Why Do Most AI Initiatives Fail?

  • Many organizations are experimenting with AI,
but struggle to identify initiatives that are
feasible, valuable, and responsible.



    This course helps you evaluate AI opportunities
before investing time, money, and resources.

What You'll Gain

By the end of this course, you’ll have concrete tools and outputs you can immediately apply to your work.

01
Identify High-Value AI Opportunities

Learn how to spot practical, low-risk AI opportunities. Apply structured ideation techniques to uncover ideas that support real business and user needs.

02
Apply Proven AI Evaluation Frameworks

Use research-driven frameworks to evaluate AI concepts based on value, feasibility, risk, and organizational readiness — so you can confidently prioritize the right initiatives.

03
Design Responsible AI Experiences

Leave with practical methods for designing AI-driven interfaces and features that support users, align with business goals, and reduce the risk of harmful AI outcomes.

Taught By Our Experts

Kerry Bodine

CEO

Kerry Bodine’s book, Outside In: The Power of Putting Customers at the Center of Your Business, helps leaders understand the financial benefits of great customer experiences — and how to deliver them. In 2014, she founded Bodine & Co., a consulting firm that blends human-centered design with AI strategy to help organizations innovate and adapt. She’s a sought-after keynote speaker at conferences and corporate events worldwide, inspiring leaders to see change as an opportunity to deepen the value they provide. Kerry’s insights have been featured in The Wall Street Journal, Harvard Business Review, Fast Company, Forbes, and USA Today. She holds a master’s degree in human-computer interaction from Carnegie Mellon University.

Dan Saffer

Assistant Professor of the Practice at the Human-Computer Interaction Institute at Carnegie Mellon University

Dan Saffer is an Assistant Professor of the Practice at the Human-Computer Interaction Institute at Carnegie Mellon University, a product design leader, and the author of four books: Designing Devices (2011), Designing Gestural Interfaces (2008), Designing for Interaction (2006, 2009) and the best-selling Microinteractions (2013). Since 1995, he's designed devices, apps, websites, wearables, appliances, automotive interiors, services, social networks, and robots. He’s worked at and for such companies as Twitter, Smart Design, Samsung, Jawbone, CNN, Philips, and Microsoft — and was most recently Head of Product Design at Flipboard. He graduated from Carnegie Mellon with a Master’s in Design, Interaction Design.

Course curriculum

Expand each section for a preview of our training content.

    1. Welcome & Course Structure Details

    2. Meet Your Instructors: Kerry Bodine & Dan Saffer

    1. Different AI Models have different data

    2. Where does data come from?

    3. Reference: Where does data come from?

    4. Data Labels & Data Diversity

    5. Module 1 Quiz

    6. Reference: Attributes of AI-ready customer Data

    7. Reference: Why Your Customer Data May Not Be AI-Ready

    8. Reference: Articles/Videos about Data & AI

    9. Optional Viewing: The Artist vs. The Algorithm

    1. Demystifying the AI Hype

    2. AI: Magical but not that smart

    3. 5 Types of AI Failures

    4. Module 2 Quiz

    1. AI Is A New Design Material

    2. Introduction to AI Capabilities

    3. The 8 Great AI Capabilities

    4. Module 3 Quiz

    5. Exercises In This Course: High Level Introduction

    6. Exercise 1.1: Traditional Ideation

    7. Printable Tool: 8 Great Capabilities Cheat Sheet

    8. AI Scavenger Hunt: Spotting AI in the Wild

    1. Where We Are In The Course

    2. Why Traditional Human-Centered Design Processes Fail

    3. AI Innovation Gap

    4. Introduction to Matchmaking

    5. Exercise 1.2: Ideation with Matchmaking

    1. Technical Feasibility & Accuracy (Video)

    2. Intern Island: An Analogy to Assess Concepts

    3. Exercise 2.1: Rapid Evaluation (Intern Island)

    4. How to Simplify Your AI Concepts

    5. Exercise 2.2: Simplifying your concepts

    6. Readings and References: Rapid Evaluation

About this course

  • 54 lessons
  • 1.5 hours of video content
  • 20+ Focused video tutorials
  • 5 Actionable tools and templates
  • Optional add on: live coaching with Kerry

Meet your instructors and learn about their experience with AI.


"The course frameworks balance business impact, user value, and AI feasibility to create well-rounded AI solutions. Highly recommend it!"

Manqian Qian

Product Designer

Erin Eisinger

Founder & CEO

Kerry and Dan delivered. I learned a methodology that mitigates the risks so often inherent in AI projects, delivers meaningful value to organizations, and keeps user needs at the core of my work. Highly recommend.

Dionne

Designer

The frameworks taught were immediately applicable to my work, and Kerry and Dan provided practical tips that directly addressed our concerns. The course struck the perfect balance with weekly content review and interactive sessions that kept our cohort consistently engaged.

Sean

Product Designer

Good strategies and frameworks that are useful for thinking through valuable AI features or products, rather than just following the hype. The course covered practical approaches to identifying where AI can genuinely add value through the capabilities it possesses. Overall, it provided a more thoughtful approach to AI ideas that work.

Flexible options for individuals and teams.

Individuals

Get immediate access — start learning today!
 
 

$ 395

Enroll Today!
  • One time payment.
  • Watch 24/7. Anywhere. Anytime
  • Instant access to the full course
  • Access to templates and tools
  • Certificate of completion

Teams & Organizations

Equip your team with shared frameworks for evaluating and developing AI initiatives.

Inquire

Contact Us
  • Team enrollment and seat management
  • Admin dashboard and reporting
  • Progress tracking across learners
  • Shared frameworks for evaluating AI initiatives

For your security, all orders are processed on a secured server.

Prefer to start with a specific AI skill?

Start with a focused mini course. Each mini course targets a critical step in building successful AI solutions — from understanding how AI works to generating ideas to identifying risks before you launch.

AI Foundations

No prior knowledge needed.

After this course, you'll be able to:

  • Describe the types of AI models, what data is required for each, and where that data comes from
  • Recognize what makes data AI-ready
  • Summarize the five types of AI failures
  • Use what AI can do (the 8 great capabilities) in your next AI task or project



AI Concept Ideation

Before taking this course, you should have general knowledge of:

  1. The types of AI models
  2. The capabilities of AI (What it can and cannot do)


After this course, you'll be able to:

  • Explain why the traditional human-centered design process alone fails for AI
  • Generate AI concepts using the capability matchmaking technique
  • Rapidly evaluate your AI concepts
  • Simplify your AI concepts to make them more feasible
  • Identify the value your AI concept brings to your users and your business


AI Potential Harms and Consequence Scanning

Before taking this course, you should have general knowledge of:

  1. The capabilities of AI (What it can and cannot do)
  2. How to generate feasible AI concepts for your users/business



After this course, you'll be able to:

  • Identify the types of AI errors and harms
  • Recognize the five common AI harm patterns
  • Use the consequence scanning framework to think through an AI product's positive impact and identify any negative impacts that might be prevented

Frequently Asked Questions

If you have additional questions or would like to enroll your team — contact us here! 

No! This is for those who want to understand how AI can create value in their organization. We focus on practical frameworks and decision-making, not coding or technical implementation.

This course is ideal for those responsible for product strategy, innovation, customer experience, design, and digital transformation. Many participants come from product, UX, research, and leadership roles.

Most AI training focuses on the technology itself. This course focuses on how organizations actually decide what AI to build and how to design AI experiences responsibly. 

You will learn research-backed frameworks and practical methods that you and/or your team can apply immediately.

We cover practical approaches for identifying ethical, operational, and user risks when designing AI-powered products and services. The goal is to help teams create AI solutions that support users, align with business goals, and avoid the kinds of failures documented in the AI Incident Database.

Yes! Many organizations bring teams so they can build a shared understanding of how AI fits into their work. If you take the course as a team, you’ll leave with:

  • A shared understanding of AI capabilities and limitations

  • Frameworks for identifying and evaluating AI opportunities

  • A prioritized set of AI concepts relevant to your organization

  • Practical approaches for designing AI-driven interfaces

Many organizations bring cross-functional teams so they can establish a shared approach to identifying and designing AI initiatives together.