Tag: AI Governance
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Responsible AI, Model Risk and Governance That Survives an Audit (Data Science Series, Part 29)
Model governance is not a policy document. It is an inventory, an independent challenge function, and a monitoring trail that lets you answer who approved this model and on what evidence. Here is how I build one that holds up when an auditor asks.
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IBM watsonx vs the Field, the Cost Recap and the Verdict (IBM Gen AI Series, Part 24)
The final part of the IBM watsonx series puts the platform against Bedrock, Azure, and Vertex on the axes that decide a regulated purchase, recaps what a governed deployment really costs, and gives a clear verdict on where watsonx wins and where to walk away.
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watsonx Reference Architectures for RAG, Agentic, and Regulated Workloads (IBM Gen AI Series, Part 23)
The three watsonx reference architectures that recur in real builds: enterprise RAG on watsonx.data, agentic systems on watsonx Orchestrate, and a watsonx.governance overlay for regulated work. Which to build first, what each costs, and where they break.
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EU AI Act Readiness and Responsible AI on watsonx (IBM Gen AI Series, Part 21)
The 2026 Digital Omnibus pushed high-risk deadlines to December 2027, but GPAI and transparency duties still bite this year. Here is how I classify a watsonx system and build the evidence pack before an auditor asks.
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watsonx.governance Risk Monitoring and AI Factsheets (IBM Gen AI Series, Part 19)
How watsonx.governance tracks models, logs AI factsheets, monitors drift and bias in production, and maps controls to the EU AI Act. Part 19 of the IBM watsonx series.
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Vertex AI Responsible AI, Governance, and Audit Logging (Google Cloud Gen AI Series, Part 27)
Data Access audit logs, SynthID provenance, Model Registry, and Access Transparency, wired into a governance baseline for a Gemini workload on Vertex AI. What is on by default, what you have to switch on, and what it costs.
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About the Author
Dr Pranay Jha
Dr. Pranay Jha is a Cloud and AI Consultant with 18+ years of experience in hybrid cloud, virtualization, and enterprise infrastructure transformation. He specializes in VMware technologies, multi-cloud strategy, and Generative AI solutions. He holds a PhD in Computer Applications with research focused on Cloud and AI, has published multiple research papers, and has been a VMware vExpert since 2016 and a VMUG Community Leader.
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