 2026, where she spoke about maintaining principles of clean-core and adopting a common reference architecture for intelligent ERP. In her presentation she spoke about how AI, data and governance can complement ERP systems to sustain a digital core, and integration of enterprise systems.
The topic of her talk illustrates a larger trend in enterprise tech—AI implementation should not be just a software-development project. Organisations must have the ability to integrate, monitor and evaluate AI models as well as have a robust structure to remove AI models from their systems without impacting critical business functions.
Raikar's skill has been nurtured over multiple generations of enterprise technology. She has expertise in SAP S/4HANA, SAP BTP, ABAP, RAP, CAP, SAP HANA, Fiori/UI5, Cloud integration technologies, cloud-native development. She has also led and contributed to multiple large-scale global technology and business transformation initiatives for major enterprises in fortune 500 enterprises including SAP, Apple, QuidelOrtho, Infineum and others spanning SAP modernization, enterprise architecture, cloud transformation, application integration, and workforce enablement. Additionally, her public speaker profile lists her interest areas as being AI-augmented SAP applications, event-driven architecture and business process automation.
Her strengths in enterprise application and emerging technology skills enable her to put her work in the context of a wider transformation taking place in large organisations. AI is no longer being thought of as an isolated layer of innovation in business usage. Rather, AI is now more reliant than ever upon integration with current applications, data stores, workflows and business processes.
This is expressed through Raikar's professional and research activities. Her past research publications have focused on the in-memory database architecture of SAP S/4HANA and the impact of architectural design on performance and scalability. She's also authored various articles on how to deploy AI into SAP without compromising the SAP clean-core concept.
This is reflected in her recent professional activities. Outside of her IEEE AIC 2026 keynote, she has been invited to speak at various other platforms like NDTV, International Conference on Applied Science, Engineering & Technology , NAF Technology Summit, , Infosys TecCohere Tech Narrator Series Edition 11, National Institute of Technology Puducherry the Nexus Industrial Summit 2026 on AI, enterprise technology and intelligent automation, as well as joined relevant discussions on optimising supply chains with AI and responsible technology adoption. Her scholarly contributions include serving as an Editor of Convergence of Information Technology: AI, Data, Cloud, Cybersecurity, Software, and Emerging Digital Systems, Volume 6 (2026), published under the IIP Series by Iterative International Publishers (IIP).
This changing need is reflected in Trupti Raikar's work.This journey into SAP transformation, enterprise architecture, cloud and AI integration provides a distinctive perspective through innovation and enterprise scale. Her clean-core focus also emphasizes the need to avoid "technical debt" when developing AI systems.
AI, Data, Apps and Governance will thus continue to be closely interwoven in the future of enterprise architecture. In organizations getting ready for that future, the goal won't be just to implement AI, but to build an architecture that can foster intelligent technologies in a responsible and scalable way. As the digital landscape evolves, Trupti Raikar's work in her field, research, and industry interactions is playing its part in this ever-changing dialogue on building tech foundations that are flexible in an AI-dominated world.
This story was distributed as a release by Jon Stojan under HackerNoon’s Business Blogging Program.
Raikar has been involved in SAP projects and enterprise technology for ~ 19 years, with deep expertise in AI/ML, SAP S/4HANA, Cloud transformations, SAP Business Technology Platform, Cloud platform integration and performance engineering & Enterprise Architecture. Her career has included experience on large-scale global technology programmes and linking technical architecture to business requirements. She also has a track record of having worked for organisations such as Apple, Rockwell Automation, QuidelOrtho, Lionsgate, Bio-Rad and infineum.
Enterprise architecture conversation is changing with the help of AI
As AI is added to enterprise systems, architecture is becoming an additional challenge for organisations. For AI models to become a reality, they need high-quality data, integration methods, computational power, governance and user-facing applications. Meanwhile, enterprises have to account for the fact that AI-driven complexity does not add to the current enterprise complexity, and that the technology for AI must not be complicated or complex enough to break current enterprise systems.
This is especially true in ERP systems where stability, security, and auditability and scalability matter. Raikar has addressed this challenge in two of her work areas: clean-core architecture and integration of AI. Her research about clean core principles in SAP systems focuses on finding ways to implement the AI functionality in suitable architectures while keeping a reasonable amount of customisation outside the core of the ERP system.
Build Intelligent Systems, without losing control
There are also governance questions with the use of AI. Predictive accuracy is not the only metric an enterprise can use in assessing an AI solution. Explainability, data privacy, security, governance,latency, scalability, cost, data residency and lifecycle management are among the factors that could impact an enterprise's suitability for an AI capability.
This architectural equilibrium has been a special focus of Raikar's recent projects. She served as a keynote speaker at IEEE AIC 2026, where she spoke about maintaining principles of clean-core and adopting a common reference architecture for intelligent ERP. In her presentation she spoke about how AI, data and governance can complement ERP systems to sustain a digital core, and integration of enterprise systems.
The topic of her talk illustrates a larger trend in enterprise tech—AI implementation should not be just a software-development project. Organisations must have the ability to integrate, monitor and evaluate AI models as well as have a robust structure to remove AI models from their systems without impacting critical business functions.
From SAP Transformation to AI-Enabled Architecture
Raikar's skill has been nurtured over multiple generations of enterprise technology. She has expertise in SAP S/4HANA, SAP BTP, ABAP, RAP, CAP, SAP HANA, Fiori/UI5, Cloud integration technologies, cloud-native development. She has also led and contributed to multiple large-scale global technology and business transformation initiatives for major enterprises in fortune 500 enterprises including SAP, Apple, QuidelOrtho, Infineum and others spanning SAP modernization, enterprise architecture, cloud transformation, application integration, and workforce enablement. Additionally, her public speaker profile lists her interest areas as being AI-augmented SAP applications, event-driven architecture and business process automation.
Her strengths in enterprise application and emerging technology skills enable her to put her work in the context of a wider transformation taking place in large organisations. AI is no longer being thought of as an isolated layer of innovation in business usage. Rather, AI is now more reliant than ever upon integration with current applications, data stores, workflows and business processes.
This is expressed through Raikar's professional and research activities. Her past research publications have focused on the in-memory database architecture of SAP S/4HANA and the impact of architectural design on performance and scalability. She's also authored various articles on how to deploy AI into SAP without compromising the SAP clean-core concept.
This is reflected in her recent professional activities. Outside of her IEEE AIC 2026 keynote, she has been invited to speak at various other platforms like NDTV, International Conference on Applied Science, Engineering & Technology , NAF Technology Summit, , Infosys TecCohere Tech Narrator Series Edition 11, National Institute of Technology Puducherry the Nexus Industrial Summit 2026 on AI, enterprise technology and intelligent automation, as well as joined relevant discussions on optimising supply chains with AI and responsible technology adoption. Her scholarly contributions include serving as an Editor of Convergence of Information Technology: AI, Data, Cloud, Cybersecurity, Software, and Emerging Digital Systems, Volume 6 (2026), published under the IIP Series by Iterative International Publishers (IIP).
Training businesses for the age of AI
This changing need is reflected in Trupti Raikar's work.This journey into SAP transformation, enterprise architecture, cloud and AI integration provides a distinctive perspective through innovation and enterprise scale. Her clean-core focus also emphasizes the need to avoid "technical debt" when developing AI systems.
AI, Data, Apps and Governance will thus continue to be closely interwoven in the future of enterprise architecture. In organizations getting ready for that future, the goal won't be just to implement AI, but to build an architecture that can foster intelligent technologies in a responsible and scalable way. As the digital landscape evolves, Trupti Raikar's work in her field, research, and industry interactions is playing its part in this ever-changing dialogue on building tech foundations that are flexible in an AI-dominated world.
This story was distributed as a release by Jon Stojan under HackerNoon’s Business Blogging Program.