TechCrunch: A primer on core AI terminology and concepts

What happened

TechCrunch has published a comprehensive glossary and guide aimed at clarifying common artificial intelligence terminology. The resource is designed to help professionals navigate the technical jargon surrounding the industry, specifically addressing concepts like hallucinations and other foundational AI terms that are frequently used in business contexts but often misunderstood. The guide serves as a foundational reference for those looking to improve their technical literacy.

Why it matters for agencies

For agency owners, the gap between "nodding along" and actually understanding AI architecture is a business risk. When you sell AI-driven services—whether it’s automated SEO, programmatic ad buying, or content generation—you are effectively selling a "black box" to clients. If you cannot explain the limitations of your tools, such as why a model might hallucinate or how it processes data, you lose credibility and expose your agency to liability.

Understanding these terms allows you to better vet the tools you integrate into your stack, such as those discussed in our guide to AI content generation. It shifts your agency from being a passive user of "magic" tools to an informed operator capable of managing client expectations regarding output accuracy. This technical fluency is essential when explaining to a client why an AI-generated campaign might require human oversight or why specific data inputs are necessary for better performance.

What to do about it

Use this glossary as a baseline for an internal team training session. Do not assume your junior copywriters or account managers fully grasp the distinction between generative models and deterministic software.

Create a "Client-Facing AI Glossary" based on these definitions. When onboarding new clients, include this document to set expectations regarding AI capabilities and risks, particularly regarding accuracy and hallucinations. If your team cannot define the terms in this guide, they are not yet ready to sell AI-managed services to high-stakes clients. Test your team’s knowledge; if they struggle, prioritize technical literacy before adding new AI tools to your workflow.

What to watch

Monitor how these foundational definitions evolve as models become more agentic and autonomous. The industry is currently moving from simple text-generation tools to complex, multi-step AI agents. Keep an eye on how "hallucination" is redefined as models gain better access to real-time, verified data sources, which may change how you frame risk to your clients in the coming months.

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Source: So you’ve heard these AI terms and nodded along; let’s fix that