Agentic AI

Agentic AI represents a significant advancement in artificial intelligence, offering autonomous decision-making capabilities that can transform various industries. However, its integration introduces specific security challenges, particularly concerning Non-Human Identities (NHI). This article explores the concept of Agentic AI, its applications, adoption trends, and associated NHI security risks.

What is Agentic AI?

Agentic AI refers to systems or programs capable of autonomously performing tasks on behalf of users or other systems by designing their workflows and utilizing available tools. Unlike traditional AI models that require explicit instructions, Agentic AI systems can plan, execute, and achieve goals with minimal human supervision, effectively acting as independent agents.

Purposes and applications of Agentic AI

The primary purpose of Agentic AI is to enhance efficiency and productivity by automating complex, multi-step processes. Key applications include:

• Business process automation: Streamlining operations by autonomously handling tasks such as data analysis, customer service interactions, and supply chain management.
• Software development assistance: Assisting developers by generating code snippets, debugging, and testing, thereby accelerating the development cycle.
• Personal assistants: Managing schedules, emails, and other administrative tasks without continuous human input.

These applications enable organizations to focus on strategic initiatives by delegating routine tasks to intelligent agents.

Adoption statistics and future outlook

The adoption of Agentic AI is on an upward trajectory. Deloitte predicts that by 2025, 25% of companies utilizing generative AI will initiate Agentic AI pilots or proofs of concept, with this figure rising to 50% by 2027.

This growth is driven by the technology’s potential to automate multi-step processes across various business functions, thereby enhancing productivity.

Investments in Agentic AI are also increasing. Over the past two years, more than $2 billion has been invested in Agentic AI startups, particularly those targeting enterprise markets.

Established technology companies are developing their own Agentic AI solutions, indicating a robust future for this technology.

NHI security risks associated with Agentic AI

The integration of Agentic AI poses unique challenges in Non-Human Identity security, primarily due to how these AI agents connect to systems and execute actions autonomously. These agents rely heavily on NHIs, such as API keys, service accounts, and other forms of machine identities, to interface with enterprise systems, databases, and third-party applications. This dependency introduces several security risks:

Expanded attack surface

Agentic AI systems frequently require extensive permissions to operate across multiple environments, such as cloud platforms, on-premises systems, and external APIs. This broad access increases the attack surface, creating more opportunities for malicious actors to exploit vulnerabilities in the connected NHIs.

Credential mismanagement

AI agents often require credentials for authentication to execute tasks like accessing sensitive databases or invoking APIs. These credentials, if hard-coded, stored insecurely, or shared across multiple systems, can be compromised, leading to unauthorized access or privilege escalation.

Unmonitored and orphaned NHIs

As agents are created or decommissioned, their associated NHIs may remain active and unmonitored. These “orphaned” NHIs are high-value targets for attackers, as they often retain elevated privileges without ongoing oversight, making them a persistent security risk.

Supply chain risks

Many Agentic AI systems depend on third-party APIs or external tools to perform their functions. When these external systems are accessed using NHIs, vulnerabilities in the supply chain can propagate into an organization’s infrastructure, creating indirect but severe risks.

Inadequate visibility and control

Traditional identity governance tools often lack the ability to provide granular visibility into how NHIs interact with systems. This blind spot makes it challenging to detect anomalies, such as an AI agent using an NHI to perform unusual or unauthorized activities.

Astrix was built to secure and manage NHIs, especially in interconnected, AI-led environments. Learn more here.