AI Readiness Measurement System
Human Readiness. AI Governance. Two independent measurements, tracked continuously, backed by evidence.
Adoption has accelerated. Readiness has not. Organizations can count deployments, training completions, and policy documents. None of that tells them whether the organization is actually ready to use AI responsibly, or gives them evidence when someone asks.
Governance frameworks define what an organization should do. Training platforms teach people what they should know. Consulting engagements assess a moment in time and produce a document. Each is useful. None of them continuously measures whether the organization is ready, and none produces evidence that holds up months later when the question is asked.
Medicine measures health. Finance measures risk. Education measures proficiency. In each case the thing being measured is not directly observable. It is inferred from signals that are. Organizational AI readiness works the same way. It is a latent condition that leaves observable evidence behind, in how people behave and in how systems are governed.
METRIS is built on that premise. It reads the evidence an organization already generates and turns it into continuous measurement.
Organizations have learned how to measure AI performance. METRIS helps them measure organizational AI readiness.
Scenario-based measurement of how people understand, judge, and use AI in their actual work.
Continuous measurement of the governance evidence an organization produces, and what that evidence indicates.
Two independent measurements. One measurement system. Together they describe organizational AI readiness.
Policies, assessments, and training records show what an organization intended. METRIS examines what the accumulated evidence indicates about what is actually true. It establishes a baseline, separates missing evidence from evidence of failure, tracks change over time, and keeps every result traceable to the evidence underneath it.
METRIS measures the governance around AI systems and the readiness of the people using them. It does not evaluate model weights or replace model validation. We are explicit about what we measure and what we do not.
METRIS is designed first for mid-size healthcare and insurance organizations, where AI decisions carry high expectations for evidence, accountability, and human oversight, and where the question of readiness arrives from a board, a customer, or a regulator rather than from curiosity.
SANJEEVANI AI is built in St. Louis, hiring locally, starting with the healthcare and insurance organizations that anchor this region, and scaling nationally from here.
Suneeta Modekurty is the Founder and CEO of SANJEEVANI AI. Her work spans artificial intelligence, data science, and bioinformatics, applied across healthcare, insurance, and education. She has spent her career measuring things that resist measurement. METRIS came from asking the same question about organizations adopting AI.
SANJEEVANI AI LLC, St. Louis, Missouri, USA. Email: suneeta@sanjeevaniai.com. Website: https://sanjeevaniai.com