Maya Kurup

AI educator & practitioner | MSc in AI | 20+ years in software & technology.

The “Oh Crap” AI Audit: 5 Risks Hiding in Your Business

Identify where everyday AI use can create problems with data, accuracy, people, access, and shadow AI.

Spot the AI risks already hiding in your business

Distinguish harmless experimentation from AI use that could create harmful business, customer, or employee consequences.

Know which AI risks actually deserve your attention

Complete a quick audit of your organization and identify the one AI risk you should investigate first.

Walk away with your own AI Risk Snapshot

You will move from using AI on faith to using it with judgement: spotting when it helps, catching when it harms, and knowing the difference.

Full Professor of Critical AI Literacy

WIRED

Financial Times

Scientific American

Dr Sam Illingworth

Founding Scholars (August 2026)

November 2026

You use AI every day at work, and you have started to feel the cost. It invents facts you have to catch, flattens your writing into the same grey voice everyone else is using, agrees with whatever you say, and quietly erodes the skills you are actually paid for. The hard part now is knowing when to believe what it gives you.AI is in the room for almost every professional decision, and the advice has not kept up. Most of it teaches you to prompt faster. None of it teaches you to judge what comes back.This course builds that judgement. Over four live sessions, taught through the humanities by a Full Professor of Critical AI Literacy, you learn to spot the four moves AI makes on you, name the hidden costs behind a confident answer, protect the skills you cannot afford to lose, and decide, every time, when to use AI and when to leave it alone.You practise on the work you actually do, running each method on your own AI tools, grounded in recent peer-reviewed research, alongside a cohort working through it with you. You leave with critical faculties you will use for the rest of your career.

Knowing when to trust AI is a skill. This is where you build it.

Catch AI fooling you before you act on it.

Protect the skills your work depends on.

Decide when to use AI and when to leave it alone.

A professional who uses AI daily for work, has started to quietly distrust it, and wants the judgement to know when to rely on it.

An educator or researcher who needs to think clearly about AI for their teaching, writing and students, beyond another list of prompts.

A manager, founder or team lead deciding how AI enters their team, who needs the judgement to govern it and explain it to others.

Learn practical ways to lead in responsible AI, with tools you can apply today. 

Responsible AI Advisor & Instructor 

Ahold Delhaize

Johnson & Johnson

ABN AMRO

Hinda Haned

Legatus I

Legatus II

Responsible AI is no longer a niche topic, it’s on the agenda of regulators, boards, and business leaders everywhere. In 2024 alone, governments worldwide issued more than twice as many AI-related regulations as the year before. Add to that more than 80 frameworks, countless checklists, and a steady stream of new tools, and the field quickly feels overwhelming. The real challenge isn’t whether AI should be used responsibly; it’s knowing where to begin. 🎯This course brings you back to the foundations: cutting through the noise, grounding you in what matters, and giving you a clear path forward.Here is detailed breakout of the course:🟩 Week 1: Power Session | Responsible AI PrimerA focused 3-hour session that cuts through the noise and gives you a practical overview of Responsible AI governance.🟩 Week 2: Mentoring &amp; Application | RAI Lab<blockquote>In the second week, you’ll have up to three hours of 1-to-1 mentoring to apply the tools directly to your own context. This may include building a governance checklist, evaluating a vendor, or stress-testing a project plan. The goal is for you to walk away with a concrete, business-ready action plan tailored to your organisation.</blockquote>

Your Responsible AI power session: from principles to practice

Understand core Responsible AI principles in practical business contexts

Recognise common AI risks through real-world system failures

Use a simple Responsible AI risk assessment framework

Define actionable first steps toward Responsible AI adoption

Anyone seeking a clear, practical intro to RAI with real-world examples to apply best practices or guide others effectively.

Leaders seeking to build or improve RAI governance with concrete SOPs and case studies from leading organizations.

Professionals who need to understand and apply RAI to meet regulatory and ethical standards, using field-tested examples.

Score your AI initiatives & build a board-ready report for your leadership team.

AI Strategist & Governance Architect

Cornell University

Google

Intel

Uber

Anderson D. Prewitt, PhD

Author of "Enhancing Business Value Through AI" | Board Advisor | AI Strategist

August 3 2026

Sep 11 2026

Your organization is deploying AI. Do you actually know where it's exposed?Most companies discover their AI risks the hard way: a financial write-down, a discrimination lawsuit, a data breach, a model that quietly starts producing toxic outputs. By then, the damage is done.IBM wrote down billions of dollars on it's Healthcare AI not because the AI was poorly built, but because no one applied a structured financial risk lens before deployment. Amazon's hiring AI systematically penalized candidates because no one audited it for disparate impact. As recently as 2026, Uber burned through its entire annual AI budget in four months because no one built a financial governance boundary into their agentic deployment.These aren't technology failures. They are governance failures. And they all had one thing in common: leaders who didn't know what to look for.The AEGIS Analysis Method is a structured, four-domain risk framework used by leaders to identify and neutralize AI governance risks before they become crises. In 2 hours, you'll apply it to a real AI initiative you're working on right now.You won't just learn the framework. You'll complete a scored AEGIS Risk Report for your own project.

This isn't a lecture. You do work & leave with a deliverable. By the end of this session, you'll have a clear understanding of your AI risk.

A completed AEGIS Risk Scorecard

 Your top 3 risk exposures 

The AEGIS Risk Assessment Template

 A One-page Executive Risk Summary

C-Suite Executives &amp; Boards who need a structured way to evaluate AI initiatives before signing off on investment or deployment.

Founders &amp; Operators who are deploying AI tools or building AI products and want to understand their exposure before a crisis finds them

AI Project Leads &amp; Program Managers who need to identify risks in their current initiative and report them upward with credibility.

Govern the AI tools you already use from HR to L&D. Know what's high-risk, build a governance map, and question vendors before you sign.

Founder,Aventura Frontiers | AI Builder 

Novartis

New York University

Aarti Mudaliar

18 Year HR Insider  | NYU Alumni | AWS , Google & Microsoft Certified 

Founder, INTLDA | AI Governance Advisor

Pfizer

Accenture

S&P Global

Uvika Sharma 

Founder, INTLDA | AI Governance Advisor | Keynote Speaker | Cornell Alum

Cohort 1

You didn't build the AI. You're still liable for it.McDonald's exposed 64 million applicant records through a default password. Air Canada was held liable for what its chatbot promised. Samsung lost 270,000 records through credentials no one rotated. Governance failures, not AI failures.Under the EU AI Act, you are the deployer of record. Article 4 requires AI literacy across your organization. Annex III classifies AI that scores assessments, routes learners, or decides who gets hired as high-risk. If you lead HR or L&amp;D, governance is your problem now.Most people leaders confuse responsible AI with governance. Responsible AI is the standard. Governance is the proof: who signs off, what gets logged, what you show a regulator when a decision is challenged.This course builds that proof live. You leave with three artifacts built on a tool your team uses: a risk-tiered inventory, a governance map, and a vendor accountability assessment. Two practitioners, 38 combined years in people operations and AI governance. Not a certificate. A file you hand your CHRO, CLO, or General Counsel on Monday.

You didn't build the AI. You're still liable for it. Here's the proof you need.

Know which of your people and learning AI tools are high-risk, and which aren't

Understand the difference between Responsible AI, AI Governance and Compliance

Build a one-page governance map for one tool you actually use

Score your vendors on evidence, not reassurance

Understand what the law actually requires of people and learning leaders now

Leave with three connected artifacts for one real tool from your stack

HR leaders who own hiring or workforce AI tools and need to govern them before a regulator forces the conversation.

L&amp;D leaders whose platforms assess, score, or route learners, and who now carry the EU AI Act's literacy mandate.

People Ops and HRBP leaders who sit between the business and the tools and need to know where humans stay in the loop.

Agentic AI

Coding with AI

AI Workflows

Claude Code

OpenClaw

Vibe Coding

AI Evals

AI Transformation

RAG & Search

AI for PMs

AI for Engineers

AI for Designers

AI for Marketers

AI for Founders

Product Sense

Product Discovery

User Research

Prototyping

Growth

Analytics

Tech Foundations

Strategy

Influence

Leadership

Career Growth

Machine Learning

LLM Ops

Context Eng

Security

System Design

Figma

Design Systems

Visual Design

Design Strategy

Automation

Content Marketing

Demand Gen

Go-to-Market

Product Marketing

Positioning

Social Media

Brand

B2B Marketing

SEO & AEO

AI for Leaders

AI Governance

Communication

Management

People Operations

Exec Presence

Storytelling

Goal-setting

Personal Brand

Fundraising

Everyone

Operators

Data Scientists

Business Analysts

User Researchers

Customer Success

Project Managers

HR Professionals

Sales People

Lawyers

Finance

Investors

Real Estate

Educators

Creators

Executives and senior leaders who set strategy, lead teams, and drive organizational outcomes.

Operations professionals who optimize processes and manage day-to-day business functions.

Applying AI tools and techniques to professional workflows — assign alongside more specific AI topics.

Establishing policies, ethics frameworks, and oversight for responsible AI use in organizations.

The “Oh Crap” AI Audit: 5 Risks Hiding in Your Business

What you'll learn

Why this topic matters

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Maya Kurup