Why AI becoming a value-driver or a chaos agent hinges on your strategic alignment
Like other Microsoft tools that came before it, Copilot could well revolutionize the workplace. Organizations must treat AI rollout differently from starting with Word, and they need to address many factors before diving in. Having technical access to Copilot doesn’t guarantee you’ll see business value.
So if you’re pushing to launch Copilot across departments without clear answers to some common but critical challenges, get ready for a bumpy ride. From wasted investments to long-term friction and security blind spots, the consequences of rushing your AI entry are real.
Here are three clear signs your team may not be ready – yet.
1. You don’t know how to measure (or can’t see) what AI success looks like
AI initiatives tend to spark excitement across the org chart. But if every department is pursuing Copilot for a different reason or chasing vague notions of “value,” it’s nearly impossible to measure success or course-correct when needed.
Business units should actively explore use cases with the clear understanding that they must ground those efforts in something more concrete than curiosity. IT should focus on enablement, Legal should address risk, and Finance should use Copilot to improve reporting—all valid goals. But those teams must also align around a shared framework that sets priorities, ensures accountability, and tracks outcomes.
According to a March 2025 Forrester report, Copilot has shown strong ROI potential – up to 116% for enterprises. But those returns require you to have well-defined goals and workflows in place. Pushing forward without these can leave you struggling to connect usage to business impact.
What to listen for:
- “We just want to see what it can do.”
- “Everyone else is doing it. We need to keep up.”
- “We’ll figure it out after deployment.”
Without a common understanding of what AI value actually means for your org – much less how to measure its ROI – Copilot is just another tool. And that’s a recipe for inconsistency.
2. You assume your data governance doesn’t have any hidden gaps

Generative AI is trained to be helpful. But it doesn’t inherently understand context, hierarchy, or confidentiality – especially if your Microsoft 365 environment doesn’t clearly enforce those boundaries.
By design, Copilot will surface any content a user already has access to. That access is based on existing permission models, which could include things like legacy permissions, overly broad SharePoint rights, and shared inboxes that haven’t been reviewed in years. Because of this, any hidden governance flaws will be exposed, not corrected.
For a timely cautionary tale, look at Microsoft’s own now-infamous Recall feature. An AI-driven screenshot history tool for Windows 11, Recall sparked intense backlash when it was first released when critics raised concerns over privacy risks and lack of visibility into what data might be stored or surfaced. While Microsoft paused and re-released Recall with added safeguards, the controversy highlighted a broader truth: AI will surface what’s already there, whether or not it should.
What to listen for:
- “I thought that folder was private …”
- “Who gave access to that proposal?”
- “Let’s not turn it on for Legal just yet.”
Copilot amplifies your data environment. If that environment is disorganized or poorly governed, the impact on your business can be immediate and unintentional.
3. Your employees are experimenting with AI without any structured support
Empowered users are a strength – until their enthusiasm outpaces enablement. If team members are exploring Copilot on their own without any guidance on responsible use, performance expectations, or data handling, your org may be heading toward AI sprawl.
A few early adopters might start sharing prompts and productivity tips in Slack or Teams, but those informal channels can’t replace a structured rollout. Training, policies, and internal champions all help shape how Copilot contributes to actual business outcomes, things that add up to more than shortcuts and handy tricks.
To help orgs help themselves, Microsoft recently launched its Copilot Skilling Center. While this can be an invaluable resource, it can’t replace internal training and policies that are built around your specific workflows and risk posture.
Microsoft has also added Copilot usage dashboards for IT admins to track engagement across apps, users, and departments. But even with this added visibility, it’s up to you to define what success looks like and help employees reach it.
What to listen for:
- “We found a cool prompt on Reddit.”
- “It works great … sometimes.”
- “No idea if we’re using it ‘right,’ but it’s fun.”
We get it. You want to be in the position of fostering innovation, as opposed to policing it. But to get there, you first have to invest time and effort into training employees and have a structured plan for adoption. For a tool as powerful and far-reaching as Copilot, think of these prerequisites as non-negotiable.
Bottom line: Readiness is a leadership issue. Start there.
Getting Copilot to work (from a technical point of view) is relatively easy. Making it work strategically is a different kind of challenge – one that requires you to rally your departments around clear, common goals built on a strong foundation of governance and change management.
According to a January 2025 McKinsey survey, 92% of companies plan to increase their AI investments over the next three years, but only 1% of leaders call their companies “mature” in their development efforts (“meaning that AI is fully integrated into workflows and drives substantial business outcomes”). The rush is definitely on, but moving fast without the right preparation will only multiply the risks to your business.
So ask the hard questions. Build internal alignment. And lead your roll out with intention.
Right now, the door to Copilot is wide open. If you’re not sure where your org stands, start a readiness conversation. Begin with IT, and include every stakeholder who expects Copilot to make a meaningful impact.