Veni, Vidi, Vici: How AI will Shape the Future of IGA

Everyone, I hope you've been enjoying AAC so far. I'm Christian Kovan, the director of product management, temp Power id, and I'm thrilled to to be here with you. And as you know, year after year, AAC has gathered people with the thirst for identities, security technologies, and technology in general. And today we're going to talk about how AI might impact the future of I G A.

You know, some, some say the world is about to change in a fundamental way. And we may look at our time as the time civilization started a new transformative path leading to a future where people and machines work side by side. And given the LA the latest AI developments, it's quite clear that the genie is already out of the bottle and it's here to stay. And here's an interesting code that I liked. AI is everywhere. It's not that big scary thing in the future.

AI is, is here with us. And indeed AI is already impacting many of the market segments every day and will be more and more present in, in our daily lives. Even the C of Google said the revolution is coming faster than, than, you know, and we can see that by the huge adoption across companies because they cannot afford to stand steel.

Therefore, I g a cannot afford to stand steel either. And if we look at the current dynamics and the, the challenges we see with the current I g A solutions, well with the help of ai, even today, we can increase efficiency by automating many of the manual tasks and by eliminating repetitive processes that are now performed by humans, and we can, of course expect to, to reduce error. And now let's take a first quick peek at the agenda before jumping too much into the subject. And we're going to start off discussing where we are today and what challenges IGA is currently facing.

And afterwards, we'll touch upon the boundaries that we can observe in the current IGA solutions and how they could benefit from the help of ai. Then we're gonna make a short overview of a few AI I g a practical applications and developments. And finally, we'll consider a few possible challenges that we'll need to overcome in the implementation of ai. So let's dive in. So which are the IGA challenges today?

Well, companies are a part of a continuous transformation and they have to become more digital, more integrated with the cloud, with a bigger need for changing their processes. And on on top of that, we have more devices, we have more data, we have more users, everybody working from any, everywhere in mixed environments, the cloud, the remote work that and every, everything needs to, to adapt. And this of course, brings us at the forefront of significant changes and challenges.

And this transformation and complexity is proving to be challenging for organizations that also need to manage access and identities effectively without, you know, involving security risks. And due to this complexity, we see manufactured results. We see manual governance processes because the data is collected from so many numerous sources and establishing basic compliance seems to still be a challenge. So perhaps what we need is not only a new compliance culture and I g a to be available for everyone from anywhere, but also more automation, less manual work.

And that's exactly where the new technologies can, can bring value. So if we look example, for example, the traditional IGA solutions, we see limit limitations. We see struggles to keep up with the complexity of modern IT environments into providing, we see challenges in providing real-time visibility, insights and actionable. We see challenges in providing automation.

It's a, they have a lack of provisioning oversight. And we know that the, the importance of implementing a zero trust security model is now understood by, by everybody.

But, and zero trust assumes that all users, devices and systems are verified before being granted access. And now we understand that IGA solutions have a very difficult job to be able to ensure zero trust because we have this different resources everywhere that are living on premises or in the cloud. We have so many people that are now working remote. So it's quite difficult to provide real time visibility and insights into identity related risk into compliance issues.

It's hard to automate all the manual processes to continuously monitor for suspicious, suspicious activities and prevent security breaches before they happen. But as technology continues to, to develop and becomes more and more capable, I hope it will have means to provide organizations with more automated and data driven processes, which now if we look at the AI technology, I have one quote that I also liked is that Dave Waters concluded that predicting the future isn't magic, it's artificial intelligence.

And hopefully with the looking towards the future of AI enabled IGA solutions, we're gonna come with more automation, we're gonna come with better insights and visibility into the identity related traits and so on. So that's how I name them AI enabled IGA solutions. And if we look into these AI enabled IG solutions, we can see some interesting patterns. The latest ad advancements, for example, in computational statistics, particularly analytics can help organizations manage data complexity and deliver more easily comprehensible outputs.

And this in turn can reduce the chan chances of, of errors and enable humans to make more informed decisions based on accurate insights. Therefore, AI enabled IGA solutions can be able to generate advanced analytics to make predictions and provide real-time insights into compliance related issues. And as AI analytics and AI tech technology is gonna continue to, to evolve, organizations can leverage them to, to streamline more and to automate their, their I G A processes. So what else can we expect from, from the future of, of I G A?

So by incorporating AI and the recommendation engines into IGA processes, for example, we could suggest access controls or permissions for user based on the actions of similar users. For instance, if a, if a user A has a similar role and responsibilities to another user who has been granted access to certain resources, the system can, can recommend that the first user also be granted access to, to those resources.

And by leveraging recommendation engines, it's also possible to provide insights on least critical access needed for a user to, to perform his or her function or eliminate over provisioned access and understanding who has access to, to what and how that access is or isn't being used. A system can provide access recommendation throughout an identity's life cycle. And this can occur from the initial access request throughout ongoing recertification campaigns.

Thus the use of recommendation engines can lead to more effective and efficient I g a processes with better access controls and of course, reduced security risks. And another interesting area to look towards is easier detection of abnormal behavior. In the era of AI enabled IGA solutions, organizations can leverage machine learning algorithms to identify unusual or abnormal behavior in data in real time this time.

And through analyzing access patterns together with user behavior, these solutions can pinpoint any data points that fall outside of the normal behavior without someone having to, to really look at the data and try to, to make sense of it. And this helps of course, identifying any suspicious user behavior and enables organizations to easily detect outliers and re reduce the, the security risks. So AI enabled IG solutions.

The, the idea is that they can handle massive amounts of data much faster than than humans. And they can provide instant alerts, they can take actions based on the analysis of data, they can improve response times. And ultimately what what we all expect enhance the, the security posture.

And as organizations continue to, to digitize their operations, AI enabled I g A solutions will become increasingly valuable because with the ability to automate decision making processes such as access request approval, access certification, recertification audits, AI can help companies to save time, reduce human error, improve overall efficiency in access control and manag managing digital identities.

These AI enabled solutions can automate also access provisioning and deprovisioning to, to, with offering better and more secure just in time access while eliminating the over privileging and increasing chances for, of course, in increasing this, the chances for for zero trust. And what we can see that with AI organizations can train their solutions to better detect and prevent potential risk violations as well. Allowing them to adapt their own set of rules, of course, without human coding or interventions, which it, it's again helpful in eliminating human human error.

And this results as well in zero maintenance of operations, self-healing risk violations that will offload huge amounts of, of the manual work. That is a challenge in nowadays. And of course, let's also talk at G P T because it is very popular today. It has a very big growth. And how cant G P t impact the, the future of, of iga? So as a part of an I AI enabled IGA solution, it can enhance efficiency by providing personalized assistance to users.

Resolving user access issues by, for example, answering frequently asked questions in real time can also assist in the automation process of assigning users to roles and managing their access permissions based on their job roles and responsibilities. And being a large language model, TE G P T can analyze and structure data such as emails and for example, by analyzing keywords related to to access requests can automatically route them to the appropriate reviewer for approval.

And additionally as well, judge G P T can assist in identifying and mitigating identity risks by analyzing user behavior and access requests to detect insider threats such as unauthorized access attempts and so on. But to wrap it up, surely as AI continues to, to develop and improve many other similar practical applications will be explored and and discovered in time. And as technology, as AI is a new technology organizations looking to, to implement AI in their I G A systems will inevitably encounter several challenges that for sure will have to be addressed.

And one such challenge from, from my perspective, is data quality and availability because you know that AI enabled IG solutions will require large amounts of data to train the, the AI and improve their algorithms. And meanwhile now we're, we have data from so many sources and so many, and it's so fractured, poor data quality or missing data or a lack of historical data can then negatively impact their accuracy and effectiveness. And now to ensure optimal performance of AI based systems, organizations must have access to high quality data and this data has to be regularly updated.

One other issue that could or challenge, let's not name it issue because it's gonna be, it's a challenge. It's in, in many cases now it's being adapted, but data privacy and ethical concerns, this constitute another important consideration. So organization must ensure that they are not collecting sensitive personal data, that they are not, they are following all the privacy regulations and ethics. And one other potential challenge that I found were to be, to be mentioned is integration with existing systems.

Because the AI enabled IG solutions, MA must be able to sim seamlessly integrate with existing systems, right? And data sources in order to, to be effective. And this may require updating or replacing existing systems to, to be able to fully take advantage of the AI enabled IGA solutions.

And now, because I need to wrap it up because we're almost out of time. In summary, while the benefits of AI enabled IG solutions are significant, organization will need to address the, the challenges we've mentioned and many others and in order to, to be able to fully realize their, their potential.

However, the advancement in AI and and machine learning will offer new opportunities to enhance IGA practices. And by leveraging the AI, IGA solutions will be able to, to provide faster data processing, complex analysis, higher granularity for better risk identification and mitigation in real time. And this can lead to more effective risk management, smarter access and auditing recommendations, increased automation of processes and operations, and ultimately of course, saving time, reducing cost, reducing human error in managing the, the digital identities.

And as the use of the AI is in IGA becomes increasingly important now because of the, the digital age organizations will have to consider, you know, starting to, to shift some resources in this direction in order to be able to, to stay competitive and reap the benefits of the, of the technology. So thank you so much for your time and attention everyone, and ready to open it up for question over.

Yes, thank thank you Christiana, please raise your hands.