Leveraging artificial intelligence (AI) in identity access management (IAM) is an effective way to improve business scalability, increase efficiency and reduce costs without compromising security and privacy in your organization. AI-powered IAM solutions can analyze behavioral patterns to detect and restrict security breaches, even before they attack your system. Considering the pace at which cyberattackers evolve in their strategies, it’s best to adopt cutting-edge technologies to protect your investments. Learn how to prepare for the impact of AI on IAM.

How Can We Expect AI to Affect the IAM Industry?

Here are five ways AI can impact the IAM industry:

  • Governance and administration: AI is expected to change and improve governance and administration by removing mundane tasks performed by humans, including access requisitions, provisioning and certification. Again, the data generated by AI can be used to develop effective policies to improve security and user experience.
  • Authentication approaches: Risk-based verification processes based on AI and machine learning (ML) can analyze user behavior and adapt to trends of security breaches. This flexible approach gives organizations a broader overview of the risks than the traditional rule-based methods.
  • Zero trust identity: A shift towards zero trust identity (ZTI) is almost inevitable, considering that most businesses are transitioning to hybrid work. AI-based IAM systems help provide seamless access and intervene with stepped-up identification when user identity is in doubt or blocks them when detected as fraudulent. 
  • User behavior analytics: The current IAM industry prioritizes user behavior because it helps predict and detect anomalies — AI performs this task efficiently. Identifying potential security threats or compliance violations is becoming straightforward with improved responses.
  • Personal data in token access: Most IAM solutions use tokens to permit and deny access, which typically requires user information. AI-based IAM platforms leverage behavior information, eliminating the need for personal data and enhancing user privacy.

Benefits of AI in IAM

Benefits of AI In IAM

Here are five benefits of AI in IAM:

1. Detect Cyber Threats

AI can improve security by detecting anomalies in user behavior. This ability can help security professionals identify threats before they breach the system and cause damage. The approach is practical and generally reliable compared to other detection methods. Advanced detection explains why AI-based cybersecurity solutions are gaining traction among top organizations. Many executives have already implemented AI for security capabilities, and even more are evaluating implementation.

AI-based IAM systems can use behavioral analysis to examine and establish standard activity patterns, including user login trends, IP addresses and actions. The system may flag deviations as suspicious activities and request further verification protocols such as risk-based and multifactor authentication.

2. Predict Cyberattacks

AI-based IAM tools have advanced risk-sensing and threat-prediction capabilities. The approach is more efficient and fluid than manual human checks and restrictive rule-based algorithms, considering cyberattackers change their strategies regularly. The system can identify new anomalies, assess the risks and create future risk predictions. 

Predicting cyber threats allows security analysts to prepare and implement security measures ahead of time. This can help the organization reduce downtime, saving time and money. Again, AI-based predictions in IAM provide more accurate results and reliable data to simplify decision-making. 

Besides predicting security attacks, AI-based IAM systems are generally accurate. Traditional signature-based antivirus software uses a database of known signatures to identify threats, which is limited to detecting malware within that category. By studying the behaviors of files and programs, AI can detect subtle patterns of known and unknown threats.

3. Enhance Threat Response 

Detecting and predicting security threats are only helpful when the necessary actions are taken. AI-powered IAM systems can send real-time alerts and notifications to security teams, allowing them to respond quickly. The alert may provide detailed information about the nature of the attack, its potential impact and recommended actions to remedy the anomaly. These actionable insights can help security professionals quickly make informed and effective decisions to mitigate risks.

AI can also automate certain aspects of the response process, including blocking malicious activities, isolating affected systems and initiating incident response workflows. Small and large companies can reduce the window opportunity for attackers and minimize the impacts of security breaches. 

4. Personalize and Secure User Experience

User experience and engagement have changed since the integration of AI in cybersecurity. AI-powered solutions allow businesses to deliver individualized and seamless experiences without compromising security. For example, risk-based or adaptive authentication leverages ML algorithms to constantly evaluate user behavior and context to determine the risk level associated with a user’s action. This development enables the system to modify the verification requirements and prompt further authentication factors depending on the result of the assessment. 

5. Enhance Compliance

Organizations must comply with security and privacy laws to mitigate legal and financial consequences. An integral part of IAM is restricting access to information to selected people, which can be challenging to manage manually. Security professionals can now integrate AI and ML to monitor, learn user trends and apply precise access limitations. In addition to biometric authentication, security experts can use sight and speech recognition for authentication purposes. These technological advancements help reduce breaches and help businesses stay compliant.

Challenges That Arise With AI in IAM

Here are the two primary challenges of AI in IAM:

  • Bias: AI models are only as good as the data they are trained on. Therefore, systems fed with biased data will generally generate skewed outcomes. This challenge may be resolved by listening to feedback, reviewing training data and maintaining quality assurance.
  • Advanced evasion techniques: Cybersecurity threats are becoming more sophisticated, with attackers using AI tools to create adaptable malware. This makes it vital to use diverse and up-to-date data to help detect and respond to emerging threats.

Best Practice for AI in IAM

Here are five tips when preparing your network for AI:

  • Outline your business: AI models efficiently solve specific problems, so begin by identifying areas in your IAM that need support. This allows you to add value, increase your return on investment and reduce risks associated with modern technology. 
  • Gather data: AI models are data-hungry. The more quality data your feed the system, the better the outcome. Collect and prepare information related to access logs, user activity and other relevant data and ensure it is accurate, up-to-date and complete.
  • Maintain human oversight: While AI can automate cybersecurity tasks, human experience and judgment remain essential. Take a phased approach when integrating AI into your IAM, starting with a pilot project designed for specific purposes.
  • Develop a data governance framework: Develop a comprehensive data governance framework, considering areas such as access control and auditing procedures. This helps you implement effective and secure structures with improved user experience.
  • Choose a reliable IAM solutions provider: Partner with an IAM solutions provider that is committed to understanding your business and has an excellent track record. The goal is to choose AI-based IAM solutions that meet specific needs. A one-size-fits-all approach is likely to fail. 

Contact Optimal IdM for Your IAM Solutions

Optimal IdM is a global provider of innovative IAM solutions at competitive pricing. We partner with clients in various industries to deliver comprehensive and fully personalized solutions according to their needs and industry standards. We aim to help improve business scalability and agility. Contact us now to learn how we can help you!

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Tags

  • The database in which all of your organization’s sensitive identity data is stored.
  • A digital ledger in which digital transactions are recorded chronologically and publicly.
  • Securely managing customer identity and profile data, and controlling customer access to applications and services.
  • The means of linking a person's electronic identity and attributes, stored across multiple distinct identity management systems.
  • A legal framework that sets guidelines for the collection and processing of personal information of individuals within the EU.
  • The policy-based centralized orchestration of user identity management and access control.
  • An authentication infrastructure that is built, hosted and managed by a third-party service provider.
  • A security system that requires more than one method of authentication from independent categories of credentials to verify the user's identity for a login or other transaction.
  • A global provider of innovative and affordable identity access management solutions. 
  • Managing and auditing account and data access by privileged users.
  • Tools and technologies for controlling user access to critical information within an organization.
  • An authentication process that allows a user to access multiple applications with one set of login credentials.