# Responsible AI Training and AI Governance Program > Responsible AI training for leaders and practitioners on AI risk, governance frameworks and practical controls, taught through real business cases. - Source: https://bodhih.com/responsible-ai-training/ - Publisher: Bodhih Training (Bengaluru, India; since 2008) - Last updated: 2026-10-15 - Contact: solutions@bodhih.com · +91 99000 11601 --- Responsible AI training for the people who approve, build, buy and oversee AI. Participants learn how to identify AI risks, apply recognised governance frameworks and put practical controls in place, so AI adoption can move quickly while staying fair, secure, transparent and accountable. ## At a glance - **Duration:** Recommended: 2 days in person, or 4 × 3-hour live virtual sessions - **Who it’s for:** Business leaders, risk and compliance, product owners, data and IT teams - **Level:** Intermediate - **Format:** In person · Live virtual · Blended - **Track record:** Since 2008 · 2,000+ companies Responsible AI training teaches leaders and practitioners how to govern AI systems across their lifecycle. It covers fairness, transparency, privacy, security and accountability, and applies the NIST AI Risk Management Framework, ISO/IEC 42001 and India's AI Governance Guidelines through risk assessments on business cases. Bodhih runs it over 2 days in person or four 3-hour virtual sessions. - Recommended: 2 days in person, or 4 × 3-hour live virtual sessions - Level: Intermediate · In person · Live virtual · Blended - Designed with the ADDIE model and customised to your context - Offered by Bodhih since 2008 to 2,000+ organisations across 7 regions **Also known as:** AI governance training, AI ethics training, AI risk management training, nist AI rmf training **Where and how:** responsible AI training as an in-person workshop in [Bengaluru](https://bodhih.com/corporate-training-in-bangalore/), [Mumbai](https://bodhih.com/corporate-training-in-mumbai/), [Delhi NCR](https://bodhih.com/corporate-training-in-new-delhi/), [Gurugram](https://bodhih.com/corporate-training-in-gurugram/), [Hyderabad](https://bodhih.com/corporate-training-in-hyderabad/), [Chennai](https://bodhih.com/corporate-training-in-chennai/), [Pune](https://bodhih.com/corporate-training-in-pune/), [Kolkata](https://bodhih.com/corporate-training-in-kolkata/), [Ahmedabad](https://bodhih.com/corporate-training-in-ahmedabad/) and [Jaipur](https://bodhih.com/corporate-training-in-jaipur/); as a live online course; or delivered overseas in [Dubai](https://bodhih.com/corporate-training-in-dubai/), [Singapore](https://bodhih.com/corporate-training-in-singapore/) and across the Middle East, Asia and Africa. Last reviewed 15 Oct 2026 by [Siddharthan VGJ](https://bodhih.com/siddharthan-vgj/), Founder · Bodhih Training, Bengaluru ## Governance has to keep pace with adoption AI use cases are multiplying across functions, often faster than policies and review processes. Without shared methods, teams either block useful ideas or approve risky ones without noticing. Responsible AI training gives business, technology and risk teams a common language and toolkit. It draws on published frameworks, including the NIST AI RMF released in January 2023 and India's AI Governance Guidelines released by MeitY in November 2025. ## What participants will be able to do ### Name the core principles Explain fairness, transparency, privacy, safety, security and [accountability](https://bodhih.com/accountability-at-work-training/) with workplace examples. ### Assess AI risk Run a structured risk and impact assessment on a proposed AI use case and rate its severity. ### Apply known frameworks Map organisational practices to the NIST AI RMF functions and the ISO/IEC 42001 management system approach. ### Design practical controls Choose controls such as human review, testing, monitoring and data minimisation that fit the level of risk. ### Set up governance roles Define who approves, owns, monitors and retires AI systems, and how issues are escalated. ### Communicate transparently Draft clear notices and explanations for users and customers affected by AI-supported decisions. ## Who should attend - Senior leaders and AI steering committee members - Risk, compliance, legal and internal audit professionals - Product owners and business sponsors of AI initiatives - Data science, engineering and IT architecture teams in [GCCs](https://bodhih.com/gcc-leadership-development-program/) - Procurement and vendor managers buying AI-enabled products ## Program outline Recommended design, customised to your context after a short needs analysis. ### **Why responsible AI matters**Module 1 · 90 min - Principles and where they come into tension - Real incidents and what went wrong - Business value of trustworthy AI ### **Understanding AI risk**Module 2 · 2 hours - Bias and fairness in data and models - [Generative AI](https://bodhih.com/generative-ai-training/) risks: hallucination, leakage, prompt injection - Privacy, intellectual property and security concerns - Automation bias and over-reliance ### **Frameworks and guidelines**Module 3 · 2.5 hours - NIST AI RMF: Govern, Map, Measure and Manage - ISO/IEC 42001 as a management system standard for AI - India's AI Governance Guidelines and data protection context - The EU AI Act's risk-based approach for global operations ### **AI risk and impact assessment lab**Module 4 · 2.5 hours - Scoping a use case and its stakeholders - Scoring likelihood and impact - Choosing proportionate controls - Lab: a credit pre-screening assistant and an HR resume screener ### **Operating model and controls**Module 5 · 2 hours - Roles, committees and approval gates - Model documentation, testing and monitoring - Vendor and third-party AI due diligence - Incident response for AI failures ### **Policy to practice**Module 6 · 90 min - Acceptable-use policy and data do's and don'ts - Transparency notices and user communication - Your 90-day governance action plan ## Sample training plan: 2-day hands-on design This two-day workshop teaches cross-functional teams to govern AI in practice, not just discuss principles. Business, risk, legal and technology participants sit together and work on real use cases: a credit pre-screening assistant for a lender and a resume screener for HR. They test a model's outputs for bias, attack a chatbot with prompt injection, map practices to public frameworks such as the NIST AI RMF and ISO/IEC 42001, run a full risk and impact assessment, choose proportionate controls and argue a go or no-go at a mock AI steering committee. 72% hands-on practice · 13.5 contact hours · Cohort: 12–24 participants in mixed business, technology and risk tables · In person · Live virtual ### Day 1: Principles and real risks Participants can explain responsible AI principles, spot concrete risks in live use cases and relate them to public frameworks. 1. 09:30–10:00 · Would you sign off? (Energiser) 2. 10:00–11:00 · When AI went wrong (Case clinic) 3. 11:15–12:00 · Principles in tension (Debate) 4. 12:00–13:00 · Bias test lab (Hands-on lab) 5. 13:45–14:45 · Break the chatbot (Group challenge) 6. 14:45–15:30 · Frameworks without the fog (Concept burst) 7. 15:45–16:45 · Scope your own use case (Build sprint) 8. 16:45–17:30 · Day one reflection (Reflection) ### Day 2: Assess, control and govern Participants can assess AI risk, design proportionate controls, set up governance roles and communicate decisions. 1. 09:30–10:00 · Likelihood and impact warm-up (Energiser) 2. 10:00–11:15 · Risk and impact assessment lab (Hands-on lab) 3. 11:30–12:30 · Proportionate controls (Group challenge) 4. 13:15–14:00 · Who owns what (Build sprint) 5. 14:00–14:45 · Buying AI from vendors (Role-play) 6. 15:00–15:45 · Telling people plainly (Skill drill) 7. 15:45–16:45 · Capstone: AI steering committee (Simulation) 8. 16:45–17:30 · My 90-day governance plan (Action planning) Recommended: 2 days in person (09:30–17:30), or 4 × 3-hour live virtual sessions, with a 90-day governance action plan review. Training only: it does not certify your organisation and is not legal advice. A sample design: every Bodhih program is customised after a short needs analysis. ### How long is responsible AI training? The recommended design is two days in person, 09:30 to 17:30, or four live virtual sessions of three hours. Mixed teams work on realistic use cases throughout. A half-day briefing suits boards and senior leaders, and a 90-day plan review follows the program. ### What activities are included in responsible AI training? Participants test a resume-screening model for bias, try to break a sandbox chatbot with prompt injection, map practices to public frameworks, run a full risk and impact assessment, buy proportionate controls with a token budget, question an evasive AI vendor and present to a mock steering committee. ## How we deliver it ### Case-based learning Every framework is applied to a realistic use case from BFSI, HR, manufacturing or IT services, so participants practise decisions, not definitions. ### Cross-functional cohorts We recommend mixing business, technology and risk participants so each hears the others' concerns and trade-offs. ### Templates you can adopt Participants leave with a risk assessment template, control checklist and role map that can be adapted to your policy. ### Training, not certification Standards such as ISO/IEC 42001 are taught as subject matter. The program does not certify your organisation and is not legal advice. ## Tailored versions ### For boards and senior leaders A half-day briefing on AI risk appetite, oversight questions to ask and how to read governance reports. ### For practitioners in GCCs Deeper coverage of model documentation, evaluation, monitoring and handling client governance requirements. ### For BFSI teams Scenarios on credit, fraud, collections and [customer service](https://bodhih.com/customer-service-excellence-training/), with emphasis on fairness, explainability and customer data. ## How we measure impact Following the Evaluate stage of ADDIE, participants complete a scenario-based pre and post assessment on AssessAll that tests their ability to spot risks and choose controls. The capstone risk assessment is reviewed against a rubric. At 30, 60 and 90 days we check progress on each team's governance action plan with sponsors and summarise adoption of templates, review gates and escalation routes. AA Pair this program with [AssessAll](https://assessall.com), Bodhih’s AI assessment platform, for pre- and post-program skill measurement. ## Frequently asked questions ### What is responsible AI training? It is a program that teaches people how to design, buy, deploy and oversee AI in ways that are fair, safe, secure, transparent and accountable. Responsible AI training blends principles with practical tools, such as risk assessments, controls and governance roles, applied to realistic business use cases. ### What is the NIST AI Risk Management Framework? The NIST AI RMF is a voluntary framework from the US National Institute of Standards and Technology, released in January 2023. It organises AI risk management into four functions, Govern, Map, Measure and Manage, and NIST has since published a companion profile for generative AI. Many organisations worldwide use it as a practical reference. ### What is ISO/IEC 42001? ISO/IEC 42001, published in December 2023, is an international standard that sets out requirements for an AI management system within an organisation. The program introduces its structure and intent as a subject of study. Bodhih does not certify organisations against it, and participants should consult accredited bodies for certification. ### What are India's AI Governance Guidelines? They are guidelines released by the Ministry of Electronics and Information Technology in November 2025 to encourage safe and trusted AI adoption. They set out guiding principles and recommendations for institutions and industry. The program summarises their intent and how they relate to your internal policies; always refer to the official text. ### Who needs AI governance training? Anyone who approves, sponsors, builds, buys or audits AI systems benefits. That includes senior leaders, risk and compliance teams, product owners, data and engineering teams and procurement. Everyday AI users usually need [AI literacy](https://bodhih.com/ai-literacy-training/) training instead, with a lighter touch on governance. ### Is this program legal or compliance advice? No. Our responsible AI training builds understanding and practical skills, and the templates are starting points for your own policies. Laws and guidance in the EU, India and elsewhere continue to change, so please check current official sources and consult your legal advisers for decisions on compliance obligations. ### How is responsible AI training different from AI literacy training? AI literacy training gives every employee a baseline understanding of AI, its risks and safe use. Responsible AI training goes deeper for the smaller group who approve, build, buy or audit AI systems. It covers risk and impact assessment, governance roles, controls and frameworks, and it ends with a governance action plan for each team.