The competition among tech giants is no longer just about building more powerful AI models; it has extended to the vocabulary used to describe the next generation of this technology.
As the industry moves from chatbots that mainly answer users' questions toward systems that can plan, use various tools, and perform multi-step tasks, new terms such as “AI agent,” “artificial general intelligence” or AGI, and “superintelligence” have entered the tech lexicon.
These words are not merely technical terms. Tech companies use them to explain products, future visions, and development roadmaps to users, developers, and investors. For that reason, a change in the industry's vocabulary can also signal a shift in its focus.
From chatbots to AI agents
The first generation of the new AI wave was largely focused on models that could understand text and images, generate content, and answer users' questions. But the next stage of development has moved toward systems that do more than respond: they can execute multiple steps in sequence to achieve a goal.
This is where the concept of an AI agent becomes important. Agents can use software tools, interact with various apps and services, obtain information from diverse sources, and choose the next action based on the outcome of each step.
As a result, the main difference from a simple chatbot is that the focus shifts from “producing a response” to “getting things done.” Different companies invested more in such systems in 2026, and AI agents became one of the main pillars of new products.
AGI; a term that still lacks a single definition
The term artificial general intelligence (AGI) describes a hypothetical stage of AI development in which a system can perform a very wide range of cognitive tasks, rather than being designed as a specialized tool for a specific application.
However, one major problem with AGI is that there is no single, agreed technical definition. Companies, researchers, and experts may have different criteria for determining when a system has reached AGI.
For this reason, AGI is not merely a technical concept, and its very definition has become part of the industry's competition and debates. For example, in 2026 even statements by executives of major tech companies about whether current-generation systems were close to or had even achieved AGI were controversial.
“Superintelligence” entered official U.S. usage
A more significant change in AI vocabulary occurred recently. On September 29, 2026, the Donald Trump administration issued an order titled “Beginning the Era of Superintelligence,” directing federal agencies to use “superintelligence” and the abbreviation SI in official communications and certain nonlegal documents instead of the terms “artificial intelligence” and “AI.”
This change is primarily linguistic and does not imply an immediate change in the legal definitions of the technology. According to an IAPP report, the new order keeps the scope of technologies called “superintelligence” under this framework aligned with the current legal definition of artificial intelligence in federal U.S. law.
Of course, “superintelligence” had been used previously in technical literature; but its common meaning differs from the new, broader official usage. In technical literature, superintelligence usually refers to a hypothetical system that surpasses humans across a wide range of cognitive abilities.
When words become part of the competition
As the technology advances, each new stage requires a term to distinguish it from the previous one. Generative models, AI agents, AGI, and superintelligence each attempt in their own way to convey an image of a different level of capability.
At the same time, not every term should be equated with a specific technical achievement. Words like “agent” can refer to different architectures, and there is still disagreement about precise definitions and criteria for AGI and superintelligence.
This issue becomes more important because industry vocabulary can influence users' and investors' perceptions of a product's actual capabilities. Therefore, when evaluating claims by tech companies, the distinction between branding, marketing terminology, and technical definition is significant.
Ultimately, the industry's changing language does not merely indicate name changes; it shows that the focus is shifting from building models that generate information toward systems that can use information, employ tools, and execute tasks in multi-step processes. Nevertheless, whether this path will ultimately lead to AGI or superintelligence and exactly how those concepts are defined remains a subject of research and disagreement in the industry.