@Vupl,
Expectations for AI run high across industries, company sizes, and geography. While most executives have not yet seen substantial effects from AI, they clearly expect to in the next five years. Across all organizations, only 14% of respondents believe that AI is currently having a large effect (a lot or to a great extent) on their organization’s offerings. However, 63% expect to see these effects within just five years.
The modern organization is made up of a mixture of human and non-human identities. Each user - whether that be an employee or a form of technology that can act independently and make intelligent decisions on behalf of people such as a bot or code – is linked to an identity. Having to manage each individual identity, remember what is linked to each, and know which identity is allowed to know specific information involves a lot of manual processing, and that’s productivity and efficiency down the drain.
Simply put, you can’t stop what you can’t see. As businesses continue to digitally transform with added technology and systems in place, enterprises will become more complex and naturally create more tasks to ensure compliance. The onboarding, managing of users, and review of certifications – it’s time-consuming. Pair that with a workforce of hundreds or even thousands, and it quickly becomes impossible.
With the help of AI and ML, organizations can make identity more intelligent and autonomous through predictive identity – the idea that user access needs can be anticipated based on an identity profile. Businesses can leverage ML to view historical access data across the organizations to assess its access behaviors and patterns. This will set a user activity benchmark and allow users to be categorized into base group models.
Behaviors that don’t fit the norm are flagged as potentially malicious and are constantly being watched by AI, removing oftentimes risky needles in a haystack. For example, as new data comes into the engine, AI can assess whether it seems abnormal in relation to what is usually seen across the peer group. Machine learning will filter the standard access and automatically certify an identity if it is deemed safe. A report may be generated to highlight any outliers so immediate action can be taken such as revoking additional access.