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Elena DuarteAI-generated
NIST AI RMF Readiness Report

Elena Duarte

Director of RevOps · RevOps AI
Software & SaaS
Actor role
deployer
Risk tier
high
Confidence
100 · High
Lifecycle
production

As a deployer on a high-risk production, your self-attested readiness is "Material gaps" (41/100). You are strongest in map — context, intended purpose & impact profile; the most material gap is in manage — risk treatment, monitoring & improvement.

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Executive summary
Readiness score
41/ 100
Material gaps
Function average
41raw

Confidence adjusts 4141.

Confidence
100High

Reflects how complete and consistent your profile and current-state answers are. It never raises readiness.

Foundational caps
0binding

Foundational gaps that cap the score and cannot be averaged away. See findings below.

What this assessment indicates

As a deployer on a high-risk production, your self-attested readiness is "Material gaps" (41/100). You are strongest in map — context, intended purpose & impact profile; the most material gap is in manage — risk treatment, monitoring & improvement.

Strongest function
Map — context, intended purpose & impact profile
Primary gap
Manage — risk treatment, monitoring & improvement
Immediate focus
Gate high-impact agent actions behind human approval

Function performance

Score out of 100 · target 70
Map — context, intended purpose & impact profile
46.2
Govern — organizational AI risk governance
41.3
Measure — TEVV, metrics & trustworthiness evaluation
40
Manage — risk treatment, monitoring & improvement
37.1
0–24 Critical25–49 At risk50–74 Moderate75–100 Strong

Trustworthiness overlay

A secondary view of how your implemented controls map to NIST’s seven trustworthiness characteristics. It does not double-count into the four function scores.

Valid & Reliable
40
Safe
31.8
Secure & Resilient
40
Accountable & Transparent
51.6
Privacy-Enhanced
40

Top strengths

  • Is there a resourced inventory mechanism for AI systems, components and workflows? GOVERN 1.6
  • Is the intended purpose, context of use, user population and deployment setting documented? MAP 1.1

Top gaps

  • Are high-impact or irreversible actions gated by human approval or policy checks? Human oversight
  • Can the organization pause, disable or revoke agent capabilities quickly? MANAGE 2.4
  • Are agent tools and permissions limited by explicit purpose and risk tier? GOVERN / MANAGE
  • Are external-system credentials, secrets and scopes managed securely? Security / resilience
  • Are agent policies and runtime controls tested against adversarial prompts and tool-abuse scenarios? MS-2.7

Prioritized remediation roadmap

  1. P0
    Gate high-impact agent actions behind human approval
    Human oversightOwner: Platform / SecurityBefore launch/continued use / 0–30 days
  2. P0
    Implement a fast kill switch to pause or revoke agent capabilities
    MANAGE 2.4Owner: Platform / SecurityBefore launch/continued use / 0–30 days
  3. P0
    Implement GenAI content safety, provenance and misuse controls
    AI 600-1Owner: Product / SecurityBefore launch/continued use / 0–30 days

Turn these findings into a remediation plan

Unlock the detailed report for a function-by-function gap matrix and a 30/60/90-day roadmap, or request a verified review with evidence and analyst input.

This is an informational, self-attested readiness result — not a NIST endorsement, certification, audit, conformity assessment, or proof that an AI system is safe, fair, valid or trustworthy. No documents or evidence were reviewed. Foundational caps prevent a strong area from hiding a missing foundation; the confidence score reflects how complete and consistent your answers are, not whether controls truly exist.