An enterprise AI strategy links AI investments to measurable business outcomes, manages risk, and builds the capability to deliver. Dr Padmanabhuni's advisory combines AI strategy with AI assurance. Every roadmap includes how each AI system will be tested, monitored and governed, so the business value can be proven to boards, regulators and customers.
Independent, vendor-neutral advice from someone who has done the research, built the systems and sat on the other side of the table.
AI governance turns responsible AI principles into decisions and evidence. Dr Srinivas Padmanabhuni helps boards, CXOs and institutions set up AI governance that works in practice: an inventory of AI systems, risk classification, clear ownership, policies for generative and agentic AI, human oversight, and testing and monitoring that produce audit-ready evidence.
Typical outputs: an AI governance charter and operating model; an AI risk register and use-case approval process; a responsible AI policy covering fairness, explainability, privacy, security and transparency; guardrails and evaluation plans for LLMs and AI agents; and a board-level AI risk dashboard. See common questions on AI governance.
ISO/IEC 42001 – the international standard for an AI management system. testAIng.com / AiEnsured, where Dr Padmanabhuni is Co-founder & CTO, is ISO/IEC 42001 certified.
NIST AI Risk Management Framework (AI RMF) – Govern, Map, Measure and Manage functions for AI risk.
EU AI Act – risk-based obligations for providers and deployers of AI systems placed on the EU market.
India AI Governance Guidelines (MeitY, November 2025) and the RBI FREE-AI framework (Framework for Responsible and Ethical Enablement of AI, August 2025) – the seven sutras for trusted AI in India and in financial services.
Digital Personal Data Protection (DPDP) Act, 2023 – India's data protection law, central to any AI system that uses personal data.
For leadership teams deciding where AI fits. Opportunity mapping, use-case prioritisation (value, feasibility and risk), build/buy/partner choices, operating model and a 12-24 month roadmap. Outcome: a board-ready AI strategy with measurable milestones.
Governance frameworks, risk assessment, model testing and assurance strategy so AI is safe, fair, explainable, privacy-preserving and audit-ready; aligned with India's DPDP Act, emerging Indian AI governance guidance, ISO/IEC 42001 and the EU AI Act.
Architecture reviews, guardrails, orchestration and evaluation strategy for multi-agent systems, and the workforce and process implications of agentic automation.
From pilots to production: use-case selection, evaluation, cost and risk controls, and change management.
Board briefings, AI literacy for directors, technology due diligence for investors, and advisory roles for AI start-ups.
Keynotes, masterclasses, faculty-development programmes and corporate workshops, including programmes delivered for 15+ corporates (see Corporate AI Enablement).
1) Discovery call. 2) Diagnostic (2-4 weeks). 3) Strategy, roadmap or assurance blueprint. 4) Ongoing advisory retainer or board seat. Formats: retainer, project, workshop, keynote.
Banking and financial services, healthcare and MedTech, IT services, education, agri and food supply chains, media.
Please reach out through the Contact page.