Page 1 GAO-25-108519 AI Agents
Science, Technology Assessment,
and Analytics
SCIENCE & TECH SPOTLIGHT:
-25-108519, September 2025
WHY THIS MATTERS
Agents are AI systems that can not only create content but
also operate autonomously to accomplish complex tasks and
make instantaneous decisions in response to changing
conditions. Agents have the potential to reshape the
workplace, with advocates emphasizing that agents could
increase efficiency in areas such as data entry and resource
management. However, policymakers are concerned about
the potential for misuse and unintended consequences, as
well as job displacement resulting from agent implementation.
KEY TAKEAWAYS
» Current AI agents are limited to specific purposes, such
as software development and autonomous vehicles.
» As AI becomes more agentic, it will be able to accomplish
more complex tasks across various fields.
» Policymakers face questions about how to prevent
misuse and unintended consequences of AI agents.
THE TECHNOLOGY
What is it? Agentic artificial intelligence (AI) builds upon the
capabilities of generative AI to not just create content, but also
to make and adjust plans when the actions required to
accomplish a goal are not clearly defined by a user. Unlike
generative AI, AI agents can interact with their environment to
perform tasks for users. For example, while a customer service
generative AI system can respond to order status inquiries, an
AI agent could interact with other software systems to process a
return or exchange, or other complex customer issues.
There is no universally agreed upon definition of an AI agent.
However, there are properties that can help determine AI
systems that are more agentic (see fig. 1).
Figure 1. Properties that Characterize AI Systems as More Agentic
How does it work?
AI agents collect data, evaluate the data, and then take action.
Sense. Agents collect data from their environment. For
example, self-driving vehicles use sensors to scan their
surroundings for obstacles such as pedestrians, and
customer service AI agents collect text or voice inputs.
Process. Agents rely on algorithms, models, and rules to
evaluate inputs, process data, and determine the next
course of action. For example, a self-driving vehicle
processes data collected from its surroundings to plan a
safe path to a destination.
Act. Agents take action to achieve a goal based on their
analysis, such as steering a vehicle or handling customer
service requests, like ordering replacement parts.
