

How prepared is your organization is to plan, build, and launch AI projects and organizational AI Transformation.
Most companies don't fail at AI because of the technology. They fail because they move before the strategy, data, people, and operating model are ready. This 5-minute assessment scores your organization across seven dimensions of AI maturity so you know exactly where you are and what to fix first.
You'll answer 21 questions across strategy, data, technology, governance, people, process, and customer trust. You get an overall maturity score, a per-section breakdown, and a tiered set of recommendations matched to your readiness level.
The assessment is built on the Voyant Method, our framework for moving mid-market companies from AI experiments to measurable results. For deeper reading on what separates AI programs that scale from ones that stall, see our Perspective library. If you'd rather talk through your situation before scoring it, get in touch.
Your scorecard is the average of your answers per section and overall.
Without a clear strategic direction, AI initiatives become expensive experiments with no measurable return. This dimension ensures your AI investments are tied to real business outcomes.
We have a clear AI goal tied to revenue, cost, or customer outcomes.
We have 2 to 5 specific use cases prioritized by expected impact and effort.
An executive sponsor is accountable for AI results.
AI is only as good as the data it learns from. Poor data quality, accessibility, or governance will undermine even the most sophisticated models.
The data for our top use cases is easy to find and access.
The data is clean, complete, and labeled where needed.
We have permission and policies to use this data for AI.
The right infrastructure turns AI prototypes into production systems. Without it, promising pilots stall before they deliver value.
We have reliable environments for development, testing, and production.
We can integrate AI outputs into apps or workflows users already use.
We can log, observe, and roll back AI changes safely.
Trust is the foundation of AI adoption. Strong governance protects your organization, your customers, and your reputation from AI-related risks.
We have policies for data privacy, security, and model access.
We have a process to review AI for bias and harmful outputs.
We have documented escalation paths for AI incidents.
Technology alone doesn't drive transformation—people do. The right skills, roles, and culture determine whether AI initiatives succeed or fail.
We have named product, data, and engineering owners for AI work.
Non technical staff know how to use AI tools safely and effectively.
We can support change management and communication for AI rollouts.
Sustainable AI requires repeatable processes for experimentation, measurement, and iteration. Ad hoc approaches don't scale.
We run small experiments with clear stop or scale decisions.
We track benefits such as time saved, quality, or revenue lift.
We have a backlog and roadmap for the next 3 months of AI work.
Responsible AI builds long-term trust with customers and stakeholders. Transparency and accountability are essential for sustainable deployment.
We tell users when AI is involved and how to get help.
We allow users to give feedback or opt out where appropriate.
We log decisions made with AI for audit when needed.
Your full report includes detailed findings for each category, specific recommendations based on your scores, and a prioritized action plan with quick wins you can start this week.
Answer all 21 questions (0/21 complete) to unlock your full report.