The AI Agent market is expected to have a promising future and is anticipated to achieve robust growth in the coming years.
According to a report by MarketsandMarkets, the autonomous intelligent agent market size is projected to surge from $345 million in 2019 to $2.992 billion by 2024, with a CAGR of 54%, and is expected to exceed $28.5 billion by 2028. It is believed that they will play a significant role in technological advancements, market growth, human-computer interaction, social structure transformation, and full automation.
Currently, we categorize AI Agents into two main types:
- Autonomous Intelligent Agents, striving to automate complex processes. When given an objective by an autonomous intelligent agent, they can independently create tasks, complete tasks, generate new tasks, reprioritize the task list, accomplish new primary tasks, and continuously repeat this process until the objective is achieved. High accuracy is required, thus external tools are more needed to mitigate the negative impact of large model uncertainty.
- Agent Simulations, aiming to be more human-like and credible. They are divided into agents that emphasize emotional intelligence and those that emphasize interaction. The latter is often in a multi-agent environment, where scenarios and capabilities beyond the designer's planning may emerge. The uncertainty generated by large models instead becomes an advantage, and diversity makes it a promising component of AIGC (AI-Generated Content).
The AI Agent market is expected to have a promising future and is anticipated to achieve robust growth in the coming years.
According to a report by MarketsandMarkets, the autonomous intelligent agent market size is projected to surge from $345 million in 2019 to $2.992 billion by 2024, with a CAGR of 54%, and is expected to exceed $28.5 billion by 2028. It is believed that they will play a significant role in technological advancements, market growth, human-computer interaction, social structure transformation, and full automation.
Currently, we categorize AI Agents into two main types:
- Autonomous Intelligent Agents, striving to automate complex processes. When given an objective by an autonomous intelligent agent, they can independently create tasks, complete tasks, generate new tasks, reprioritize the task list, accomplish new primary tasks, and continuously repeat this process until the objective is achieved. High accuracy is required, thus external tools are more needed to mitigate the negative impact of large model uncertainty.
- Agent Simulations, aiming to be more human-like and credible. They are divided into agents that emphasize emotional intelligence and those that emphasize interaction. The latter is often in a multi-agent environment, where scenarios and capabilities beyond the designer's planning may emerge. The uncertainty generated by large models instead becomes an advantage, and diversity makes it a promising component of AIGC (AI-Generated Content).
Appreciate the breakdown.