Hello, everyone—Jeremy Nurse here, co-founder with a passion for helping organizations navigate digital transformation. In the fast-paced world of AI, tools like Microsoft 365 Copilot are generating a lot of excitement, promising to automate routine tasks, enhance decision-making, and boost overall efficiency. However, as I've seen through years of working with emerging technologies, AI's effectiveness depends heavily on the underlying infrastructure. If your Microsoft 365 environment—often referred to as your tenant—isn't properly prepared, even the most advanced AI features can underperform or introduce unnecessary complications.
This post dives into the importance of conducting an AI readiness check, essentially a thorough assessment of your tenant's health, to ensure you're positioned for success. We'll cover the potential pitfalls of skipping this step, what a readiness check entails, and practical self-audit tips to get started, all supported by recent data and insights.
The AI Promise—and the Hidden Hurdle
Microsoft 365 Copilot integrates seamlessly into familiar applications such as Word, Excel, Teams, and SharePoint, where it can analyze data, generate content, and provide real-time insights. Research indicates that organizations leveraging AI effectively can see significant productivity improvements—for instance, the 2025 Microsoft Work Trend Index reports that companies with high AI readiness experience up to 3.2 times greater productivity gains compared to those with lower readiness. Yet, Copilot's performance is directly tied to the quality of your Microsoft 365 tenant, which encompasses configurations, user permissions, data structures, and adoption levels. When the tenant is cluttered with outdated files, inconsistent policies, or underutilized features, AI tools struggle to deliver accurate or efficient results.
A Forrester Total Economic Impact study from 2022 highlights that optimizing Microsoft 365 can yield an ROI of 205%, with potential savings from reduced hardware, software, and maintenance costs, alongside time efficiencies like 1.5 hours per week per user in collaboration tasks. Adding AI amplifies these benefits, but only if the foundation is solid. Without an initial readiness check, you're essentially deploying advanced technology on an unoptimized base, which can limit returns and increase frustration.
What’s at Stake?
Jumping into AI without assessing your tenant's readiness can lead to suboptimal outcomes. For example, a Forrester 2024 study on Microsoft 365 Copilot notes that organizations can reduce operating costs and enhance efficiency, but these gains are contingent on proper setup. Gartner forecasts that by 2026, more than 80% of enterprises will have adopted generative AI technologies or applications. Those who prepare inadequately may face delays, higher costs, or security issues. Here are key risks, along with self-audit tips to evaluate them:
Data Disconnects: Copilot relies on accessing structured data across emails, documents, and chats. If SharePoint sites are disorganized or permissions are overly broad, it may retrieve irrelevant or incomplete information, leading to errors.
- Self-Audit Questions: How much digital clutter exists, such as duplicate files or inactive channels? Are permissions set so users only access necessary data?
- Quick Action Steps: Conduct a content inventory using Microsoft 365 admin tools to identify and archive files older than two years. Implement sensitivity labels via Microsoft Purview to classify and protect data automatically.
License Waste: Unused or overlapping licenses inflate expenses while missing AI prerequisites, like specific Microsoft 365 plans required for Copilot features.
- Self-Audit Questions: Are all licenses actively utilized? Do they align with AI capabilities, such as those enabling advanced data processing?
- Quick Action Steps: Review licensing reports in the Microsoft 365 admin center to spot underused subscriptions and reallocate them for better coverage.
Adoption Lag: Low engagement with core tools like Teams or OneDrive can make Copilot feel disconnected, reducing its utility.
- Self-Audit Questions: What are current usage patterns across departments? On a scale of 1-10, how comfortable are users with existing Microsoft 365 features?
- Quick Action Steps: Survey teams to gauge adoption levels and introduce basic training sessions on high-impact tools to build familiarity before AI rollout.
Compliance Risks: AI processes potentially sensitive information, so weak governance can expose organizations to breaches or regulatory violations.
- Self-Audit Questions: Are data loss prevention (DLP) policies in place? How effectively are sensitivity labels applied to protect confidential data?
- Quick Action Steps: Enable DLP rules in Purview to monitor and block sensitive data in AI interactions. Form a cross-functional team to review compliance settings quarterly.
These risks aren't hypothetical—skipping preparation can stall adoption and erode trust in AI tools.
The AI Readiness Check: Your AI Prep Kit
An AI readiness check is a systematic evaluation of your tenant across technology, processes, and people, ensuring alignment with AI demands. It typically results in a report highlighting strengths, gaps, and a prioritized roadmap. Here's a breakdown of core areas, with integrated self-audit guidance:
SharePoint, Teams, and OneDrive Health
These platforms form the data backbone for Copilot. Inefficiencies like redundant sites or sprawl can hinder AI's ability to retrieve accurate information.
- Self-Audit Questions: Are Teams channels focused and active? Is content in OneDrive siloed when it could be collaborative in SharePoint?
- Quick Action Steps: Scan for inactive sites using admin tools and consolidate them. Encourage best practices for organizing content to improve AI accessibility.
Microsoft 365 Licensing
Ensuring licenses match needs prevents waste and unlocks AI features.
- Self-Audit Questions: What percentage of features are unused? Are Copilot prerequisites met?
- Quick Action Steps: Audit via the admin center and adjust assignments to optimize costs and capabilities.
Tenant Governance
Structured processes keep data organized and secure, which is essential for AI.
- Self-Audit Questions: Is there routine monitoring for content lifecycle? Are DLP and governance policies enforced?
- Quick Action Steps: Set up automated retention policies in Purview and review them regularly to maintain a clean environment.
Security and Compliance
AI requires robust protections to handle data safely.
- Self-Audit Questions: How are file-sharing settings configured? Are sensitivity labels consistently used?
- Quick Action Steps: Assess Purview tools for information protection and update sensitive information types as needed.
People and Processes
Human factors determine long-term success.
- Self-Audit Questions: What's the team's AI literacy level? Are change management processes in place?
- Quick Action Steps: Run a skills survey and plan workshops on AI basics. Identify champions to promote adoption.
Optimization Fuels AI Success
Empirical data underscores the value: A Forrester study shows optimized Microsoft 365 environments boost ROI by 205%. An IBM report indicates AI can reduce customer service costs by up to 30%, with similar efficiencies possible in knowledge work via Copilot. As of 2025, Microsoft 365 has over 400 million commercial users, reflecting widespread adoption. Preparation through a readiness check maximizes these benefits.
Real-World Wins: What Readiness Unlocks
Consider a scenario with 500 users: Without a check, Copilot adoption might linger at 20% due to data issues and lack of training. With preparation—cleaning up sites, optimizing licenses, and building skills—adoption can reach 70%, yielding substantial productivity lifts. In compliance-sensitive settings, addressing Purview gaps prevents risks while enabling confident AI use.
Why Now? The AI Clock Is Ticking
With features like SharePoint agents now generally available as of 2025, AI integration is accelerating. Delaying a readiness check risks compounded issues, while acting now—through self-audits or deeper evaluations—positions you for seamless gains. It's a proactive step toward turning AI from hype into tangible value.