Jean-Michel VAN

For Org Leaders: How to Avoid AI Pilot Failures

Veeva Systems

IQVIA

Product School

Envision Pharma Group

Co-founder & CEO at Ryseflow AI (ex-Head of Products at Healthcare Fortune500)

Understand the decision mistakes leaders make when funding AI initiatives.

Identify why most AI pilots fail before delivering ROI

Learn how to evaluate AI opportunities based on impact, risk, and adoption.

Apply a simple AI ROI scorecard

Leave with confidence that you can get a ranked list of AI opportunities you can confidently sponsor.

Prioritize AI use cases into a clear execution backlog

Join the top 1% of AI-powered project managers & leaders shaping how work gets done, while others are still managing tasks.

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CEO @ Projects Right | AI & Projects

Microsoft

Amazon

Chevron

McKesson

Medtronic

Justin Bateh, PhD

CEO | 25,000+ learners | 80+ Projects | 8x Awards | LinkedIn Learning Instructor

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No map. No playbook. No backup. Just pressure to deliver.That’s the reality most professionals face now.Titles don’t matter. Results do.The truth: if you can’t lead projects + use AI, you’re replaceable. Companies aren’t paying for effort. They’re paying for execution that moves the bottom line.That’s why I built the Project Execution Framework™, a 7-step system I’ve taught to thousands of leaders to align teams, use AI strategically, accelerate execution, &amp; deliver results that get noticed.And these aren’t abstract lessons. You’ll walk away knowing how to:<ul><li>Fix stakeholder misalignment</li><li>Eliminate busywork with real AI workflows.</li><li>Lead confidently even when you don’t have the title.</li></ul>It’s about learning the practical survival skills that keep you valuable when pressure is high &amp; outcomes matter most. This is your solution to future-proof your career.In a world where projects fail daily and AI reshapes work overnight, this course is your insurance policy. Miss it, and you'll fall behind. Take it and you secure your seat at the table.*Live attendance is optional. Learn live if you can, or use the recordings when it fits your schedule.*Join February's cohort &amp; lock in a complimentary retake.

Evolve beyond task management into the top 1% of AI-powered project leaders.

A clear execution model to run projects with confidence and control

A decision-level leadership approach that works without formal authority

AI-assisted workflows that reduce coordination and improve decisions

A stakeholder influence system that drives alignment and momentum

A repeatable project execution system you can scale across teams

You’re here to apply, decide, and deliver in real situations, not study for an exam.

You want to run real projects, not memorize vocabulary. 

You want tools and systems that work when priorities collide and stakes are high.

You care more about execution under pressure than perfect theory.

You want practical ways to reduce friction and improve decisions, not tool hype.

You’re ready to use AI as leverage, not as a checkbox skill.

Aspiring or Accidental Project Managers No title, no playbook? Gain the skills to lead with clarity and confidence.

Mid-Level Managers Projects everywhere, chaos nonstop? Learn to lead with structure, speed, and AI.

Senior Leaders &amp; Founders Strong teams, but stalled execution? Align stakeholders, cut noise, and deliver results.

A systems-first leadership OS for decision velocity, intelligent execution & AI-native transformation

AI Executive & Educator | Microsoft MVP 

Vidhi Chugh

AI Executive & Board Member | Microsoft MVP | AI Patentholder | 150k students

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Most AI initiatives fail for reasons that have nothing to do with models, tools, or talent.They fail because of two recurring issues:1) Teams start with a solution instead of a problem2) Leaders miss a clear decision lens for when and how to pursue AI Experienced leaders know this pattern well:<ul><li>Promising ideas that lead to "Let’s just pilot and see"</li><li>Those pilots “work” technically but collapse when scaled</li><li>Trade-offs are being glossed over because problem is slowly reshaped to fit the solution</li><li>Costs, risk, and failure modes surface far too late</li></ul>AI amplifies this problem because its requirements are hard to specify upfront, and once commitments are made, decisions become expensive or irreversible.This course is anchored in decisions, not just knowledge. If these thoughts sound familiar, this course is for you:<ul><li>We’re betting too much on something we barely understand.</li><li>This could blow up with severe consequences.</li><li>Everyone wants agents; no one wants ownership.</li><li>If this fails, it’ll be on me.</li><li>Everything is moving too fast, but business impact still feels shallow.</li></ul>By the end of this course, you’ll own AI decisions, without relying entirely on vendors, technical teams, or external opinions.

A problem-first system for making high-stakes AI decisions

Opportunity Discovery Framework

Decision Velocity Toolkit

Experiential AI Systems Under Enterprise Constraints

AI Tradeoff Radar

Learn what “good” looks like, how to measure success. 

Enterprise leaders (heads of AI, data, or innovation) asked to sponsor or approve AI initiatives.

Entrepreneurs &amp; Founders who are either building an AI-first company or integrating AI agents into an existing business

Product &amp; Strategy Leaders looking for the tools to prioritize AI opportunities, assess feasibility, and measure ROI effectively

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

Circle I

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.

Lead AI initiatives with clear goals, defensible evaluation, explicit risk decisions, and exec updates that drive alignment and investment.

CPO, GM xBraintrust, Nextdoor, OpenTable

Braintrust 🧠

Nextdoor

LiquidSpace I Work from where it works.

OpenTable

BlackRock

Elena Luneva

f-CPO. Product executive (Braintrust, Nextdoor, OpenTable, LiquidSpace)

AI Career Boost Founder, Coach, Advisor

Schneider Electric

Convergent Media Solutions

Polly Allen

AI Product Coach, Advisor, AI Career Boost Founder

AI increases IC leverage, but it also breaks the management systems most teams rely on. Prototypes multiply. “Quality” becomes subjective. Risk can ship quietly. Leadership gets pulled into every review because no one is sure what good looks like, or who is accountable for evaluation, failure modes, and rollout decisions.If you’re a Director, Head of Product/Eng/Data, or VP with multiple AI initiatives in flight, you’re likely seeing the same pattern: lots of demos, uneven production outcomes, rising cost and reliability questions, and execs asking, “How do we know it’s good?” “What can go wrong?” “What’s the ROI?”This workshop gives you a practical operating system for leading AI-native work without slowing teams down. You’ll leave with a repeatable review process to assess evaluation and risk, a portfolio and cadence that prevents orphan experiments, and executive-ready updates that translate AI progress into cost, ROI, risk posture, and clear next decisions. The result: faster alignment, fewer surprises, and AI work that ships to production with confidence.

Lead AI-heavy teams with clear standards, explicit decisions, and real outcomes.

Run AI evaluation and risk reviews that drive decisions

Install an AI-native operating cadence that keeps speed and alignment

Diagnose AI work patterns and catch drift before it ships

Communicate AI progress to execs and GTM

Manage AI cost and ROI as first-class leadership inputs

Reclaim 5 hours a week by shifting from approval gate to system architect

Director/Head of Product: Leads AI initiatives; turns prototypes into production with clear quality, gates, and exec updates.

Eng leader (Sr Mgr/Dir/VP): Ships AI fast while managing reliability, security, and cost with consistent eval + risk reviews.

Data/ML leader (Dir/Head): Owns evals and performance; aligns product and execs with shared language and decision-ready tradeoffs.