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About nist.gov (Regulatory)
This page provides details about nist.gov (Regulatory) which was ranked #2 out of 80 in the list of sources (4 citations (13.9% share)) in answers from AI models (OpenAI ChatGPT Latest) when they were asked the following 1 question: "What are the most common mistakes people make with AI Tools for Marketers and how can they be avoided?" on Oct 24, 2025 by AI Content & Web. This source is referenced for brands: NIST AI Risk Management Framework.
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Pages from nist.gov (2 links)
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| www.nist.gov | 0 | N/A |
| /itl/ai-risk-management-framework | 4 | 4 |
Brands Referenced By This Website (1 brand)
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Citations from AI Responses
OpenAI ChatGPT Latest
(4 citations)
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 [...]