Sectona at Infosecurity Europe 2025 | June 3–5 | ExCeL London
Stop by our booth (Stand C 95) for live demo of Sectona’s Modern Infrastructure Access Platform
AI Agent Is Getting Smarter. Is Your Security Keeping Up?
How often do you use AI in your day-to-day work? What about across your organisation?
The answer varies from person to person and business to business. One thing is certain, though: AI has become a regular part of how most people work. Whether it’s drafting emails, writing code, analysing data, or automating repetitive tasks, nearly everyone uses AI in one way or another.
As AI adoption accelerates, the way in which organisations get work done is evolving rapidly. In fact, Gartner predicts that by 2030, AI-native development platforms will enable 80% of organisations to transform large software engineering teams into smaller and more agile teams augmented by AI.
That brings us to an important question: What comes to mind when you hear the term ”AI agent”?
Many people assume AI agents are simply AI chatbots. While they share some similarities, they differ significantly in their capabilities.
Traditional AI chatbots are designed primarily to answer questions. They rely on user prompts, typically use a single AI model, generate text-based responses, and have limited memory or contextual awareness.
AI agents, on the other hand, go far beyond answering questions. They can perform tasks autonomously, proactively take actions, and combine AI models with tools, APIs, and workflows. They can interact with databases, enterprise applications, and external services while maintaining memory and context across interactions. This enables them to make informed decisions, execute multi-step tasks, and adapt to changing circumstances with minimal human intervention.
Simply put, an AI agent is software that can perceive information, make decisions, and take actions autonomously to achieve specific goals. It can plan tasks, use tools, retain information, and continuously adapt its behaviour based on new inputs and changing conditions.
As organisations increasingly integrate AI agents into critical business processes, the security implications become impossible to ignore. As AI agents gain access to enterprise applications, data, and infrastructure, they effectively become new digital actors within the organisation.
This shift introduces a fundamental security challenge: How do you secure an entity that can think, decide, and act on your behalf?
In this blog, we’ll explore the risks associated with AI agents and discuss how organisations can mitigate those risks by treating AI agents as digital identities, applying the same governance, authentication, authorisation, and lifecycle management principles used to secure human and machine identities.
How Do Familiar Patterns Evolve in AI?
Familiar patterns are repeated characteristics or relationships that AI identifies during its training. These patterns help AI make predictions or perform specific tasks. Familiar patterns include recognising faces in photographs, detecting spam messages or emails, predicting customer preferences based on previous purchases, understanding language patterns, and identifying fraudulent financial transactions based on unusual behaviours.
How do these patterns evolve?
- Data collection
- Pattern recognition during training
- Learning from feedback
- Generalisation
- Continuous improvement
The quality of these evolving patterns depends on reliable data, well-designed algorithms, and responsible human oversight. As AI continues to advance, understanding how patterns evolve will remain essential for developing systems that are accurate, fair, and trustworthy.
Also Read: Securing Identities in the Age of AI
How Can You Mitigate AI Risks?
AI has integrated into businesses such as healthcare, finance, education, and government.
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Therefore, it becomes important to identify and mitigate the risks associated with AI’s use. Mitigating AI risks involves implementing technical, legal, and ethical measures to make sure that AI systems are safe, fair, transparent, and accountable. When you treat an AI agent as an identity, it holds the person who had access to the particular action accountable.
Here’s how you can mitigate AI risks.
- Ensure transparency
- Maintain human oversight
- Improve data quality
- Reduce bias and promote fairness
- Protect privacy and data security
- Conduct regular AI audits
- Establish clear governance
- Comply with laws and regulations
- Educate users and employees
As AI becomes more autonomous, many of the security concerns they introduce mirror familiar identity and access management patterns. The difference between them is that “user” is no longer a human; it is an intelligent agent capable of making decisions and taking actions on their own.
How Does Large Language Model Access Become Misuse?
Large Language Model (LLM) is a technology that is built to tell its users all the information and data it has learned. That’s why it is important not to share confidential or sensitive information with it to avoid the data being leaked. Additionally, malicious data training can be used for biased output or to attack the application. Hence, having a robust understanding of data usage in the application is the key to understanding the security of an LLM application.
Here’s how an LLM application gets compromised:
- Supply chain attacks
- Payloads in model files
- Malicious adapters
- Data poisoning
- Backdoor attacks
- Direct model compromise
Securing an LLM application requires protecting every stage of the AI lifecycle, including data collection, model training, fine-tuning, deployment, inference, and ongoing monitoring.
Also Read: Modern Security Beyond Traditional DevSecOps Controls
Why Is It Important to Recognise AI as Identity?
You cannot hold AI accountable if something goes wrong. When you recognise AI as an Identity, you can hold the person who approved the workflow, the person who wrote the code, or the person who had access to the same.
AI has become an important part of human life, influencing how people communicate, work, create content, learn, and make decisions. Nowadays, most modern AI systems can generate realistic texts, images, videos, and engage in human ways during conversations. With the increasing popularity of AI, it will be important to recognise an AI agent as an identity and people should be notified that they are interacting with an AI system rather than a human.
When it comes to recognising AI systems as identities, it doesn’t mean giving AI systems rights like humans, emotions, or legal parenthood. It means acknowledging AI as a separate category of technology that has unique capabilities, limitations, and responsibilities.
Here’s why you need to identify AI agents as identities:
- Promotes Transparency:
Transparency is one of the key factors for recognising an AI as an identity. Users should always know whether they are interacting with an AI agent or a human. Transparency prevents deception and ensures that AI is used honestly in customer service, education, healthcare, journalism, and social media. - Ensures Accountability:
Recognising AI as an identifiable system helps establish accountability. AI can make mistakes, generate biased outcomes, and produce inaccurate information. When AI systems are clearly identified, it becomes easier to determine who is responsible for their actions, whether it is the developer, the company that deployed the AI, or another responsible organisation. - Encourages Ethical AI Development:
Ethical AI development requires fairness, honesty, respect for users, and responsible use of technology. Recognising an AI agent as an identity supports these ethical principles by ensuring users know exactly when the AI is involved in their usual tasks or decision-making.
Clear identification ensures that no unethical practices, such as impersonating humans, manipulating public opinions, and creating fake identities online. - Supports Legal and Regulatory Compliance:
As the usage of AI is increasing, government and international organisations are developing laws and guidelines to regulate AI. Many proposed regulations require companies to disclose when AI is being used, especially in the high-risk sectors, such as education, finance, healthcare, law enforcement, and elections.
Recognising AI as an identifiable system helps organisations comply with these regulations and demonstrates responsible governance.
How Can Sectona PAM Help in Recognising AI Agent as an Identity?
As AI agents evolve from passive assistants to autonomous decision-makers, they require the same identity-centric security controls that are traditionally reserved for privileged users. Instead of relying on shared credentials or long-lived API keys, every AI agent should have a unique and governed identity with clearly defined permissions and accountability.
Sectona’s modern infrastructure access platform is well-positioned to support this approach by applying identity-first Privileged Access Management principles to both human and machine identities.
Here’s how Sectona PAM can help in recognising AI agents as identities:
- Assigning Unique Identity to AI Systems
Treats every AI agent as a distinct digital identity instead of a shared service or application, enabling granular governance and accountability. - Strengthens Authentication and Credential Security
Secures passwords, API keys, tokens, SSH keys, and other secrets in a centralised vault, with automated rotation and controlled access to prevent credential exposure. - Supports Regulatory Compliance
Helps organisations meet compliance requirements by enforcing access controls, maintaining detailed audit logs, managing privileged credentials, and demonstrating governance over machine identities.
Identity Is the New Security Parameter
As AI agents become more autonomous, they are no longer just software executing predefined instructions. They are active participants interacting with critical systems, sensitive data, and privileged resources. This shift demands a fundamental change in how organisations approach AI security.
Instead of treating AI agents as applications, they must be recognised and governed as identities. This identity-first control strengthens security and improves accountability, governance, and compliance in increasingly AI-driven environments. Organisations that embed identity-centric security into their AI strategy will be better equipped to innovate confidently while staying resilient against evolving cyber threats. With a modern privileged access management solution like Sectona, businesses can extend proven identity and access controls to AI agents.
If you want to learn more about Sectona PAM, feel free to reach out to us or schedule a demo.
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