What is Agentic AI

What is Agentic AI?

Agentic AI refers to a category of artificial intelligence systems designed to operate autonomously, making decisions and taking actions to achieve specific goals without the need for continuous human oversight. This advanced form of AI utilizes sophisticated reasoning and iterative planning to navigate complex, multi-step challenges, adapting to changing environments and circumstances through probabilistic reasoning. For a deeper understanding, you can explore our in-depth look at machine learning data catalogs.

What are the key features of Agentic AI?

Agentic AI systems possess several distinctive features that set them apart from traditional AI systems:

• Autonomy: Unlike traditional AI systems that often require human intervention, Agentic AI can function independently, making decisions based on the information available and the goals it is programmed to achieve.
• Sophisticated reasoning: It employs advanced algorithms that enable it to analyze situations, predict outcomes, and optimize actions, making it capable of handling intricate problems that may involve multiple variables and uncertainties.
• Adaptability: Agentic AI systems are designed to learn from their experiences, allowing them to adjust their strategies in response to new data or changes in their environment. This adaptability is crucial for effectively addressing dynamic challenges.

How does Agentic AI differ from other AI types?

One of the primary distinctions between Agentic AI and other forms of artificial intelligence, such as Generative AI, lies in their operational focus. While Generative AI is primarily concerned with creating content or generating outputs based on input data (such as text, images, or music), Agentic AI emphasizes autonomous action and decision-making. This fundamental difference shapes their applications and impacts across various industries. To understand more about the implications of AI in data governance, check out our insights on top trends in data governance for 2025.

What are the applications and use cases of Agentic AI?

Agentic AI has a wide range of potential applications across multiple sectors, including:

• Healthcare: Autonomous systems can assist in diagnosing diseases, managing patient care, and optimizing treatment plans based on real-time data analysis.
• Finance: In the financial sector, Agentic AI can automate trading, assess risks, and manage investment portfolios, improving efficiency and decision-making.
• Manufacturing: By optimizing supply chains and production processes, Agentic AI can enhance productivity and reduce waste.
• Customer service: AI-driven chatbots and virtual assistants can handle inquiries and provide support without human intervention, improving customer experiences.

What is the impact of Agentic AI on work and productivity?

The introduction of Agentic AI is poised to transform the workplace by automating routine tasks, enabling employees to focus on more strategic and creative endeavors. This shift could lead to increased productivity and efficiency, although it also raises questions about job displacement and the future of work. Organizations must navigate these challenges while leveraging the benefits of Agentic AI to enhance their operations. For insights on improving data quality in this context, consider reading about four ways to improve data quality.

What tools and platforms utilize Agentic AI?

Several companies and platforms are at the forefront of developing and implementing Agentic AI technologies, including:

• Microsoft: Known for integrating AI capabilities into its software solutions, Microsoft is exploring ways to enhance productivity through autonomous systems.
• IBM: IBM's AI initiatives focus on providing businesses with the tools needed to harness the power of Agentic AI for improved decision-making and operational efficiency.
• OpenAI: As a leader in AI research, OpenAI is exploring the potential of Agentic AI in various applications, pushing the boundaries of what autonomous systems can achieve.

What are the future implications of Agentic AI?

As interest in Agentic AI continues to grow, it is essential to understand its capabilities, applications, and implications across different fields. By exploring the nuances of this technology, organizations and individuals can better prepare for the transformative changes it may bring to the landscape of work and productivity. As we move forward, the dialogue surrounding Agentic AI will undoubtedly evolve, shaping our understanding of its role in the future of technology and society. For those interested in data intelligence, our glossary entry on data intelligence provides valuable insights.

For more in-depth insights, consider checking out the NVIDIA Blog, Harvard Business Review, and UiPath.

Who benefits from using Secoda?

Secoda is utilized by various stakeholders in the data management landscape:

• Data teams: Companies like Remitly, Cardinal Health, and Vanta use Secoda to automate data governance at scale and deliver secure, trusted data.
• Data leaders and innovators: Data leaders leverage Secoda to streamline data management, enhance governance, and improve productivity.
• Enterprise data teams: Secoda is used by enterprise data teams worldwide to manage, monitor, and govern their company data effectively.