The AI revolution is charging forward, and major tech companies are placing big bets on a new concept: AI agents. OpenAI CEO Sam Altman has confidently stated that AI agents will “join the workforce” this year. Microsoft’s Satya Nadella has suggested that AI agents will replace certain knowledge work, while Salesforce’s Marc Benioff envisions his company as the “number one provider of digital labor in the world.”

Yet despite these ambitious proclamations, there remains a glaring issue, no one can seem to agree on what an AI agent actually is.

The definition of “AI agent” has become muddled, with each company offering its own interpretation. OpenAI describes them as systems capable of independently performing tasks on behalf of users, while Microsoft draws a line between AI assistants and agents, positioning the latter as “new apps” with specialized expertise.

This lack of consensus is leading to confusion in the market, making it difficult for businesses and consumers alike to understand the true capabilities and limitations of AI agents.

Why It Matters: Without a clear definition, businesses risk investing in AI technologies that don’t align with their needs. The ambiguity also raises concerns about marketing hype, making it harder for enterprises to evaluate and compare AI solutions effectively.

• Diverging Definitions Create Market Confusion: OpenAI, Microsoft, Google, and others each define AI agents differently, making it difficult for businesses to make necessary decisions. Without a common framework, organizations struggle to assess AI agent capabilities and determine their practical value.

• Marketing vs. Technical Reality: Industry experts, including AI pioneer Andrew Ng, have pointed out that marketing teams have co-opted the term, leading to inconsistencies in its usage. This divergence raises concerns that AI agents could become another overused buzzword rather than a truly transformative technology.

• Unmet Expectations and ROI Challenges: Companies investing in AI agent technology need clarity on what they’re purchasing, yet the lack of a standardized definition makes it difficult to measure ROI. When organizations expect fully autonomous AI systems but receive limited-functionality assistants, it leads to frustration and diminished trust in AI-powered solutions.

• Flexibility vs. Standardization: On one hand, the fluid definition of AI agents allows companies to innovate and create tailored solutions for different industries. On the other, it creates inconsistencies in how they are built, evaluated, and deployed, making it challenging to establish industry-wide benchmarks for success. Without a clear framework, businesses may struggle to ensure that AI agents deliver reliable and consistent outcomes.

• The Future Remains Uncertain: Given the history of AI-related jargon, there is little indication that the industry will ever settle on a single definition for AI agents. Much like terms such as “artificial general intelligence” (AGI) and “multimodal AI,” the meaning of AI agents will likely continue to evolve. This ongoing ambiguity could either drive greater innovation or further complicate adoption, leaving businesses in a state of uncertainty regarding AI’s true potential.

Go Deeper -> No one knows what the hell an AI agent is – TechCrunch