Stop Rolling Out AI. Start Onboarding It.

Build trust, accelerate learning, and turn technology into a true teammate.

By Dr. Eve Kedar, guest blogger

The Ways We Work

Volume 1, Number 9

“We welcome technology like a system update, not like a teammate. And in skipping the people, we miss the point.”

Opening Reflection

Every day brings another headline about artificial intelligence reshaping work. Yet one number from MIT’s GenAI Divide report stands out. Ninety-five percent of enterprise AI implementations fail.

That number becomes even more striking when we remember that organizations with strong onboarding programs improve retention by 82% and productivity by 70%.

After 20 years of designing onboarding programs that help professionals succeed, I see the connection clearly. Technology adoption and employee onboarding are the same challenge on different days.

When companies introduce AI, they often focus on systems and software instead of people. They skip the human side of learning, trusting, and belonging — the same elements that determine whether a new hire succeeds.

AI adoption isn’t a rollout. It’s a relationship. And relationships take time, empathy, and design.

From Anxiety to Amazement

When I work with teams introducing AI, the emotional arc is predictable. It begins with anxiety as people question what the change means for their jobs. That turns into fear as they wonder if technology will replace them. Handled well, something transformative happens. Fear gives way to amazement as people see that AI can amplify their work rather than threaten it.

It’s the same pattern new employees experience: from imposter syndrome to confidence, from confusion to competence. The difference is that we prepare people for that journey, but not our technology.

Successful adoption requires the same playbook that helps humans thrive: structure, empathy, and shared purpose.

The MIT Reality Check

MIT’s GenAI Divide report helps explain why so many companies fall short. Startups are racing ahead, some scaling from zero to $20 million in revenue using AI, while large enterprises remain stuck in “pilot purgatory”.

The issue isn’t model quality or data size. It’s the learning gap. Established companies fall into three traps that keep them from scaling success.

The Zero-Sum Trap

Employees see AI as a competitor rather than a collaborator. When automation is framed as replacement, resistance follows.

The Integration Illusion

Organizations add tools like ChatGPT without adapting workflows or expectations. It’s like hiring someone brilliant and never explaining how the company works.

The Training Desert

More than half of corporate AI budgets fund sales and marketing tools, yet MIT found the highest ROI in back-office automation. The people who most need AI support rarely get training.

These gaps create distrust. And without trust, no transformation can last.

Practical Playbook: The SEID Framework

To close the learning gap, we can borrow from proven human onboarding models.

In my early work on sales enablement, I developed the SEID Framework — Specific, Engaging, Interactive, Designed. It applies directly to AI adoption.

Specific

Start with one team, one process, and one clear win. Focus builds credibility.

Engaging

Make success visible. Share peer stories instead of executive memos. Let employees show what AI helped them achieve.

Interactive

Create spaces to experiment safely. Host AI play sessions where mistakes are expected and learning is celebrated.

Designed

Support different learning styles. Offer short videos, workshops, and examples so everyone can build confidence at their own pace.

When leaders apply SEID, AI becomes part of the culture, not another tool collecting dust on the shelf.

The Human Path Forward

MIT’s research also revealed that companies partnering with experienced AI vendors succeed 67% of the time, while internal builds succeed only 33% of the time.

The reason is simple: partnership mirrors mentorship. People learn faster and retain more when they have guidance, feedback, and community.

But the most important driver of adoption isn’t the technology team. It’s the line manager. These are the professionals who normalize new behavior, reward curiosity, and make experimentation safe.

When managers model confidence and curiosity, entire teams follow. Culture shifts from compliance to creativity. That’s where the real ROI begins.

Final Frame

Imagine onboarding AI as you would a new teammate.

Weeks 1–2: Build belonging. Talk openly about what AI can and can’t do. Reassure teams that this technology exists to support, not replace. 

Month 1: Focus on small, high-value wins that make daily work easier. 

Month 2: Expand capabilities and show how AI strengthens creativity, speed, and judgment. 

Month 3: Embed AI into daily workflows until it feels natural, not novel.

The companies that succeed won’t be the ones with the flashiest algorithms. They’ll be the ones that onboard AI with empathy and intention — helping their people move from anxiety to amazement and from pilot to progress.

An Invitation

👉 From Eve: Learn more about my work at EveKedar.com and explore how human-centered frameworks like SEID help organizations navigate change, build trust, and turn AI adoption into measurable growth.

👉 From Mary: At Meerkat, we’re sharing forward-looking perspectives through The Ways We Work series. Join our community to see how professionals across industries are adapting to AI’s impact on their work and relationships.

Follow our journey at trymeerkat.ai and connect with us on LinkedIn to stay up to date with new insights, stories, and resources.

Dr. Eve Kedar is a leading expert in sales enablement, community building, and AI integration with more than 15 years of experience transforming teams at Apple, Gainsight, and Seagate. She is the author of Build a Kicka$$ SalesTeam and Build a Kicka$$ Online Community. She helps organizations bridge the human side of technological transformation through inclusive, engaging change management.