I Built an AI Adoption Framework Using the Technology I Was Afraid Of

I Built an AI Adoption Framework Using the Technology I Was Afraid Of

I did not come to AI as an early adopter. 

I came to it the way a lot of experienced professionals did: skeptical, cautious, and not entirely sure it belonged in the work I had spent my career building. 

I am an Organizational Change Management (OCM) practitioner. My work is about how people experience change, not about the technology driving it. 

When AI started showing up in every conversation, my first instinct was not curiosity. It was caution.

That caution had roots. 

I spent years as the OCM lead on cybersecurity projects. I am not a cybersecurity technologist and I would never position myself as one. But when you spend enough time in environments where people think every day about: 

  • what you give information to

  • what you allow into your systems

  • who might be on the other end

that thinking becomes part of how you evaluate everything. 

I did not need to witness a breach to understand why guardrails matter. 

I absorbed a posture: 

Pay attention to trust access and exposure before you pay attention to capability

So when AI productivity tools started arriving on people’s desktops, I was not the person in the room saying “let’s try it.” 

I was the person noticing the questions that were not being asked. 

Not because I was looking for reasons to say no, but because those questions felt important and nobody seemed to be slowing down long enough to ask them.

The shift was not a single moment. There was no dramatic conversion. It was a gradual recognition that the caution I brought to this work was not a limitation. It was exactly what the work needed.

Every organization adopting AI faces the same tension: 

  • move fast enough to capture value

  • move carefully enough to do it responsibly. 

The OCM profession is built for that tension. 

And the questions I had been carrying from my cybersecurity work, questions about trust, about what deserves human review, about where guardrails are non-negotiable, those were not obstacles to AI adoption. They were the foundation of doing it well.

I did not stop being cautious. I started building with that caution as a design principle.

Before I built anything, I prepared:

  • Months of reading

  • Attending Prosci’s human-centered AI workshops where I learned Prosci’s AI Integration Framework

  • Earning the Applied AI Change Management Certification from the Change Management Review. 

I was among the first to complete that certification, in the second cohort of approximately 25. I waited for the second cohort deliberately. Let someone else test it first. That felt right for the posture I was carrying.

I started experimenting with Gemini as a research assistant before I committed to building. 

When I was ready, I began working with Claude. 

What I built is a human-centered AI adoption methodology grounded in OCM principles designed for organizations navigating this specific kind of change

I could not have built it without AI. That is the honest truth, and I think it matters to say out loud. 

I brought the: 

  • OCM expertise

  • practitioner judgment,

  • cybersecurity-informed instinct about where the risks live 

I knew when: 

  • the output looked right but had errors, missed a point, or went down the wrong path

  • a design choice would fall apart

  • to push back on an answer that missed how organizations actually work  

AI brought: 

  • pattern recognition

  • research synthesis

  • an iteration speed I could not have matched on my own

The methodology is not something AI generated for me. 

It is something we built together, with me making every design decision and AI helping me see connections, test ideas, and move faster than I could have working solo. 

Neither of us could have done it alone. 

I did not come out the other side of this as an AI evangelist. I came out as a practitioner who: 

  • builds with AI

  • brings a critical eye to every decision about how it gets used

  • helps organizations navigate the same journey I went through

Responsible use is not something I layer on at the end of an engagement. It is part of how I work from the beginning. 

  • What data is exposed? 

  • What outputs need human review? 

  • What guardrails are non-negotiable? 

Those questions come first, not after something goes wrong.

The frameworks I studied along the way, Prosci’s AI Integration Framework and the SAFE-AI Pathway by the Change Management Review, shaped how I think about this work. 

But the methodology I built is mine. It reflects what I learned, what I tested, and what I believe organizations actually need when they are trying to make AI adoption real for the people doing the work.

I wrote this because the question I get most often is not about the methodology. It is about me. 

People want to know who I am before they evaluate what I offer. Fair enough. Now you know. 

I am an OCM practitioner who brought her caution, her preparation, and her judgment to AI, and built something with it. The caution did not go away. It became the work.

Let’s talk about what AI adoption really takes.   ➤ Contact me today

Laurie Feuerstein