Mediumsystemic

Agent Washing

Vendors rebrand existing products as "AI agents" without substantial agentic capabilities, misleading organizations about what they're purchasing.

Overview

How to Detect

Products marketed as agents lack autonomous decision-making. "Agent" features are essentially chatbots with API calls. Expected capabilities don't match marketing claims.

Root Causes

Market hype creates pressure to rebrand products. Lack of clear industry definitions for "agent." Buyer unfamiliarity with agentic capabilities. Vendor incentives to oversell.

Test your agents against this failure mode
Try Playground

Deep Dive

Overview

"Agent washing" is the practice of rebranding existing AI products—chatbots, RPA, and basic automation—as "AI agents" to capitalize on market hype. Organizations purchase these products expecting autonomous, goal-directed behavior but receive limited automation dressed in agentic marketing.

The Problem

Gartner warns that "many vendors are engaging in 'agent washing' – the rebranding of existing products like AI assistants and RPA without substantial agentic capabilities."

What Gets Agent-Washed

PRODUCT TYPE              REBRANDED AS
────────────────          ────────────────
Chatbot with intents  →   "Conversational Agent"
RPA with LLM wrapper  →   "Intelligent Agent"
API orchestration     →   "Autonomous Agent"
Workflow automation   →   "Agentic Workflow"
Search with RAG       →   "Research Agent"

True Agentic Characteristics

A genuine AI agent should demonstrate:

Goal-Directed Autonomy

  • Pursues objectives without step-by-step instructions
  • Makes decisions about how to achieve goals
  • Adapts approach based on feedback

Planning Capability

  • Breaks down complex tasks
  • Sequences actions appropriately
  • Handles dependencies

Tool Use

  • Selects appropriate tools for tasks
  • Invokes tools with correct parameters
  • Interprets and acts on results

Reasoning

  • Explains its decision-making
  • Handles novel situations
  • Learns from outcomes

Red Flags

Marketing vs. Reality

  • "Autonomous" but requires constant human input
  • "Intelligent" but follows rigid decision trees
  • "Adaptive" but can't handle variations

Limited Tool Access

  • Only uses pre-configured integrations
  • Can't reason about when to use which tool
  • No ability to chain tool calls dynamically

Scripted Interactions

  • Follows predetermined conversation flows
  • Can't deviate from trained scenarios
  • Breaks on unexpected inputs

No Planning

  • Only executes single-step actions
  • Can't decompose complex tasks
  • No ability to recover from errors

Organizational Impact

Misaligned Expectations

Teams expect autonomous operation but get supervised automation.

Wasted Investment

Budget allocated for agent projects spent on chatbot upgrades.

Lost Opportunity

Real agent projects deprioritized due to "failed" agent-washed products.

Pilot Failures

Agent-washed products fail to deliver, creating skepticism about genuine agent capabilities.

Evaluation Framework

Before purchasing, assess:

Criterion                  Score (1-5)
─────────────────────────────────────
Goal decomposition         ___
Autonomous tool selection  ___
Multi-step planning        ___
Error recovery             ___
Novel situation handling   ___
Explanation capability     ___

Total: ___ / 30
< 15: Likely agent-washed
15-22: Partial agentic capabilities
> 22: Genuine agent characteristics

How to Prevent

Clear Requirements: Define specific agentic capabilities needed before vendor evaluation.

Capability Assessment: Evaluate products against specific agentic criteria, not marketing claims.

Proof of Concept: Require demos of autonomous behavior on novel, unscripted scenarios.

Reference Checks: Talk to existing customers about real-world autonomous operation.

Incremental Adoption: Start with limited scope to validate capabilities before full commitment.

Industry Standards: Push for industry-standard definitions of agentic capabilities.

Want expert guidance on implementation?
Get Consulting

Real-World Examples

A 2025 industry survey found that 67% of products marketed as "AI agents" failed to demonstrate autonomous goal pursuit when tested with novel scenarios outside their training distribution.

PreviousSycophancy Amplification
NextConformity Bias
Tags
marketingvendorprocurementhypedefinitions

Was this failure mode helpful?

Report a new failure mode