Addressing 'We're Not Ready': Change Management Over Technical Readiness

Overview

“We’re just not ready for Copilot yet. Maybe next year, once we get a few things in order.” This is the most common objection and the most dangerous—because it sounds reasonable but often masks fear of change.

Here’s the uncomfortable truth: If you wait until you feel “ready,” you’ll never deploy Copilot. Readiness isn’t a state you achieve through planning—it’s a capability you build through experience.

This video unpacks what “not ready” really means, examines the cost of waiting, and provides a pilot-based framework for building readiness through action rather than endless preparation.

What You’ll Learn

• What “not ready” usually means (and what it’s really saying)
• The hidden cost of waiting for perfect conditions
• Pilot-based readiness framework for learning by doing
• Minimum viable readiness to start

Script

The Perpetual ‘Not Ready’

The objection: “We’re just not ready for Copilot yet. Maybe next year, once we get a few things in order—clean up our data, finish the security review, complete the reorganization, wrap up the other IT projects.”

This sounds reasonable. Government organizations should be thoughtful about technology adoption. You shouldn’t rush into deployments without proper planning.

But here’s what makes this objection dangerous: There will always be something not quite finished. There will always be higher priorities. There will always be a reason to wait “just a little longer.”

If you wait until you feel “ready,” you’ll never deploy Copilot. Readiness isn’t a state you achieve through planning—it’s a capability you build through experience.

Let’s unpack what “not ready” really means and how to move forward anyway.

What ‘Not Ready’ Usually Means

When leaders say “not ready,” they typically mean one of four things, though they may not articulate it clearly.

First: “We don’t understand it well enough.” This is actually valid—you should understand what you’re deploying. But understanding comes from doing, not just reading. A 90-day pilot teaches you more than six months of research.

Second: “Our users won’t adopt it.” This is fear of change resistance, which is real. But research shows AI tools have much higher organic adoption than traditional enterprise software because users actually want them. The adoption challenge is usually scaling fast enough to meet demand, not forcing reluctant users to try it.

Third: “We have technical prerequisites to address.” Usually data governance, security reviews, or infrastructure concerns. But in most cases, these aren’t actually blockers—they’re ongoing work that happens in parallel with pilot deployment.

Fourth, and most common: “We have higher priorities right now.” This is the killer. There will ALWAYS be higher priorities. Every organization has a backlog of important initiatives. If Copilot waits for a clear calendar, it will never happen.

The question isn’t whether you’re ready in all these dimensions. The question is whether the benefits of starting outweigh the risks of waiting—and whether you can manage the risks through thoughtful pilot design.

The Cost of Waiting

Let’s talk about what happens while you’re “getting ready.”

Your employees continue spending 60% of their time on work about work—searching for information, coordinating meetings, formatting documents. That’s productivity value you’re leaving on the table every day you wait.

Your peer agencies and industry partners are already using AI tools. The capability gap grows every quarter. In five years, when you’re finally “ready,” the organizations that started now will be five years ahead in AI maturity and organizational learning.

Top talent—especially younger employees—increasingly expects modern tools. When you tell a talented analyst “We’re not ready for AI,” they hear “We’re not keeping up with the times.” That affects recruitment and retention.

And here’s the paradox: The things you’re waiting to fix—data governance, change management capability, user readiness—actually get easier with experience. You learn what matters by deploying, not by planning.

The security concerns you think need resolution before starting? You’ll understand them better after a 50-person pilot than after six months of theoretical risk assessment.

The data governance work you think is a prerequisite? You’ll identify what actually matters by seeing how users work with Copilot, not by trying to perfect information architecture in the abstract.

Waiting doesn’t reduce risk. It delays learning and foregoes value.

The Pilot-Based Readiness Framework

So what’s the practical approach? Build readiness through staged pilots, not big-bang deployments.

Phase one: 30-50 users, high-value roles, volunteers only. Duration: 90 days. Goal: Prove value and learn what works.

During the pilot, you’re building three critical capabilities: User champions who can evangelize to peers and provide peer-to-peer support. Concrete use case examples that demonstrate ROI and provide templates for broader deployment. Organizational know-how about what works in your specific environment—because every organization is different.

Phase two: Expand to 200-500 users based on pilot lessons. This is where you refine your change management approach, identify department-specific use cases, and scale your support model.

Phase three: Enterprise deployment with proven playbook, trained champions network, and documented success stories.

Each phase builds readiness for the next. You’re never “ready” upfront—you become ready by doing. This is how successful organizations adopt any significant new capability—not through perfect planning, but through thoughtful experimentation and rapid iteration.

Minimum Viable Readiness

What’s the absolute minimum readiness required to start a pilot? Three things.

One: Basic understanding of what Copilot is and how it respects permissions. You need to explain it accurately to pilot users so they have appropriate expectations. This requires maybe 4 hours of research and a conversation with your Microsoft account team.

Two: Confirmation that your Microsoft 365 environment meets licensing requirements (E3 or E5, appropriate cloud environment for government). This is a yes/no question you can answer in 30 minutes.

Three: Executive sponsorship—someone at senior level willing to champion the pilot, remove barriers, and make decisions when issues arise.

That’s it. You don’t need perfect data governance before starting. You don’t need comprehensive training programs. You don’t need detailed change management plans.

Those things get built during the pilot, informed by real usage patterns and actual user feedback. You’re not launching enterprise-wide deployment—you’re running a controlled experiment to learn what works.

The organizations that get stuck in “not ready” purgatory are trying to solve every problem before starting. The organizations that succeed are starting small, learning fast, and scaling based on evidence.

Start Before You’re Ready

Bottom line: The organizations succeeding with Copilot are the ones who started before they felt ready.

They deployed a small pilot, learned what worked in their specific context, discovered that some concerns were overblown while others were legitimate, built champions through experience, and scaled based on demonstrated value.

The organizations still planning, still researching, still waiting for the right moment—they’re falling behind, not reducing risk.

Deploy a pilot. Make it small enough that failure is manageable. Make it long enough to get past novelty phase (90 days minimum). Measure rigorously. Learn fast. Iterate based on feedback.

Readiness is built through experience, not achieved through planning. Start now.

Sources & References

Internal Knowledge Base

• Frontier Agency Framework - Government-specific change management and pilot methodology
• Copilot Adoption Best Practices - Pilot design, phased deployment approaches

External Resources

• Copilot Research & Data - Adoption patterns and success factors