How often is nist.gov cited by AI models?

nist.gov was cited 2 times by AI models, representing 14.6% of all source citations.

Which AI models cite nist.gov?

nist.gov is cited by 1 AI models including Perplexity Sonar (with search) (latest), Anthropic Claude Sonnet (latest), OpenAI ChatGPT Latest, Google Gemini Flash (latest), X.AI Grok (latest).

What is nist.gov's ranking among source domains?

nist.gov ranks #2 out of 70 source domains analyzed (with 50 brands also tracked).

What brands are associated with nist.gov?

AI models reference nist.gov when discussing brands like Google, NIST AI Risk Management Framework, OWASP Top 10 for LLM Applications.

How is source ranking determined?

Sources are ranked by Share of Voice = Model Coverage × Quality Score. Model weights are based on Monthly Active Users (OpenAI ChatGPT Latest: 900M MAU, Google Gemini Flash (latest): 650M MAU, Perplexity Sonar (with search) (latest): 45M MAU, etc.). Sources appearing earlier in AI responses receive higher prominence scores.

#{{ domain.rank }}

Share of Voice

{{ domain.linkTypeName }} • Visit • {{ botCount }} AI models • {{ questionCount }} questions

About nist.gov (Regulatory)

This page provides details about nist.gov (Regulatory) which was ranked #2 out of 70 in the list of sources (2 citations (14.6% share)) in answers from AI models (OpenAI ChatGPT Latest) when they were asked the following 1 question: "What do industry leaders recommend as the first steps when starting with AI Tools for Marketers?" on Oct 24, 2025 by AI Chat Watch. This source is referenced for brands: Google, NIST AI Risk Management Framework, OWASP Top 10 for LLM Applications.

#{{ domain.rank }}

Rank

Voice

Position

{{ formatPercent(domain.mentionsAsPercent) }} ({{ domain.mentions || 0 }})

Citations

Used by AI Models

Model	Voice	Position	Citations
{{ bot.name.charAt(0) }} {{ bot.name }}	{{ getInfluenceForBot(bot.id) }}	{{ getPositionForBot(bot.id) }}	{{ getMentionsForBot(bot.id) }}

Pages from nist.gov (1 link)

URL Path	Citations	Position
/itl/ai-risk-management-framework	2	2

Brands Referenced By This Website (3 brands)

Brand	Voice	Mentions
Google	34.2%	8
NIST AI Risk Management Framework	5.7%	1
OWASP Top 10 for LLM Applications	5.4%	2

Citations from AI Responses

OpenAI ChatGPT Latest (2 citations)

What do industry leaders recommend as the first steps when starting with AI Tools for Marketers?

[...] pot.com/marketing/ai-marketing) - Establish lightweight guardrails and an internal AI policy before wide use. Define approved tools, data handling, human review, transparency, and risk processes. Use these widely referenced frameworks and principles: - NIST AI Risk Management Framework (AI RMF) (https://www.nist.gov/itl/ai-risk-management-framework) - Google AI Principles (https://ai.google/principles/) - Microsoft Responsible AI resources (https://www.microsoft.com/ai/responsible-ai) - OpenAI Usage Policies (what’s permitted, safety expectations) (https://openai.com/policies/usage-policies) - Protect data and privacy from day one. Tra [...]

nist.gov/itl/ai-risk-management-framework October 24, 2025

[...] bspot.com/marketing/ai-marketing) - Scale gradually and govern. When a pilot meets your thresholds, templatize the workflow, add guardrails (policy + reviews), and expand to adjacent use cases. Revisit risk and performance regularly: - NIST AI RMF (operationalizes risk, governance, measurement) (https://www.nist.gov/itl/ai-risk-management-framework) - OWASP Top 10 for LLM Applications (keep security considerations front-and-center as usage grows) (https://owasp.org/www-project-top-10-for-large-language-model-applications/) If you share your specific marketing goals and current stack, I can help you pick 2–3 pilot use cases and draft prompt [...]