---
id: "prereq-ai-typology"
type: "prereq"
source_timestamps: ["§ A Survey of Executives Suggests Anticipatory Effects"]
tags: ["ai-fundamentals"]
related: ["concept-ai-economic-value-measurement", "claim-genai-hardest-to-value"]
reason: "Required to understand why 44% of executives find generative AI uniquely difficult to value compared to other established forms of AI."
sources: ["execution"]
sourceVaultSlug: "hbr-seg-execution"
originDay: 8
articleStem: "hbr-foci-62-layoffs-ai-potential-not-performance"
sourceUrl: "https://hbr.org/2026/01/companies-are-laying-off-workers-because-of-ais-potential-not-its-performance"
sourceTitle: "Companies Are Laying Off Workers Because of AI’s Potential—Not Its Performance"
---
# Understanding of AI Typologies

**Prerequisite knowledge:** The distinctions among **generative AI, analytical AI, deterministic AI, and agentic AI**.

**Why it matters:** The article's key measurement claim — that generative AI is the *hardest* form of AI to assess for economic value — only lands if the reader can contrast generative AI against these other established forms. Required to grasp [[concept-ai-economic-value-measurement]] and [[claim-genai-hardest-to-value]] (and its contrarian framing [[contrarian-genai-hardest-to-value]]).

**Quick orientation:** *analytical* AI = statistical/predictive modeling on structured data; *deterministic* AI = rule-based, reproducible-output systems; *generative* AI = probabilistic content generation (LLMs, image models) with qualitative, hard-to-quantify outputs; *agentic* AI = goal-directed systems that plan and take multi-step actions. Generative AI's diffuse, qualitative impact on knowledge work is what makes its value uniquely hard to measure.