GenAI Readiness Checker
Is your organization ready to build with generative AI? Get your readiness score and discover the right AWS AI starting point — in under 4 minutes.
Question
Your GenAI Readiness Score
Based on 5 critical dimensions of AI adoption
Score by Dimension
Recommended AWS Starting Point
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Book a Free AI Strategy Session →Who This Tool Is For
CTOs and product leaders at companies considering their first Amazon Bedrock or SageMaker deployment who need a structured way to assess internal readiness. If your board is asking "Should we invest in AI?" and your data/team/infra readiness is unclear, this quiz cuts through the hype and gives you an honest answer.
Why We Built This Tool
Every CTO gets asked about AI now. Most guides for AI readiness are vendor white-papers or consulting pitches. We needed a tool that was vendor-neutral, grounded in AWS reality, and honest about what actually matters for GenAI adoption. This quiz asks the hard questions: Do you have data governance? Can your team actually deploy models? Is your infrastructure cloud-ready? Then it tells you your starting point—Bedrock (fastest), SageMaker (most control), or Amazon Q (quickest win).
What Problem It Solves
- Vague board asks. "Should we do AI?" is too broad. This quiz gives you a concrete readiness score to justify the conversation.
- Service proliferation. AWS has 10+ AI services. Without understanding your own maturity, you pick wrong and waste months in PoC hell.
- Team skepticism. Data teams, ops, and engineering often have conflicting views on readiness. A shared assessment builds consensus.
- MVP clarity. Knowing your readiness level helps you scope the right first project (commodity task vs. differentiator vs. experimentation).
Explore our generative AI on AWS services for hands-on guidance from proof-of-concept to production.
How to Use This Tool
- Answer 15 questions. Questions span data maturity, team skills, infrastructure readiness, and GenAI use-case clarity. Be honest—this is for you, not for anyone else.
- Get your readiness score. A score out of 100 (Ready, Mostly Ready, Needs Work, or Not Ready) with category breakdowns.
- See your AWS AI starting point. Based on your score, we recommend: Amazon Bedrock (pre-trained models, fastest), SageMaker (custom models, more control), Amazon Q (enterprise search & coding, quick wins), or "Not Yet" (build data/team first).
Frequently Asked Questions
What's the difference between Bedrock, SageMaker, and Amazon Q?
Bedrock: Use pre-trained models (Claude, Mistral, etc.) without managing infrastructure. Fastest time-to-value. SageMaker: Build, train, and deploy custom models. More control, steeper learning curve. Amazon Q: Generative AI chat for your enterprise knowledge base or codebase. Best for RAG and code generation. This quiz recommends the right one based on your skills and data.
Can our small team be "ready" for GenAI?
Absolutely. Readiness isn't about team size; it's about discipline. A 5-person team with strong data governance, clear use cases, and DevOps automation can be more ready than a 50-person team without those things. This quiz measures readiness, not scale.
What if we score "Not Ready"?
That's useful data. It tells you what to fix first: data governance, team skills, or cloud infrastructure. Most "Not Ready" teams can get to "Mostly Ready" in 4–8 weeks by addressing those gaps. Book a strategy session to build your readiness roadmap.