Move Fast, But Not Yet: Why readiness is the fastest path to AI adoption
Move Fast, But Not Yet
Why readiness is the fastest path to AI adoption
Every organization wants to move fast with AI. The pressure is real:
competitors are adopting
boards are asking questions
the technology is evolving weekly
The instinct to jump straight to implementation is understandable.
It is also one of the most predictable reasons AI adoption stalls.
The organizations that succeed with AI do something counterintuitive first
They slow down.
Not to delay, but to build the foundation that makes speed possible later.
And they are not guessing about this. Two of the most established frameworks in organizational change and project management say the same thing.
Prosci says: Prepare before you manage
Prosci’s 3-Phase Process, the backbone of structured change management, begins with “Prepare Approach.”
Before any implementation work starts, this phase requires:
defining success
assessing organizational readiness for change
developing a strategy aligned with what the assessment reveals
This is not optional preparation.
It is the phase that determines whether the change management work that follows has any chance of landing. Skip it, and you are managing change without knowing what you are changing from.
AI Applications
When applied to AI adoption specifically, Prosci's study, Keys to Unlocking AI Adoption, surveyed more than 1,100 participants and found that the conditions in place before implementation:
leadership engagement
transparency
experimentation support
organizational knowledge
are what separate organizations that succeed from those that stall.
The Project Management Institute (PMI) says: Initiate before you execute
The PMI framework mirrors the same logic from a different discipline. The PMI initiation phase exists to:
pull together high-level information
identify stakeholders
align expectations with purpose
establish the business case before execution begins
Project managers know intuitively that skipping initiation creates problems that are exponentially more expensive to fix later.
The same principle applies to AI adoption, except the stakes are higher because AI changes how people work, not just which system they use.
What this looks like in practice
For AI adoption, the data-gathering phase at L Feuerstein Consulting answers three foundational questions before implementation planning begins. These three questions are where the readiness work starts.
1. Where is old thinking quietly slowing you down?
AI adoption requires different approaches from previous technology transformations. A facilitated diagnostic surfaces where the organization is still applying old playbooks and where that gap is creating risk.
2. What conditions are in place to support successful adoption?
Evaluating where the organization stands against those conditions, before investing in implementation, produces a prioritized map of what to strengthen and where to focus first.
3. How will you know it is working?
Measurement is foundational, not an afterthought. A structured conversation about what success looks like and what to track establishes the frame that makes progress visible and course correction possible.
These are not theoretical exercises.
At L Feuerstein Consulting, each of these questions is answered through facilitated tools and structured conversations grounded in research.
Prevention, not remediation
The executive question is always: why invest time in readiness when we could be implementing?
The answer is simple:
Done before implementation, this work is prevention.
Done after adoption stalls, it is remediation.
Prevention is faster, less expensive, and preserves the organizational trust that remediation often damages.
Organizations that skip the readiness phase do not skip the work.
They just do it later, under pressure, after the problems the assessment would have surfaced have already become obstacles.
The path forward
AI adoption is a human transformation.
As human-centered AI research consistently reinforces: the technology handles the math; your people handle the meaning.
Starting with readiness is not a delay. It is the foundation everything after it depends on.
Let’s talk about what AI adoption really takes. Contact Laurie Today