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About nist.gov (Regulatory)
This page provides details about nist.gov (Regulatory) which was ranked #4 out of 266 in the list of sources (11 citations (3.4% share)) in answers from AI models (OpenAI ChatGPT Latest) when they were asked the following 4 questions: "What are the proven best practices and strategies experts use for AI Tools for Marketers?", "What tools, resources, or frameworks are essential for success with AI Tools for Marketers?", "What are the most common mistakes people make with AI Tools for Marketers and how can they be avoided?", "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 AI, NIST AI Risk Management Framework, Google, OWASP Top 10 for LLM Applications.
Used by AI Models
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Pages from nist.gov (3 links)
| URL Path | Citations | Position |
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| www.nist.gov | 0 | N/A |
| /itl/ai-risk-management-framework | 8 | 10 |
| /ai/risk-management | 3 | 160 |
Brands Referenced By This Website (4 brands)
| Brand | Voice | Mentions |
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58.6% | 104 |
| NIST AI Risk Management Framework | 3.7% | 7 |
| Google AI | 2.6% | 6 |
| OWASP Top 10 for LLM Applications | 0.8% | 3 |
Citations from AI Responses
OpenAI ChatGPT Latest
(11 citations)
What are the proven best practices and strategies experts use for AI Tools for Marketers?
[...] ragas](https://github.com/explodinggradients/ragas), Arize Phoenix [https://github.com/Arize-ai/phoenix](https://github.com/Arize-ai/phoenix) 7) Governance, legal, and brand safety guardrails - Adopt an AI risk framework; define roles, approvals, and audit trails. NIST AI Risk Management Framework [https://www.nist.gov/ai/risk-management](https://www.nist.gov/ai/risk-management) - Security and prompt-injection defenses for marketing agents and chatbots: OWASP Top 10 for LLM Apps [https://owasp.org/www-project-top-10-for-large-language-model-applications/](https://owasp.org/www-project-top-10-for-large-language-model-applications/), Microsoft prompt injection guidance [htt [...]
[...] nd playbooks; train teams on prompting and policy. - Manage change with structured frameworks: Prosci ADKAR [https://www.prosci.com/methodology/adkar](https://www.prosci.com/methodology/adkar) - Document everything: prompts, datasets, evaluation sets, and decision logs for auditability. NIST AI RMF [https://www.nist.gov/ai/risk-management](https://www.nist.gov/ai/risk-management) Channel-specific quick starts (playbook recipes) - Content/SEO: Use SEMrush/Ahrefs for research → draft with LLM + RAG to your docs/case studies → fact-check and cite → optimize per Google’s AI content guidance → publish → feed performance back to improve prompts. - SEMrush [https://www.semrush [...]
[...] C on AI claims in advertising [https://www.ftc.gov/business-guidance/blog/2023/02/keep-your-ai-claims-check](https://www.ftc.gov/business-guidance/blog/2023/02/keep-your-ai-claims-check) - U.S. Copyright Office AI guidance [https://www.copyright.gov/ai/](https://www.copyright.gov/ai/) - NIST AI RMF [https://www.nist.gov/ai/risk-management](https://www.nist.gov/ai/risk-management) - Control crawler access for AI training: GPTBot robots [https://openai.com/index/robots-for-gptbot/](https://openai.com/index/robots-for-gptbot/), Google-Extended [https://developers.google.com/search/blog/2023/09/introducing-google-extended](https://developers.google.com/search/blog/2023/09/intr [...]
What tools, resources, or frameworks are essential for success with AI Tools for Marketers?
[...] ](https://www.notion.so/product/ai) - Campaign databases and structured content ops: [Airtable AI](https://www.airtable.com/ai) - No-code automation with AI steps: [Zapier AI](https://zapier.com/ai) Governance, risk, and compliance (ship AI safely and earn trust) - AI risk management and controls: [NIST AI Risk Management Framework](https://www.nist.gov/itl/ai-risk-management-framework) - AI management system standard: [ISO/IEC 42001:2023](https://www.iso.org/standard/81230.html) - Privacy regulations guiding data use: [GDPR (EU Regulation 2016/679)](https://eur-lex.europa.eu/eli/reg/2016/679/oj), [California CCPA/CPRA Regulations](https://cppa.ca.gov/regulations/ccpa.html) Prom [...]
[...] or pipeline. Use NIST AI RMF to document risks and controls. - RACE: [Smart Insights – RACE](https://www.smartinsights.com/digital-marketing-strategy/race-planning-framework/) - OKRs: [What Matters – What are OKRs?](https://www.whatmatters.com/getting-started/what-are-okrs) - NIST AI RMF: [NIST AI Risk Management Framework](https://www.nist.gov/itl/ai-risk-management-framework) 2) Data foundation: Implement GA4 and stream key events to a warehouse (BigQuery or Snowflake). Build a lightweight dashboard in Looker Studio. - GA4: [Google Analytics 4](https://marketingplatform.google.com/about/analytics/) - BigQuery: [Google BigQuery](https://cloud.google.com/bigquery [...]
What are the most common mistakes people make with AI Tools for Marketers and how can they be avoided?
[...] and set confidence thresholds for publication. Train teams on the limitations of large language models (LLMs). Sources: Large language model (https://en.wikipedia.org/wiki/Large_language_model), GPT-4 Technical Report (https://arxiv.org/abs/2303.08774), NIST AI Risk Management Framework (AI RMF) (https://www.nist.gov/itl/ai-risk-management-framework) - Mistake 3: Weak prompting and lack of process How to avoid: Provide role, audience, goal, constraints, examples, and success criteria in prompts; iterate with drafts; create prompt templates and a prompt library for consistency. Sources: OpenAI Prompt Engineering (https://platform.openai.co [...]
[...] mix_modeling) - Mistake 8: Bias and representational harm in content or targeting How to avoid: Audit datasets, prompts, and outputs for fairness; add human review for sensitive topics; diversify examples in prompts; document known risks/mitigations. Sources: NIST AI Risk Management Framework (https://www.nist.gov/itl/ai-risk-management-framework), Google AI Principles (https://ai.google/responsibility/principles/) - Mistake 9: Ignoring security risks (prompt injection, data exfiltration) How to avoid: Treat prompts as an attack surface. Use input/output filters, allow‑lists for tools/connectors, content scanning, and isolation for exter [...]
[...] 10: Tool sprawl and “shadow AI” How to avoid: Centralize procurement, create an approved AI catalog, set usage and retention policies, and train teams. Map risks and controls to a formal framework. Sources: Shadow IT (https://en.wikipedia.org/wiki/Shadow_IT), NIST AI Risk Management Framework (https://www.nist.gov/itl/ai-risk-management-framework) - Mistake 11: Brand voice inconsistency and accessibility gaps How to avoid: Provide brand voice/tone guides to AI, require style adherence checks, and run accessibility checks (alt text, color contrast, captions) on AI creatives. Sources: Mailchimp Content Style Guide (https://styleguide.mai [...]
[...] ces: OpenAI Pricing (https://openai.com/pricing), Anthropic Pricing (https://www.anthropic.com/pricing), Google Vertex AI Pricing (https://cloud.google.com/vertex-ai/pricing) Quick, high‑leverage safeguards you can implement this quarter - Create an AI use policy and training based on NIST AI RMF (https://www.nist.gov/itl/ai-risk-management-framework). - Build a prompt library with templates and brand/style constraints (https://platform.openai.com/docs/guides/prompt-engineering; https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering). - Add a review workflow: fact check, compliance check, brand check, and accessibility check (h [...]
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 [...]
[...] 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 [...]