Nobody Really Knows What an AI Agent Actually Is

Silicon Valley is betting big on AI agents. OpenAI CEO Sam Altman predicts they will “join the workforce” this year, while Microsoft CEO Satya Nadella believes they will replace some knowledge-based jobs. Salesforce CEO Marc Benioff has even stated that the company aims to be “the number one provider of digital labor” through its suite of AI-driven services.

Yet, there’s little consensus on what an AI agent actually is.

In recent years, tech leaders have hailed AI agents as transformative, just as chatbots like OpenAI’s ChatGPT reshaped how we access information. However, defining an “agent” is tricky. Like other AI buzzwords—such as “multimodal,” “AGI,” and even “AI” itself—the term “agent” is being used so broadly that it risks losing all meaning.

Industry-Wide Confusion Over AI Agents

This ambiguity creates challenges for companies like OpenAI, Microsoft, Salesforce, Amazon, and Google, all of which are building product lines around AI agents. An agent from one company may function entirely differently from another, leading to confusion and customer frustration.

Ryan Salva, a senior product director at Google and former GitHub Copilot leader, expressed his frustration, saying, “I think our industry overuses the term ‘agent’ to the point where it is almost nonsensical.”

The debate over what defines an AI agent is not new. Last year, former TechCrunch reporter Ron Miller highlighted the issue, noting that nearly every company developing AI agents has its own interpretation.

This confusion has only grown.

OpenAI’s Inconsistent Definitions Add to the Confusion

This week, OpenAI published a blog post defining agents as “automated systems that can independently accomplish tasks on behalf of users.” Yet, in its developer documentation, the company described them as “LLMs equipped with instructions and tools.” OpenAI’s API product marketing lead, Leher Pathak, later suggested that “assistants” and “agents” were interchangeable terms, further blurring the distinction.

Microsoft, on the other hand, attempts to differentiate agents from AI assistants. According to its blogs, agents are “new apps” designed for an “AI-powered world” with specific expertise, while assistants handle general tasks like drafting emails.

Anthropic acknowledges the inconsistency, stating in a blog post that agents can be seen as either “fully autonomous systems that operate independently over time” or “prescriptive implementations that follow predefined workflows.” Meanwhile, Salesforce offers an even broader definition, categorizing agents into six types, from “simple reflex agents” to “utility-based agents” that respond to customer inquiries.

AI’s Evolution and Marketing Hype Blur Definitions

The lack of a clear definition stems from both the evolving nature of AI and marketing influence. OpenAI, Google, and Perplexity recently introduced their first agents—Operator, Project Mariner, and a shopping agent—each with vastly different capabilities.

Rich Villars, GVP of worldwide research at IDC, noted that tech companies rarely adhere strictly to technical definitions, prioritizing innovation in rapidly evolving fields. Andrew Ng, founder of DeepLearning.ai, argues that marketing has played a major role in distorting the term, stating that “about a year ago, marketers and a few big companies got a hold of it.”

Jim Rowan, head of AI at Deloitte, sees both opportunity and risk in the ambiguity. While it allows companies to tailor agents to their needs, it also leads to “misaligned expectations” and difficulty in measuring value and ROI. Without a standardized definition, benchmarking performance and ensuring consistent results become challenging.

Given how the term “AI” itself has evolved, a universal definition for “agent” seems unlikely to emerge—if it ever does.

Read the original article on: TechCrunch

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