---
id: "entity-agentic-ai-d4"
type: "entity"
entityType: "other"
canonicalName: "Agentic AI"
aliases: ["AI agents", "autonomous AI agents"]
source_timestamps: ["§ Myth 3"]
tags: ["technology", "ai-agents"]
related: ["concept-agentic-ai-sales", "evidence-agentic-scale-caveats"]
sources: ["attention"]
sourceVaultSlug: "hbr-seg-attention"
originDay: 4
articleStem: "hbr-cl-90-genai-myths-sales-marketing"
sourceUrl: "https://hbr.org/2025/02/5-gen-ai-myths-holding-sales-and-marketing-teams-back"
sourceTitle: "5 Gen AI Myths Holding Sales and Marketing Teams Back"
---
# Agentic AI

## Agentic AI

**Type:** Technology category / advanced application of Generative AI (recorded here as entityType `other` — a technology paradigm rather than a person, org, or specific product).

**Definition:** AI systems that can plan and execute **multi-step workflows**, interact with tools/APIs, and act autonomously across channels — rather than simply generating text in a chat interface. In the source, agentic AI is the reality that dismantles Myth 3. See [[concept-agentic-ai-sales]].

**Canonical reference:** No single canonical URL. Agentic AI is discussed across research communities (autonomous multi-step, tool-using systems; workflow orchestration) and enterprise vendors framing "AI agents" that automate tasks across CRM, email, and customer service.

**Context:** In sales, agentic AI powered the equipment-manufacturer case that engaged ~50,000 customers and generated 1M+ quotes in month one ([[claim-agentic-scale]]). The literature the article only hints at covers **guardrails, monitoring, and failure modes** — see [[evidence-agentic-scale-caveats]] and the open question [[question-agentic-quality-control]]. Distinguishing plain LLMs from agentic AI is a prerequisite — [[prereq-llm-familiarity]].