Challenge Accepted series

June 3rd, 2026 | Hosted by  Klil Nevo: The Learning Table & Juno Journey
Expert: Guy Laufer

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ICYMI: Designing Career Pathways People Actually Use

AI adoption is at the top of every organization's priority list.

Yet despite the excitement, many AI initiatives struggle to create meaningful change. Teams receive access to new tools, pilot programs are launched, and training sessions are delivered—but real adoption often falls short of expectations.

In our latest Challenge Accepted session, Guy Laufer shared a different perspective.

Drawing on more than 15 years of experience in learning, enablement, product development, and digital transformation, Guy explored how Design Thinking can help organizations move beyond tool deployment and create AI initiatives that employees actually embrace and use.

The central message was simple:

Successful AI implementation isn't a technology challenge. It's a human-centered design challenge.

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Why Traditional AI Rollouts Often Fail

Many organizations approach AI implementation by starting with the solution.

They select a tool, purchase licenses, build training programs, and then ask employees to adapt.

The problem?

Employees don't experience work through technology. They experience work through challenges, workflows, goals, and daily realities.

When organizations begin with the tool instead of the user, adoption becomes difficult, engagement remains low, and business impact is limited.

Design Thinking flips that process.

Instead of asking:

"Which AI tool should we deploy?"

Organizations should start by asking:

"What problems are our people trying to solve?"

The Design Thinking Framework

Guy introduced a practical framework built around four stages:

1. Discover

Before building anything, understand the environment.

This means gathering data, interviewing employees, understanding business goals, identifying challenges, and learning how people actually work.

Rather than making assumptions, organizations should spend time understanding users, stakeholders, workflows, and business priorities.

2. Define

Once data is collected, the next step is identifying the real challenge.

What are the barriers?

What outcomes matter most?

Where are employees struggling?

The goal is to move from observations to a clear problem statement that everyone can align around.

3. Design

Only after understanding the problem should organizations begin designing solutions.

This phase includes ideation, experimentation, and creating experiences that employees can immediately connect with and apply in their daily work.

Importantly, design isn't about making something look attractive.

It's about creating something useful, relevant, and intuitive.

4. Deliver

Once the solution is ready, it's time to launch.

But delivery is more than deployment.

It includes communication, measurement, stakeholder alignment, and ongoing support.

Most importantly, organizations must continue listening and learning after launch.

AI Adoption Requires Relevance

One of the most practical insights from the session focused on AI enablement.

Guy shared that different employee groups require different AI experiences.

Engineers, for example, often need specialized AI tools that align with coding workflows.

Other functions may benefit more from general-purpose AI assistants.

The key is not teaching AI in the abstract.

It's helping employees understand how AI improves their specific work.

Instead of saying:

"Here's our new AI platform."

Organizations should demonstrate:

• How AI helps an accountant complete recurring tasks.
• How AI supports a marketer creating campaigns.
• How AI assists a customer success manager preparing for meetings.
• How AI improves an engineer's workflow.

The closer the learning experience is to real work, the greater the adoption.

Prototype Before You Scale

One of the most powerful principles discussed was the value of prototyping.

Before investing heavily in a new initiative, test the concept.

Create a simple version.

Gather feedback.

Refine.

Then scale.

Guy shared examples from large-scale transformation programs where early prototypes helped secure stakeholder buy-in, validate assumptions, and improve the final solution before major investments were made.

In a world where AI evolves weekly, the ability to test and iterate quickly is becoming a critical capability for L&D, HR, and business leaders.

Change Management Still Matters

Technology alone doesn't create transformation.

People do.

When discussing AI implementation, Guy emphasized the importance of creating buy-in across the organization.

Rather than simply announcing a change, leaders should involve stakeholders early, demonstrate value, and create opportunities for people to understand why the change matters.

This is especially true for leadership teams.

If senior leaders don't understand the opportunity, it's difficult for the rest of the organization to embrace it.

Successful change happens when people feel included in the journey—not when change is simply imposed upon them.

The Real Opportunity

Perhaps the biggest takeaway from the session was that AI implementation is not fundamentally about AI.

It's about understanding people.

The organizations that succeed won't necessarily be the ones with access to the newest tools.

They'll be the ones that deeply understand their employees, design solutions around real needs, measure impact, gather feedback, and continuously improve.

Design Thinking provides a framework for doing exactly that.

As AI continues to reshape how work gets done, human-centered design may become one of the most valuable skills organizations can develop.

About the Speaker

Guy Laufer is a learning, enablement, and digital transformation leader with more than 15 years of experience helping organizations drive growth through innovative learning experiences, product enablement, design thinking, and user-centered solutions. Throughout his career, he has led global transformation initiatives, built scalable learning programs, and helped organizations navigate change by putting people at the center of the experience.