AI Agents: Last year’s most popular and impactful AI trend will continue in 2026
Jonnathan Resendiz
Assistant Professor; AI Incubator Faculty Director
Grand Rapids Community College
If you measure AI trends by simply watching commercials that appear during your favorite TV shows, you could clearly see that in 2025 the conversation shifted from simply mentioning AI to a more specific and newer concept: AI agents. Organizations have moved beyond experimenting with AI and saying they are thinking about incorporating it into their products, toward a tangible technology known as AI agents. This shift has come about not because agents generate better text or images, but because they represent an evolution of AI systems toward more autonomous, capable, and deeply integrated pipelines (Amazon Web Services [AWS], 2024; Google Cloud, 2024).
Unlike earlier AI tools that relied heavily on human prompts and oversight, AI agents are designed to pursue goals, make decisions, and act on behalf of users. This shift is reshaping how we think about AI and automation, and we believe that this trend will continue to dominate the conversation in 2026 as it is adopted across a wide range of industries, from cloud infrastructure and business operations to education and workforce development.
What Are AI Agents?
As mentioned earlier, in the early stages of generative AI—roughly one to two years after the release of OpenAI’s ChatGPT—AI was primarily a reactive tool. It performed tasks such as answering questions, generating content, or analyzing data and making predictions. In contrast, AI agents are expected to operate with significantly more independence and responsibility. In essence, AI agents are autonomous software systems that can observe their environment, reason about what they see, plan next steps, and act to achieve defined goals with minimal human intervention.
Rather than responding to a single prompt, agents can:
- Gather information from multiple sources
- Maintain context over time
- Decide what actions to take
- Execute tasks using tools, APIs, and workflows
- Adapt based on feedback or new information
This ability to reason, plan, and act is what separates agents from traditional AI models and makes them especially powerful in real-world environments (Google Cloud, 2024).
The Cloud as the Engine of Agentic AI
Just as the explosion of new AI research required massive amounts of data and computational power, this new era will require cloud infrastructure to succeed. Cloud infrastructure will play a critical role in the rapid adoption of AI agents. As an example, let’s explore some popular approaches.
Google Cloud
Google Cloud emphasizes AI agents that can process multimodal information, collaborate with tools, and coordinate complex workflows. According to Google, agents are designed to continuously observe, reason, and refine their actions, enabling advanced use cases such as workflow automation, analytics, and intelligent assistance across applications (Google Cloud, 2024).
AWS
AWS defines AI agents as systems that interact dynamically with their environment by collecting data, reasoning about outcomes, and independently selecting actions to achieve human-defined goals. By integrating agents with cloud services, APIs, and enterprise systems, AWS enables organizations to embed agentic AI directly into real operational workflows (AWS, 2024).
Across both platforms, the message is consistent: AI agents represent the next major interface between humans, data, and systems.
OpenAI and Microsoft
OpenAI and Microsoft have AI agents that combine reasoning with practical action inside their workflows. OpenAI focuses on models that can use tools, maintain memory, and execute multi-step plans, allowing agents to move beyond simple conversation and toward goal-driven behavior (OpenAI, 2024). Microsoft extends this capability through Azure AI Agent Service and Copilot Studio, embedding agents into Microsoft 365 and enterprise applications so they can coordinate documents, data, and business processes (Microsoft, 2024).
Beyond Chatbots: Agents That Act and Plan in Higher Education
To showcase an example of a powerful AI agent, it is helpful to highlight how this technology could be incorporated into higher education. Traditional chatbots, which are now common in many college systems, are very useful for answering FAQs; however, they are limited in the scope of their responses, and any potential follow-up they provide is often minimal or inconsistent. By contrast, because AI agents can reason over time and act autonomously, they could support students with long-term academic goals after being instantiated, rather than stopping at answering questions (Google Cloud, 2024). AI agents could function as academic partners or coaches that understand institutional requirements, track student progress, and initiate support to help students succeed.
In practice, these systems could:
- Monitor academic engagement and performance, identifying patterns that indicate progress or potential concern
- Suggest targeted interventions, such as tutoring, advising check-ins, or supplemental coursework
- Proactively remind students about critical deadlines, including registration, financial aid, and graduation milestones
- Recommend personalized study resources or practice exercises tailored to individual strengths and learning gaps
Looking Ahead
The most exciting aspect of AI agents is their potential as a tool for teaching AI itself. Imagine building curricula or learning experiences where students create agents in safe and secure environments to meet specific needs, allowing those agents to become active partners in their education. By enabling systems that can think, plan, and act with purpose, agents are reshaping how organizations operate, how students navigate education, and how humans collaborate with intelligent technology.
The question is no longer whether AI agents will shape the future, but how thoughtfully we choose to integrate them into our lives.
References
Amazon Web Services. (2024). What are AI agents? https://aws.amazon.com/what-is/ai-agents/
Google Cloud. (2024). What are AI agents? https://cloud.google.com/discover/what-are-ai-agents/
Microsoft. (2024). Azure AI Agent Service and Copilot Studio overview. https://learn.microsoft.com/azure/ai-services/agents/overview
OpenAI. (2024). Introduction to the Assistants API and agent capabilities. https://platform.openai.com/docs/assistants/overview