For many organisations, Identity & Access Management is a critical weapon in their cyber security battle. It is a great and robust solution to mitigate against data breaches, as well as manage the risks that come with remote working and Bringing Your Own Device – BYOD. IAM is constantly evolving across critical functions including data security, authentication, synchronizing internal data, enabling consumer contact preference management and meeting privacy compliance requirements.

The importance of a clever and mature IAM strategy shouldn’t be underestimated. Deciding who should have access to what information is difficult for many businesses and this challenge leaves their systems vulnerable. According to a Forrester research report, 83% of organizations do not have a mature approach to IAM. The risk that these organizations meet problems with a data breach is twice as high compared to organizations that have their IAM strategy. The report also presents a direct correlation between smarter IAM approaches and reduced security risk, improved productivity, increased privileged activity management and greatly reduced financial loss.

What is the Approach to Artificial Intelligence in IAM?


In the past several years, Machine Learning successfully develops due to its unique features like adaptability, scalability and ability to handle unknown challenges and to reduce human effort and intervention. AI and Machine Learning technologies could be a significant support for effective IAM. These trendy technologies could facilitate enterprises mature from excessively technical access management to access management that’s understandable on all levels.

Modern technologies provide ways to learn new insights and automate processes, which significantly speeds up the existing IAM compliance controls. They can detect anomalies and potential threats, without the need for a large team of security experts. This gives employees (technical and non-technical) the information needed to make correct decisions. Such progress is crucial, especially in the area of anti-money laundering and fraud detection, but also in the area of combating insider threats. That’s why it could be said that AI can serve as a lever to improve the enterprises’ IAM workflow and that ability makes it increasingly important in cybersecurity and Identity and Access Management.

  • AI monitoring and increased visibility

As business systems become more interconnected the need for seamless, continuous, and accurate access to information will become increasingly important. For that reason, AI advanced authentication systems will play a huge role, especially when collecting and analysing the information much faster than humans. Working within a user’s access permissions, AI systems could constantly monitor users as they move around the network, but they could also monitor any unusual, irrational or variable behaviour. They could detect whether users are trying to access a part of the system they wouldn’t normally or downloading more documents than they generally would.

  • Automation and Flexibility

Because AI monitors the details of users’ actions, it’s possible to automate authentication for low-risk access situations. In this way it can offload some of the burden of IAM administration and can prevent the “security fatigue” among users. AI is capable of looking at the total set of circumstances surrounding access requests including time, device type, location and resources being requested.

Considering these details, before granting network access, it makes IAM contextual and granular and can control potential problems caused by improper provisioning or deprovisioning. AI-powered systems are able to apply appropriate IAM policies to any access request based on needs and circumstances, so that the IT department doesn’t have to waste time figuring out the basics of “least privilege” for every use case.

  • More effective regulatory compliance

Enterprise software applications which integrate AI can increase the efficiency and effectiveness of regulatory compliance programs across a variety of industries. Many enterprises believe that complying with security and privacy regulations is sufficient to keep hackers away, but that’s not enough to meet the security needs. The basics of compliance means ensuring information is only accessed by those who need it and rejecting everyone else.

Implementing compliance rules for new security laws can be a burden, and noncompliance is a common practice. The flexible, adaptable nature of AI-powered IAM is useful in these situations. AI and ML constantly monitor traffic, learn behaviours and apply granular access controls, so enterprises face less of a challenge when enforcing security protocols, and it becomes difficult for hackers to get any use out of stolen credentials.

Nowadays hackers are getting better and braver in infiltrating networks. Detecting unauthorized access attempts requires detailed scrutiny which could not be performed precisely by human monitoring. This is the reason why companies rely on artificial intelligence technologies to implement better IAM practices for improving access security and maintaining the integrity of user identities.When AI and ML are performed with the appropriate monitoring and reporting tools, it becomes possible to visualize network access and reduce overall breach risk using intelligent and adaptable IAM policies.In the highly competitive world of global finance and regulated industries, investing in AI and ML can increase the accuracy and efficiency of compliance systems, as well.