We are currently living in the 2025 Identity Security landscape and its complicated phase of relationship with AI. The industry surveys reveal some of the key identity security risks every year. This year, AI delivered the trifecta- attack weapon, defense tool, and risk multiplier. Cybercriminals are leveraging AI to inject phishing emails and AI-driven deepfakes, which can mimic even the pro users. On the other side, businesses embracing AI and large language models now need to strike a balance between the innovation rewards and the increasingly complicated and exposed attack surface. AI is dependent on extensive data that not only increases the risk of unauthorized access but also makes the AI models vulnerable to tampering. However, AI is only a slice of a cake. There is a vast explosion of privilege sprawl. When asked, professionals. 59% of them predicted that machine identities will be a key factor behind the identity growth, outperforming AI and LLMs. Meanwhile, the security teams with work overload find shrinking visibility across their cloud settings. Do not worry, this article is to help you navigate such changes. Let’s find out the top identity security risks and the cybersecurity investment that should not be ignored.
Top 3 Identity Security Risks
Defender, Attacker, and Risky New Hire
AI-powered efficiency is a table turner. Around 94% of the respondents utilize AI to improve their identity security strategies, and almost 72% of the working professionals regularly use the tools to do their job. However, with the growing use of AI within organizations, they can also increase the risks. The model itself needs a large amount of data, spawns new machine identities and poses a large number of risks that most legacy controls are not designed to manage.
AI and LLMs are expected to be the major creators of new identities with privileged and confidential data in 2025. Surprisingly, although the businesses cite AI as the best creator of new identities with privileged access, 68% of the respondents do not ensure the necessary identity security controls to effectively manage these technologies.
There is also an increasing issue of Shadow AI, which is an unknown AI tool with no record of the number of people using it. Around 47% of the people cite that they cannot fully track this budding issue. Criminals are not just using AI as a weapon to automate phishing, bypass measures, and replicate users with increasing accuracy; they are also exploring new ways to manipulate AI models into jailbreaking or secretly gathering and sending the personal info of users and their payment details.
AI Agent Dilemma
Let’s support the idea that intelligent, autonomous tools can reduce 15% of your daily jobs. This is what decision-makers expect AI agents to do by 2028. Unlike static machine identities, the AI agents can perceive, consider, and act on the preset goals. Although this seems like a great opportunity for the businesses, you may not fall prey to it. This could be a serious concern about the sensitive information and data that can block its wider adoption.
AI agents can be easily fooled into executing prompts, disclosing data, and permitting access without human intervention. Most identity and access management systems are not immune to dealing with the authentication, privileged access, and lifecycle controls, which pose risk to thousands of self-operating entities.
To equip the organizations against these risks, clear and consistent government approaches that align AI behaviour with security policy are essential. This can prevent ‘scale’ from becoming ‘sprawl’.
Unmanaged Growth of Machine Identities
With the rising adoption of AI, the number of machine identities is also increasing. These identities validate workloads, automate jobs, and support contemporary ecosystems. However, the conventional security tools often miss these identities. Unfortunately, there are a lot of them, and not abundant but privileged. Machine identities have become an emerging risk in terms of the most undermined, unknown identities across the IT landscape.
Surprisingly, 88% of the respondents still believe these ‘privileged users’ as human beings. This is very risky, mainly when 42% of machine identities have access to sensitive information. These unidentified, unmanaged machine identities show an increasing area of sophisticated attack surface.
Silos in Your Security Foundation
With the growing number of organizations scaled, merged, and modernized, identity controls were often fragmented. Different teams utilize different tools to solve this issue in slightly incompatible ways. The outcome is usually a patchwork of overlapping technologies and misaligned policies. Even though 94% of people report the deployment of tools that automatically safeguard and track the cloud sessions, around 49% are still uncertain about who has access to what. Unsurprisingly, 70% of security leaders find identity silos as the primary source of organizational threats.
Integration remains a major hurdle, and 68% of the respondents cite that the misalignment between identity and security systems affects threat identification. The results are not just operational. Silos intricate compliance and increase the cybersecurity investment premiums. The majority of people report the increasing demands around security controls, and insurers are now enforcing less privilege more actively.
How to Secure AI Agents?
AI is now an integral part of modern business. However, safer adoption relies on the security teams and their proactive approach towards it.
Secure development: Make sure you filter out training data and adopt strong coding principles
Secure deployment: Protect AI systems in production with strong identity controls
Secure use: Leverage AI to identity security strategies from scratch and not as an afterthought.
Machines that act like humans need both human and machine identity security controls. Lack of these double-layered protections poses a risk to the identity chaos of early robotic process automation (RPA) integrations, where impersonation, over-privileged access, and lack of governance create an opportunity for attacker exploitation.
To strengthen your expertise in this field, consider enrolling in the “AI in Cybersecurity: Predictive Threat Detection” course offered by Holistique Training.
Promising Role of Identity Governance and Administration (IGA)
The report reveals that IGA is one of the top strategic identity cybersecurity investments that you must not miss. IGA plays an important role by centralizing and automating identity management across on-premise, cloud, and hybrid settings, and helps overcome fragmented legacy systems.
Together with privileged access management, IGA ensures consistent policies, backs least privilege access, and aligns with Zero Trust approaches. IGA also minimizes manual work, removes latency, and helps firms address regulatory demands without impacting the security teams in the process.
What’s Ahead?
Although AI continues to pose a threat, robust identity security is important to control it. At its essence, almost all attacks are identity. Despite the strategy of the attackers, the endgame remains the same- gain identity control. The entities thus should focus on cybersecurity investment that builds a strong immune system. Lastly, securing every human and machine identity with a comprehensive, end-to-end strategy is the best way to navigate through the complexity.
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