What Exactly Is an AI Agent? The Tech Industry Can’t Seem to Agree

Silicon Valley is betting big on AI agents. OpenAI CEO Sam Altman claims they will “join the workforce” this year, while Microsoft’s Satya Nadella predicts they will replace certain types of knowledge work. Salesforce CEO Marc Benioff has even positioned his company as the leading provider of “digital labor” through AI-driven agent services.

Yet, despite the hype, no one seems to agree on what an AI agent actually is.

AI Agent

The term “AI agent” has quickly become the latest buzzword, much like “multimodal AI” and “AGI” before it. Tech leaders insist that agents will transform how we work, just as AI chatbots like ChatGPT revolutionized information retrieval. However, without a clear definition, the term is becoming increasingly vague—if not outright meaningless.

The Definition Dilemma

The inconsistency in defining AI agents is already creating challenges. Tech giants like OpenAI, Microsoft, Google, and Amazon are rolling out agent-based products, but each company has a different interpretation of what an agent does. This is leading to confusion—and frustration—among users and businesses trying to navigate the space.

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

OpenAI’s recent blog post described agents as “automated systems that can independently accomplish tasks on behalf of users.” But just days later, its developer documentation defined them as “LLMs equipped with instructions and tools.” To complicate matters further, OpenAI’s API product marketing lead, Leher Pathak, suggested that “assistants” and “agents” are essentially the same—blurring the lines even more.

Microsoft attempts to separate agents from AI assistants by suggesting that agents are more specialized and can be tailored for expertise, while assistants handle general tasks like drafting emails. Meanwhile, AI lab Anthropic acknowledges the lack of a unified definition, stating that agents can range from fully autonomous systems to structured workflows following predefined steps.

Salesforce takes perhaps the broadest approach, classifying agents as any system that can “understand and respond to customer inquiries without human intervention.” The company even lists six different agent types, from simple reflex agents to more advanced utility-based models.

Why the Confusion?

The rapid evolution of AI agents is partly to blame. Companies like OpenAI, Google, and Perplexity have only recently launched what they consider their first AI agents—such as OpenAI’s Operator, Google’s Project Mariner, and Perplexity’s shopping agent. Each product serves a different purpose, making it difficult to pinpoint a universal definition.

Rich Villars, GVP of worldwide research at IDC, argues that tech companies have never been strict about definitions. “They care more about what they are trying to accomplish,” he said, especially in fast-moving markets like AI.

But marketing also plays a significant role. AI expert Andrew Ng, founder of DeepLearning.ai, believes the term “agent” once had a clear technical meaning. That changed when marketers and major tech companies began using it loosely to promote new AI capabilities.

The Risks and Opportunities of a Vague Definition

The lack of a standard definition presents both challenges and opportunities, according to Jim Rowan, head of AI at Deloitte. On one hand, it allows companies to shape AI agents to fit their specific needs. On the other, it can create “misaligned expectations” and make it harder to measure success.

“Without a standardized definition, at least within an organization, it becomes challenging to benchmark performance and ensure consistent outcomes,” Rowan said. The ambiguity could lead to confusion about what AI agents should deliver, making it difficult to track ROI or set clear project goals.

While a more standardized understanding would help businesses maximize their AI investments, history suggests that may not happen. If the industry’s struggle to define AI itself is any indication, it’s unlikely that we’ll see a universal definition of AI agents anytime soon—if ever.