AWS prescriptive-guidance documentation change
Summary
Reformatted table structure by changing from bold headers to pipe-based alignment. Updated organizational capability layer description.
Security assessment
Formatting changes to table presentation without altering security-related content. The 'Security and compliance' row remains substantively unchanged, focusing on existing data protection considerations rather than introducing new security documentation.
Diff
diff --git a/prescriptive-guidance/latest/strategy-transform-adm-operating-model-gen-ai/challenges.md b/prescriptive-guidance/latest/strategy-transform-adm-operating-model-gen-ai/challenges.md index a473e6bbb..e298c8611 100644 --- a//prescriptive-guidance/latest/strategy-transform-adm-operating-model-gen-ai/challenges.md +++ b//prescriptive-guidance/latest/strategy-transform-adm-operating-model-gen-ai/challenges.md @@ -13,10 +13,10 @@ Area | Key challenges | Mitigation strategies -**Data management** | Data quality and integration challenges | Ensure consistent, high-quality data across diverse systems and processes. -**Governance and ethics** | AI governance and ethics | Establish clear guidelines for AI use and decision-making. -**Workforce adaptation** | Cultural adaptation | Prepare the workforce for AI-augmented roles. -**Process integration** | Integration with existing processes | Incorporate AI into established workflows seamlessly. -**Trust, reliability, and human oversight** | Validating AI-generated insights and recommendations for consistent accuracy | Maintain appropriate human control while taking advantage of AI automation. -**Technical complexity** | Lack of skills and experience | Manage the increased intricacy of AI-enhanced systems. -**Security and compliance** | Lack of data protection and IP ownership guidelines | Maintain data protection and regulatory adherence in AI-driven environments. -**Organizational alignment** | AI recommendation alignment | Ensure AI suggestions align with organizational policies and best practices. -**Platform complexity** | Lack of skills and readiness for change | Manage the intricacy of AI-enhanced platform and IT support services. -**Outsourcing challenges** | Capability gaps in outsourced operations | Address AI-readiness in managed service providers. +Data management| Data quality and integration challenges| Ensure consistent, high-quality data across diverse systems and processes. +Governance and ethics| AI governance and ethics| Establish clear guidelines for AI use and decision-making. +Workforce adaptation| Cultural adaptation| Prepare the workforce for AI-augmented roles. +Process integration| Integration with existing processes| Incorporate AI into established workflows seamlessly. +Trust, reliability, and human oversight| Validating AI-generated insights and recommendations for consistent accuracy| Maintain appropriate human control while taking advantage of AI automation. +Technical complexity| Lack of skills and experience| Manage the increased intricacy of AI-enhanced systems. +Security and compliance| Lack of data protection and IP ownership guidelines| Maintain data protection and regulatory adherence in AI-driven environments. +Organizational alignment| AI recommendation alignment| Ensure AI suggestions align with organizational policies and best practices. +Platform complexity| Lack of skills and readiness for change| Manage the intricacy of AI-enhanced platform and IT support services. +Outsourcing challenges| Capability gaps in outsourced operations| Address AI-readiness in managed service providers. @@ -30 +30 @@ To use the Amazon Web Services Documentation, Javascript must be enabled. Please -Organization capability layer +Organization capability layer of an ADM operating model