Responsible AI training teaches leaders and practitioners how to govern AI systems across their lifecycle. It covers fairness, transparency, privacy, security and accountability, and introduces frameworks such as the NIST AI Risk Management Framework, ISO/IEC 42001 and India's AI Governance Guidelines, applied through risk assessments on realistic business use cases.
- 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, Mumbai, Delhi NCR, Gurugram, Hyderabad, Chennai, Pune, Kolkata, Ahmedabad and Jaipur; as a live online course; or delivered overseas in Dubai, Singapore and across the Middle East, Asia and Africa.
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 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
- Procurement and vendor managers buying AI-enabled products
Program outline
Recommended design, customised to your context after a short needs analysis.
01Why responsible AI mattersModule 1 · 90 min+
- Principles and where they come into tension
- Real incidents and what went wrong
- Business value of trustworthy AI
02Understanding AI riskModule 2 · 2 hours+
- Bias and fairness in data and models
- Generative AI risks: hallucination, leakage, prompt injection
- Privacy, intellectual property and security concerns
- Automation bias and over-reliance
03Frameworks and guidelinesModule 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
04AI risk and impact assessment labModule 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
05Operating model and controlsModule 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
06Policy to practiceModule 6 · 90 min+
- Acceptable-use policy and data do's and don'ts
- Transparency notices and user communication
- Your 90-day governance action plan
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, 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.
Pair this program with AssessAll, 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 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.