Free Assessment
Is Your Organization Ready for AI?
Eight questions. Two minutes. A clear picture of where your organization stands on AI adoption — and what to do next.
Breakdown by Domain
Ready to move from exploration to execution?
I help organizations evaluate AI opportunities, run structured pilots, and build governance frameworks that scale — without the cost of a full-time AI hire.
What This Assessment Measures
Every organization is talking about AI. Most haven't done the foundational work to deploy it responsibly. This assessment scores your organization across eight domains that determine whether an AI initiative will create value — or create expensive technical debt.
Data Governance
Is your data organized, accessible, and governed — or scattered across spreadsheets and siloed systems?
Automation Maturity
AI builds on existing automation. Organizations without basic workflow automation rarely succeed with AI.
Team Technical Depth
You don't need a data science team, but you need someone who can evaluate tools, architect integrations, and set guardrails.
Compliance Posture
AI in regulated industries requires explicit governance. Do you know what applies to you?
Budget Clarity
AI pilots need defined budgets with measurable outcomes — not open-ended exploration funds.
Vendor Evaluation
How do you evaluate AI tools? "Someone on the team tried it" isn't a procurement process.
Use Case Clarity
Have you identified specific processes with quantifiable ROI, or is AI still a vague initiative?
Risk Tolerance
How would leadership react to an AI mistake? The answer shapes which use cases you should start with.
Who This Assessment Is For
This scorecard is for business leaders — founders, CEOs, COOs, executive directors — who are being asked (or asking themselves) whether their organization should be using AI. Not the individuals already experimenting with ChatGPT, but the leaders responsible for deciding whether to invest organizational resources.
If you've been to a conference where every vendor had an "AI-powered" slide, if your board is asking about your AI strategy, or if you've seen competitors announce AI initiatives and aren't sure whether to follow — this assessment will cut through the noise and tell you exactly where you stand.
Built by Alex van Rossum, a fractional CTO based in north metro Atlanta who helps organizations evaluate AI opportunities and build governance frameworks that don't require a full-time AI hire. Learn more about working together.
Frequently Asked Questions
What does "AI readiness" actually mean? +
AI readiness is your organization's ability to deploy AI operationally — not just experiment with ChatGPT. It covers data governance, team capability, compliance posture, budget allocation, and whether you've identified specific use cases with measurable ROI. Most organizations are less ready than they think, and this assessment surfaces the gaps before you spend money on tools.
Do we need to hire AI engineers to use AI effectively? +
Not necessarily. Many high-impact AI deployments use existing platforms and APIs — no ML engineering required. What you do need is someone who can evaluate vendors, architect integrations, set guardrails, and measure outcomes. That's a strategic role, not a data science hire. A fractional CTO can fill that role without a full-time salary commitment.
How do we know which processes are good candidates for AI? +
The best candidates share three traits: high volume, repeatable patterns, and tolerance for imperfection. Document processing, customer inquiry routing, content drafting, data extraction from unstructured sources — these are where AI creates immediate ROI. Avoid starting with processes where errors are catastrophic or regulatory exposure is high.
What are the biggest risks of deploying AI without proper governance? +
Hallucinated outputs reaching customers, compliance violations from unreviewed AI decisions, vendor lock-in to platforms you don't fully understand, and the subtle one — organizational over-trust where people stop checking AI outputs. Governance isn't bureaucracy; it's the difference between a tool and a liability.
How much should we budget for an AI pilot? +
A well-scoped pilot for a single use case typically runs $15K–$50K including the technical advisory, platform costs, and integration work. The goal is to prove (or disprove) ROI on one specific process before scaling. Organizations that skip the pilot phase and go straight to enterprise AI platforms routinely waste 5–10x that amount.
What's the difference between using AI tools and deploying AI operationally? +
Using AI tools means individuals using ChatGPT, Copilot, or similar products ad hoc. Deploying AI operationally means integrating AI into business workflows with defined inputs, outputs, quality checks, and monitoring. The first is experimentation; the second is infrastructure. Most organizations are stuck between the two.
How do we evaluate AI vendors without technical expertise? +
Start with three questions: What data do they need access to (and where does it go)? What happens to your workflows if they shut down or raise prices? Can you export your data and integrations to a competitor? If a vendor can't answer these clearly, that's your answer. A fractional CTO can run a structured vendor evaluation in 2–3 weeks.