☑️ ISO/IEC 22989:2022
Information technology - Artificial intelligence - Artificial intelligence concepts and terminology
☑️ ISO/IEC 23053:2022
Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML)
☑️ ISO/IEC 23894:2023
Information technology - Artificial intelligence - Guidance on risk management
☑️ ISO/IEC TR 24028:2020
Information technology - Artificial intelligence - Overview of trustworthiness in artificial intelligence
☑️ ISO/IEC 42001:2023
Information Technology - Artificial Intelligence - Management System (AIMS)
☑️ ISO/IEC AWI 42003
Information technology - Artificial intelligence - Guidance on the implementation of ISO/IEC 42001
☑️ ISO/IEC 42005:2025
Information technology - Artificial intelligence (AI) - AI system impact assessment
☑️ ISO/IEC 42006:2025
Information technology - Artificial intelligence - Requirements for bodies providing audit and certification of artificial intelligence management systems
☑️ ISO/IEC AWI 42007
Information technology - Artificial intelligence - High-level framework and guidance for the development of conformity assessment schemes for AI systems
☑️ NIST AI Risk Management Framework (AI RMF)
(Rev 1.0 - 2023)
☑️ NIST SP 800-53
Security and Privacy Controls for Information Systems and Organizations (Rev 5.1.1 - Nov 7, 2023)
☑️ EU AI Act
The AI Act is a European regulation on artificial intelligence (AI)
(July 2024)
☑️ General Data Protection Regulation (EU GDPR)
Europe’s data privacy and security law includes hundreds of pages’ worth of new requirements for organizations around the world
(May 2018)
☑️ ENISA AI Cybersecurity Guidelines
☑️ High-Level Expert Group on AI (HLEG) Ethics Guidelines
⬇️ Technical Part
☑️ MITRE ATLAS™
ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems) is a globally accessible, living knowledge base of adversary tactics and techniques against Al-enabled systems based on real-world attack observations and realistic demonstrations from Al red teams and security groups.
☑️ OWASP AI Security & Privacy Guide
☑️ OWASP GenAI Security Project
☑️ Google Secure AI Framework (SAIF)
#AI standards and frameworks
Information technology - Artificial intelligence - Artificial intelligence concepts and terminology
☑️ ISO/IEC 23053:2022
Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML)
☑️ ISO/IEC 23894:2023
Information technology - Artificial intelligence - Guidance on risk management
☑️ ISO/IEC TR 24028:2020
Information technology - Artificial intelligence - Overview of trustworthiness in artificial intelligence
☑️ ISO/IEC 42001:2023
Information Technology - Artificial Intelligence - Management System (AIMS)
☑️ ISO/IEC AWI 42003
Information technology - Artificial intelligence - Guidance on the implementation of ISO/IEC 42001
☑️ ISO/IEC 42005:2025
Information technology - Artificial intelligence (AI) - AI system impact assessment
☑️ ISO/IEC 42006:2025
Information technology - Artificial intelligence - Requirements for bodies providing audit and certification of artificial intelligence management systems
☑️ ISO/IEC AWI 42007
Information technology - Artificial intelligence - High-level framework and guidance for the development of conformity assessment schemes for AI systems
☑️ NIST AI Risk Management Framework (AI RMF)
(Rev 1.0 - 2023)
☑️ NIST SP 800-53
Security and Privacy Controls for Information Systems and Organizations (Rev 5.1.1 - Nov 7, 2023)
☑️ EU AI Act
The AI Act is a European regulation on artificial intelligence (AI)
(July 2024)
☑️ General Data Protection Regulation (EU GDPR)
Europe’s data privacy and security law includes hundreds of pages’ worth of new requirements for organizations around the world
(May 2018)
☑️ ENISA AI Cybersecurity Guidelines
☑️ High-Level Expert Group on AI (HLEG) Ethics Guidelines
⬇️ Technical Part
☑️ MITRE ATLAS™
ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems) is a globally accessible, living knowledge base of adversary tactics and techniques against Al-enabled systems based on real-world attack observations and realistic demonstrations from Al red teams and security groups.
☑️ OWASP AI Security & Privacy Guide
☑️ OWASP GenAI Security Project
☑️ Google Secure AI Framework (SAIF)
#AI standards and frameworks
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Future of #cloud
According to Gartner, by 2027, cloud computing will become a key driver for business innovation and the common style of computing.
According to Gartner, by 2027, cloud computing will become a key driver for business innovation and the common style of computing.
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A Secure Web Gateway (SWG) is a security solution that protects users from web-based threats by enforcing policies and filtering traffic.
#security
#security
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1. Hyper-Modular #Microservices
While microservices have been the standard for several years, 2025 sees this approach becoming even more #modular and granular. The concept of hyper-modular microservices involves breaking down traditional microservices into smaller, highly specialized services. This enables even more flexibility and faster deployment cycles. In this architecture, each #service is lightweight and designed to fulfill a specific function, making the system easier to maintain and scale as needed. This trend aligns with the growing demand for highly adaptable and rapidly deployable applications.
While microservices have been the standard for several years, 2025 sees this approach becoming even more #modular and granular. The concept of hyper-modular microservices involves breaking down traditional microservices into smaller, highly specialized services. This enables even more flexibility and faster deployment cycles. In this architecture, each #service is lightweight and designed to fulfill a specific function, making the system easier to maintain and scale as needed. This trend aligns with the growing demand for highly adaptable and rapidly deployable applications.
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2. AI-Optimized Architectures
#AI and machine learning are no longer just add-ons; they are integral to the #architecture itself. AI-optimized architectures involve embedding intelligent algorithms into the core layers of applications, allowing systems to self-optimize in real-time based on changing conditions. These architectures can dynamically adjust resource allocation, optimize workflows, and enhance user experiences through predictive analytics. AI-driven infrastructure management, where the architecture adapts and evolves autonomously, is expected to be a major trend by 2025.
#AI and machine learning are no longer just add-ons; they are integral to the #architecture itself. AI-optimized architectures involve embedding intelligent algorithms into the core layers of applications, allowing systems to self-optimize in real-time based on changing conditions. These architectures can dynamically adjust resource allocation, optimize workflows, and enhance user experiences through predictive analytics. AI-driven infrastructure management, where the architecture adapts and evolves autonomously, is expected to be a major trend by 2025.
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3. Quantum-Ready Architectures
As #quantum computing becomes more accessible, software architecture is being designed to leverage the power of quantum algorithms. By 2025, developers are beginning to incorporate quantum-ready architectures that can interface with both classical and quantum computing environments. These hybrid architectures allow applications to perform complex calculations that were previously impossible with classical computing alone. Industries such as cryptography, logistics, and pharmaceuticals are particularly interested in quantum-ready solutions to gain competitive advantages.
As #quantum computing becomes more accessible, software architecture is being designed to leverage the power of quantum algorithms. By 2025, developers are beginning to incorporate quantum-ready architectures that can interface with both classical and quantum computing environments. These hybrid architectures allow applications to perform complex calculations that were previously impossible with classical computing alone. Industries such as cryptography, logistics, and pharmaceuticals are particularly interested in quantum-ready solutions to gain competitive advantages.
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4. Composable Enterprise Architecture (CEA)
In 2025, #composable #architecture is set to become the backbone of enterprise software. #CEA allows businesses to build digital systems from interchangeable #components that can be quickly reassembled as market conditions or strategies evolve. This #modular approach enhances business agility by enabling rapid iteration and customization without major overhauls. The composable enterprise architecture concept also integrates low-code and no-code platforms, empowering non-technical stakeholders to contribute directly to application development.
In 2025, #composable #architecture is set to become the backbone of enterprise software. #CEA allows businesses to build digital systems from interchangeable #components that can be quickly reassembled as market conditions or strategies evolve. This #modular approach enhances business agility by enabling rapid iteration and customization without major overhauls. The composable enterprise architecture concept also integrates low-code and no-code platforms, empowering non-technical stakeholders to contribute directly to application development.
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5. Decentralized and Blockchain-Driven Architectures
The adoption of #decentralized systems continues to expand in 2025, driven by #blockchain and distributed ledger technology (DLT). Decentralized architectures enable trustless transactions, greater transparency, and enhanced security. While these architectures have been associated with cryptocurrencies, their applications are broadening across industries like supply chain management, finance, and even content distribution. Smart contracts and decentralized autonomous organizations (#DAOs) are also becoming more prevalent as programmable governance frameworks, allowing businesses to operate with minimal centralized control.
The adoption of #decentralized systems continues to expand in 2025, driven by #blockchain and distributed ledger technology (DLT). Decentralized architectures enable trustless transactions, greater transparency, and enhanced security. While these architectures have been associated with cryptocurrencies, their applications are broadening across industries like supply chain management, finance, and even content distribution. Smart contracts and decentralized autonomous organizations (#DAOs) are also becoming more prevalent as programmable governance frameworks, allowing businesses to operate with minimal centralized control.
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6. Sustainable and Energy-Efficient Architectures
With environmental concerns becoming a global priority, the #sustainability of software architectures is now a key consideration. In 2025, #energy-efficient architectures are designed with a focus on minimizing the carbon footprint of software systems. This involves optimizing code for low-power consumption, leveraging #edge #computing to reduce data transfer, and using AI to monitor and minimize energy use. Green cloud solutions and carbon-neutral software development practices are not just trends but necessities in this era of environmental consciousness.
With environmental concerns becoming a global priority, the #sustainability of software architectures is now a key consideration. In 2025, #energy-efficient architectures are designed with a focus on minimizing the carbon footprint of software systems. This involves optimizing code for low-power consumption, leveraging #edge #computing to reduce data transfer, and using AI to monitor and minimize energy use. Green cloud solutions and carbon-neutral software development practices are not just trends but necessities in this era of environmental consciousness.
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7. Edge-Native Architectures
#Edge #computing has advanced from a complementary technology to a primary architectural strategy. By 2025, edge-native architectures are specifically designed to operate efficiently at the edge, where data is processed as close to the source as possible. These architectures are crucial for real-time applications such as autonomous vehicles, smart cities, and industrial #IoT. Edge-native systems combine low latency with high availability, supporting use cases that demand immediate decision-making and data processing at the network’s edge.
#Edge #computing has advanced from a complementary technology to a primary architectural strategy. By 2025, edge-native architectures are specifically designed to operate efficiently at the edge, where data is processed as close to the source as possible. These architectures are crucial for real-time applications such as autonomous vehicles, smart cities, and industrial #IoT. Edge-native systems combine low latency with high availability, supporting use cases that demand immediate decision-making and data processing at the network’s edge.
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8. Zero-Trust Security Architectures
#Security is a fundamental concern in any #architecture, and in 2025, zero-trust principles are at the core of modern system design. Zero-trust architectures assume that every request, whether inside or outside the network, is a potential threat. This approach involves continuous authentication, granular access controls, and micro-segmentation. As cyberattacks become more sophisticated, building security directly into the architecture rather than relying on perimeter-based defenses is critical for protecting sensitive data and maintaining operational integrity.
#Security is a fundamental concern in any #architecture, and in 2025, zero-trust principles are at the core of modern system design. Zero-trust architectures assume that every request, whether inside or outside the network, is a potential threat. This approach involves continuous authentication, granular access controls, and micro-segmentation. As cyberattacks become more sophisticated, building security directly into the architecture rather than relying on perimeter-based defenses is critical for protecting sensitive data and maintaining operational integrity.
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9. Federated and Collaborative AI Systems
In 2025, federated learning and collaborative #AI architectures are enabling multiple organizations to train AI models collectively while keeping their data private. This trend is essential in industries where data sharing is restricted due to privacy regulations. By using decentralized AI training methods, organizations can collaborate on global AI models without exposing their proprietary data. These architectures are particularly important in healthcare, finance, and government sectors.
In 2025, federated learning and collaborative #AI architectures are enabling multiple organizations to train AI models collectively while keeping their data private. This trend is essential in industries where data sharing is restricted due to privacy regulations. By using decentralized AI training methods, organizations can collaborate on global AI models without exposing their proprietary data. These architectures are particularly important in healthcare, finance, and government sectors.
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