Agentic or pathetic? Gartner warns of “agent washing” as only 130 AI products truly behave agentically

Gartner analysts have identified a new deceptive practice called “agent washing,” where vendors falsely market basic automation tools and chatbots as advanced AI agents. Out of thousands of supposedly agentic AI products tested, only 130 genuinely possessed the autonomous capabilities they claimed, highlighting a widespread misrepresentation that threatens to undermine trust in AI innovation.

What you should know: True AI agents differ fundamentally from standard automation tools by their ability to reason, plan, and execute complex tasks with minimal human intervention.

• Genuine agentic AI can complete multi-step processes, interface with external systems, and adapt to new situations without pre-programmed instructions.
• These systems can write and execute code when needed, make autonomous decisions, and engage in long-term goal-oriented planning.
• Unlike simple chatbots or robotic process automation (RPA), real agents don’t just follow predetermined steps—they actively problem-solve and strategize.

The deceptive practices: Vendors are rebranding existing technologies as “agentic” when they lack true autonomous capabilities.

• Customer service “agents” are often just chatbots that can only generate advice or connect users to humans.
• RPA systems that execute predetermined steps are being mislabeled as AI agents, despite having no reasoning or decision-making abilities.
• Marketing automation platforms and workflow tools claim to be agentic simply because they orchestrate multiple AI systems, without true autonomous coordination.

Real vs. fake examples: The difference becomes clear when comparing actual capabilities across similar use cases.

• A chatbot might write emails on command, while a true agent would write emails, identify optimal recipients, send them, monitor responses, and generate personalized follow-ups.
• In e-commerce, chatbots can search catalogs for products, but agents can shop across multiple sites, compare prices, and complete purchases autonomously.
• LLM tools with API access require precise instructions, whereas genuine agents can figure out how to communicate with unfamiliar systems independently.

Why this matters: Gartner predicts up to 40% of agentic AI projects will fail or be cancelled by the end of 2027, largely due to inflated expectations and misunderstanding.

• Businesses investing in falsely marketed tools may experience operational failures when systems can’t deliver promised autonomous capabilities.
• Overconfidence in AI abilities could lead to serious risks in critical applications, from customer service to cybersecurity.
• The practice threatens to erode trust in AI technology and undermine legitimate innovation in the space.

The bigger picture: Agent washing represents a broader threat to AI industry credibility and genuine technological progress.

• Misleading marketing makes it harder for startups and developers working on real agentic breakthroughs to gain traction and funding.
• The practice could damage public trust in AI concepts that, when properly implemented, offer significant benefits.
• Building AI literacy across organizations becomes crucial for distinguishing between genuine innovation and marketing hype.

What experts recommend: Companies should demand transparency and accountability from AI vendors while building internal expertise to evaluate claims.

• Organizations need to develop the ability to identify systems that can genuinely plan long-term and adapt to changing circumstances.
• Vendors should be held to higher standards when communicating both strengths and limitations of their products.
• Understanding the fundamental differences between automation and true agency helps avoid costly implementation failures.