Krishna Singh

About Krishna Singh

Enterprises are spending billions on AI. Most of it never delivers real business outcomes in production. Most enterprise AI initiatives are not failing because of bad models. They are failing because the solution was built without truly understanding the data landscape, the governance gaps, or the regulatory constraints. I help C-suite leaders make sure the opposite happens.I\'ve spent 22 years at the intersection of data engineering and AI-driven business outcomes. The first 16 were spent building the data foundations that AI now depends on — data pipelines, data integration, data governance, data quality, data lake ecosystems on multi-cloud and on-premise infrastructure, and analytics engines that turn raw data into insights and recommendations. I understand what production-grade data infrastructure demands, because I\'ve architected it from the ground up. That foundation matters — every AI model is only as reliable as the data layer underneath it.For the past 6+ years, I\'ve brought that data engineering depth into the AI space — designing and operationalizing ML pipelines, building Generative AI and RAG solutions, architecting multi-agentic AI systems, and standing up MLOps/LLMOps practices.Before an AI initiative moves forward, I ensure AI fits real business processes and delivers measurable P&L impact, not just impressive demos. I know what it takes to move from proof-of-concept to production, because I\'ve built both sides of that equation.Where I work with CXOs: • AI Transformation Strategy • ML, GenAI & Agentic AI Architecture • Data Engineering Pipeline • Regulatory AI Compliance • Data Foundation AssessmentRegulated industries where I\'ve delivered — not just advised: • Banking & Financial Services - Model Risk Management (MRM) • Pharma & Life Sciences - GxP, FDA 21 CFR Part 11, HIPAA/GDPR • Oil & Gas / Energy - Sustainability, ESG,CSRD compliance • Automotive & ManufacturingA continual learner who balances short-term goals with long-term vision, I\'ve built and led high-performing teams, established Centers of Excellence, and fostered cultures of continuous improvement — because sustainable AI transformation isn\'t a project, it\'s an operating model.

Experience

1. Principal Consultant -ai Strategy & Transformation Leader

   Capgemini

   Feb 2020 — Present · US

   Driving enterprise AI transformation — designing AI strategy grounded in data reality, assessing readiness before investment is committed, and architecting solutions that move from proof-of-concept to production. I connect AI investment to measurable P&L impact, not impressive demos.I lead Data and AI readiness assessments evaluating data maturity, governance posture, and regulatory compliance before initiatives are proposed — because every AI model is only as reliable as the data layer underneath it. I architect enterprise data pipelines, RAG systems, multi-agent AI workflows using LangGraph and MCP, and production-grade ML systems.Regulated industries where I\'ve delivered: Banking MRM, Pharma (GxP, FDA 21 CFR Part 11), Energy (CSRD, ESG).

Education

• Birla Institute of Technology and Science, Pilani

  Master of Technology - M.Tech