10 AI Terms to Learn

By Curtis Brown

AI is no longer just a buzzword—it’s the difference between staying ahead of the competition or falling behind. For financial advisors and executives, speaking the language of AI isn’t optional—it’s essential.

Here’s your Tier1 quick primer on 10 must-know AI terms—each one paired with why it matters to your business.

  1. Core AI Concepts
  • Artificial Intelligence (AI) – Software that performs tasks requiring human intelligence, from answering client questions to detecting fraud.
    Why it matters: AI can automate routine work so you can focus on high-value client relationships.
  • Machine Learning (ML) – AI that improves performance by learning from data without explicit programming.
    Why it matters: It can spot portfolio risk trends and client behavior patterns before you do.
  • Generative AI (GenAI) – AI that creates new content—emails, presentations, or research summaries—based on learned patterns.
    Why it matters: Cuts prep time for client communications from hours to minutes.
  1. How AI Understands & Communicates
  • Natural Language Processing (NLP) – The tech that lets AI understand and respond to human language, powering chatbots and voice assistants.
    Why it matters: Enables scalable, personalized client service—even outside business hours.
  • Large Language Model (LLM) – AI trained on massive datasets to generate human-like responses and insights.
    Why it matters: Delivers fast, research-quality summaries tailored to your questions.
  • Retrieval-Augmented Generation (RAG) – AI that searches external data sources before generating answers, improving accuracy.
    Why it matters: Ensures answers are based on real, relevant, and up-to-date information—critical for compliance.
  • Prompt Engineering – Crafting precise instructions to get the best AI output.
    Why it matters: The right prompt can make the difference between a vague answer and a client-ready deliverable.
  1. Trust & Accuracy
  • Bias in AI – When AI produces unfair results due to biased training data.
    Why it matters: Helps avoid compliance and reputational risks in client decision-making.
  • Fine-Tuning – Customizing a pre-trained AI to perform better in a specific industry, like wealth management.
    Why it matters: Produces tools that speak your business language and meet your specific needs.
  • Hallucination – When AI confidently generates incorrect or made-up information.
    Why it matters: A reminder that human oversight is essential—especially for regulated communications.

You’re already competing with firms that speak this language fluently!
Get the full 20-term AI guide here

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