Sharing links nobody revoked
"Anyone with the link" shares created during a deadline years ago, still live, still open.
Finding them no longer needs the link — a prompt is enough.
The difference between AI success and AI failure isn't the technology—it's the AI readiness of your organization.
Trusted by Leading Organizations
Three classes account for most of what we find — and all three are invisible until someone looks.
"Anyone with the link" shares created during a deadline years ago, still live, still open.
Contractors, auditors and partners whose project ended but whose access didn't.
Salary records, PII and financials carrying no sensitivity label at all.
Six Microsoft 365 workloads — plus the pillar almost every readiness assessment leaves out.
Guest users, ownerless teams, private channel exposure
Anonymous links, broken inheritance, "everyone" shares
External shares, chat files, departed-user drives
Mail forwarding, inbox rules, full-access delegates
Admins without MFA, dormant guests, Conditional Access
Unlabelled files, DLP gaps, audit log completeness
Licence usage against assigned seats, role fit, sponsorship and enablement gaps. A tenant can be perfectly secure and still waste every seat.
Five questions, one per pillar. Your score and profile appear on screen — we don't ask for your email to release it.
Scripts and scanning tools both produce findings. Neither closes them — and that gap is where most readiness engagements quietly end.
Read-only access granted to the admin centres, scope confirmed in writing.
Full permission and exposure scan across six workloads, plus licence usage.
Findings scored across five pillars, each fix estimated for effort and cost.
Your score, weakest pillar, deploy recommendation and what it costs to move up.
Remediation runs through our AI governance service. If you're already ready and the question is what to build next, that's the AI strategy service.
An AI Readiness Assessment evaluates whether your organization has the people, processes, data, technology, and governance needed to adopt AI successfully. It identifies gaps that could increase risk, delay implementation, or limit the value of your AI investments. A comprehensive assessment typically reviews data quality, security, governance, infrastructure, business processes, and organizational readiness before creating a prioritized roadmap for successful AI adoption.
AI Readiness measures how prepared your organization is to begin or expand AI adoption today. It focuses on whether your business has the right foundation, including governance, data, security, infrastructure, and skilled teams. AI Maturity, on the other hand, measures how advanced your organization already is in using AI across the business. It evaluates the level of AI adoption, operational capabilities, and long-term optimization. In short, AI readiness asks, "Are you prepared to start?" while AI maturity asks, "How advanced is your AI journey?"
The cost of an AI Readiness Assessment depends on your organization's size, complexity, existing technology landscape, and assessment scope. Small businesses typically require a focused assessment, while enterprise organizations often need a broader evaluation covering governance, security, compliance, infrastructure, and multiple business units. The best approach is to start with a consultation to define the scope and provide a tailored assessment based on your business objectives.
Most AI Readiness Assessments take between 2 and 6 weeks, depending on the size of your organization and the depth of the review. Smaller assessments can often be completed in a few weeks, while enterprise engagements involving multiple departments, governance reviews, and stakeholder interviews may require additional time. The outcome is a practical roadmap that prioritizes improvements and helps accelerate successful AI adoption.
Most AI projects fail because organizations focus on the technology before preparing the business. Poor data quality, weak governance, security risks, unclear business objectives, limited executive sponsorship, and low employee adoption often prevent AI initiatives from delivering measurable value. An AI Readiness Assessment helps identify these challenges early, reducing implementation risks and increasing the likelihood of long-term AI success.
A Data Readiness Assessment focuses specifically on the quality, accessibility, governance, and structure of your data to determine whether it can support AI models. An AI Readiness Assessment is much broader — in addition to data, it evaluates governance, security, compliance, infrastructure, business processes, leadership alignment, change management, workforce readiness, and organizational strategy. Simply put, data readiness is one component of AI readiness, but successful AI adoption requires much more than high-quality data.
Yes. Establishing an AI Governance Policy before deploying AI helps reduce security, compliance, and operational risks while ensuring AI is used responsibly across the organization. A governance policy defines how AI tools should be used, who is accountable, how sensitive data is protected, and how regulatory and ethical requirements are met. Organizations that implement governance early are better positioned to scale AI confidently, maintain compliance, and build trust with employees and customers. Learn more about our AI Governance Consulting services to create a governance framework tailored to your business.
Thirty minutes with a Microsoft readiness consultant. We'll tell you which pillar we'd expect to be weakest — and whether you need a full assessment or just two weeks of cleanup.
No obligation · Direct with Garry and the delivery team