So, thank you very much, Jenny, for the introduction and a warm welcome for my end as well, to DIC 2019. I'm really happy that we have so many attendees this year. And as usual was the number 13 for me. So to speak, I'll do the opening keynote. The topic of this year is navigating identity and access management. Or I am into the digital age, connected consumers, connected business, connected data and AI subtitle roadmap for identity experts and tech leadership. And given that I only have 20 minutes, so it'll be more, a high level walkthrough. So a number of things which we think about which, which we feel are, are a very relevant. And when we look at how this entire thing is changing, as thought about the connected consumer, I think it's very important to start with taking a consumer customer perspective. So what is identity in the mind of the consumer and what are consumers looking for?
And when we look at sort of the identity in demand of the consumer, then there is a great wish to use only few identities, not hundreds of user and password combinations, but also to have some control about these identities. So bring your own identities, definitely one of these things, which are increasingly important, these things should work from every device seamlessly. They should be secure. Privacy is important for some, for some not. I think we shouldn't always assume that every one is really very privacy, a fine, some are, some are less, but it's an important issue. Identity and payment and commerce should walk hand in hand and we should get seamless access. Getting rid of this sometimes really cumbersome KYC processes, where could lengthy registrations and identification processes. Cetera. We want to reuse it. I think it's the mind of the consumer really is around that.
And it's also about to some extent, even about the work life convergence in the sense of the identity. So can I use the same sometimes if I want in the same way? So it's a different perspective than most what we really face when we are using identity in our day to day life. When we take a business perspective, things are somewhat different. A lot of what we see happening right now is around sharing data and even sharing AI. So it's not that there's one big AI. I think it's, we use AI in, in a lot of places and all that is based on data. So we need to share data to add intelligence. And when we go back quite a while, so around 1800, we had this industrial revolution, which was really about optimizing the single business that took quite a while. I think my microphone is not working anymore.
Okay, better again. We had done the trust in time era, starting around the 1980s, where it was really about networking businesses, but only sharing data for a little bit of your business, really only for the minimal data around the supply chain, so to speak. Then the new economy happened around 2000. Some of you might still remember that what, which was around sort of optimizing it service delivery, but it didn't fundamentally change things. It was trust that business tried to be a little bit more efficient in the way to do it within the three, four, oh, we still were more or less at optimizing a single business. And what right now is about to happen is really that businesses more and more rely on networks of shared data and share AI. So I have a couple of examples later in my talk, but when you look at what all is shared right now, data service and other stuff, this is fundamentally changing and businesses really are interchange because it's really about a totally different supply chain data.
And it services are part of the supply chain. If you look at a connected vehicle, you look at medicine, healthcare, cetera. It's not that one business does everything itself. It consumes a lot of services, which are based on data, and this is really changing the way we deal with data and other stuff. So that actually means we are at the end of siloed data, we need to think about shared data and shared APIs because data is really the fuel of what is happening here in this transformation of businesses. So we many, many years ago started with files. Then the databases came into play big data, but all that was really more within the enterprise from a perspective, then open data started to happen with the APIs, but what you really need today is we need to make data a service. We need data to become available as a service that can be monetized, that can be shared, that can be used for various purposes in our business.
And this is a, also one of the fundamental shifts we are observing, which then allows us really to, to, to do different business, use new digital services, but it requires us also to unlock the data. And I think there are, from my perspective, there are various drivers for unlocking that data. So when we look at this data from different perspectives, from different angles, we have to use this and the users are individuals and some of them don't want their data being locked. Others don't care much, but some really want to get more control. And this is a long term topic of EIC around self identity and other stuff, personal data stores, some want it, we have on the other hand regulations. And when you look at regulations and about identity, we frequently think about GDPR only, but there are other regulations which are about liability for stuff you deliver cetera, and who owns data frequently takes some sort of liability and not every business, if there's, if you think it's, SRU that perspective, which also is part of regulations on laws might be willing to take too much liability for all the data.
So locking data can be a risk in some sense, and from a business perspective, there's the thing around balance of power. When you look at it from business perspective, being dependent on sort of a monopoly always is a challenge. It's a risk. So it's nothing the interest of most businesses that very, very few Monopoli own. Most of the data that is a really big business risk. So unlocking data is essential from a business perspective. And we also see that in all these use cases we are looking at today, data becomes more and more autonomous. We have a lot of autonomous devices and other types of entities, vehicles, et cetera. And that also means we need to unlock data so that autonomous entities of whatever type can communicate with that autonomous services can access the data. And if we have data locked into silos that will not work, what does this mean for the way we do identity?
We do data and all that related stuff. And how does AI come into play here? AI, as I've said, is about AI builds on large amounts of data. That means it also requires to gather the data that requires also sharing and data and shared services, but also networking AI. And so AI basically builds on data. This data is used by some AI platforms. So we have these platforms which deliver AI services, which then work on that data. And these services are then sort of the, the, the baseline capabilities. So the platforms deliver the, the foundational things, text to speech, text recognition, the services then go into, for instance, text understanding. We yesterday evening had a case around understanding contracts and stuff like that, based on that the AI solutions, which then are delivered in some form to the user in an autonomous vehicle by text translation, by augmenting the view of factory workers and all that stuff.
And these things come together in fact, in networks, which can really change our, the way we work. So if you look at the connected vehicle, it's not a vehicle with one set of AI, but there's whatever, there's the GPS service. There are many, many other different services which come together. And in fact, we are approaching a network of these things, which also requires us to network and to share the data. Otherwise, all these new smart services will not work. So identity has to change. And when we look at this evolution of identity, then when go back a while, then we had this system perspective. So really user management accounts per system, etcetera, following that identity management. So in the more traditional sense came into bla, we synchronized accounts between systems at our provisioning workflow still have them, hopefully, hopefully have them finally also working well.
We focus on employee identities in that space Federation was sort of the next evolutionary stage. We approached. So networking with the partners, providing some single sign on some standard protocols becoming established over the past few years. And when you have been visiting EIC for a while, so consumer identity management became a hot topic a few years ago. It definitely is currently a very hot topic and supporting the consumer beyond the partners, beyond the employees is sort of the next evolutionary stage and the next step which we need to do in the context of this changing business of this shared business, where we share data, where we share services is that we also move towards public shared universal identity, supporting concepts, like bring your own identity, public universal identity provider standards, shared KYC. So not doing KYC processes again and again, and all the other stuff we need to do.
So this is in fact, the evolution of identity. And when we look at this new ecosystem, one of the essential things to to do right now is to segregate these areas. We need to segregate to be successful, need to segregate identities, applications, and data. And part of the shared data, part of the shared identity is that we segregated. But the fact that most of the applications still own include us. Their data, big data helped a little, but not really solved this. We need to make another step on this step is really that we understand their identities tied to the individual, not the application, the applications, which in fact are a set of services. So think microservice architecture. I touched it in a minute and data data in fact then is provided as a service. So don't mix the term application, service services, something fairly different than the application, which combines services.
If we segregate data, we make it reusable. We can use it in a variety of business contexts in a far more flexible manner. What we need for that are microservices. They deliver from an architectural perspective, the agility for the digital area. So what do microservices deliver to us? They delivered the agility, small services. We can deploy in a flexible manner services where we can orchestrate to react on business demand, which we can deploy cleverly. If we package them right where we support hybrid deployment models. If we do it right, it's not easy. And we have a couple of talks around that, how to secure microservices and other stuff, but we can do a lot of other things. They give us the flexibility. We can far easily rewrite a small microservice. Then we can rewrite a complex monolithic application. We can, if you do it right, become far more flexible.
We can grow gradually. We can move forward better, and we can reuse. We can reuse the same services for a variety of things. And if you look at how AI frequently is constructed, this is sets of services. We reuse for different purposes. We put together to our solutions, the AI solutions, which then end up in our business services. We deliver to our customers. When we look at identity, then from an it perspective in that new world, it's about and more from an enterprise centric perspective of it. Then it's about connecting everyone to every service. And then also something which goes beyond the way we commonly do it today, where we split a lot of disciplines, such as provisioning, access governance, Federation, and other services. It's about more thinking about how can we have one consistent identity service, which helps us connecting everyone. The employee partner, the consumer, to all these services, be it cloud federated, or legacy.
The consumers come in with different IDs, the partners federate, or we manage them. We are an identity API platform. We have, our employees might be still in our standard directory services. And we reach out, we are Federation, web single sign on proprietary APIs to the services. What we need to deliver is a couple of things which are not new to us. It's access management, it's the administration governance. It's the constant privacy and other services. And what we should do is we should rethink our entire IM architectures, our big pictures and think about what I tend to call an identity fabric. So we should have something which helps us in a consistent way to deliver the services. And it's not one service, it's a set of services, which allows us to connect everyone to all the service. That's the internal perspective. If we take a business angle to that, it looks slightly different from a business perspective. Again, it's about consumers. It's about partners. It's about employees. All of them play their role in the business.
On the other hand, we have certain things which are relevant businesses have those legacy. They have these new services around AI. They have the cloud services. They consume consumers are from a business perspective relevant because at the end, that's where the revenue comes from, but also where data, this new goal, so to speak comes from the partners are the channel supply or delivery. We have the employees, the operations part. So we have to cloud services, SA cetera. We have the AI services. We have the service and data, and we need to bring these things together as a business. Why? Because we need to deliver services, which help us earning money. And it's about these digital service them where it's about USAR periods, capabilities we consume as service. And this is where we connect, where we share stuff. It's not that we do everything ourselves. We consume as a business to be successful for new digital service.
We consume more and more of these services from external parties, from business partner, from cloud providers, as AI service, we need the identity for the onboarding, for the access, for the management of all the access for handling all the security aspects. And we need the data to deliver the services, but also to use and monetize these services. That is what we need to build these digital services for our digital business. So it's really about again, about identity, about services, about data, which help us to build the new applications, the new service, the new digital services for our digital business. So coming to an two quick examples, how these things come together, orchestrating data, identities, AI, and services. When we look at, for instance, healthcare patients, data anonymous, anonymized, patient data, research data, and more data flows into that. We have a lot of identities we need to manage.
We have more and more AI capabilities, decision support for symptoms cause for therapy, radiomics, purpose-built drugs and other stuff. And we have to new services, the telemedicine, new therapies, customer therapies. We only can deliver the services if we bring together the data, the identity and the AI. If we look at the mobility space, again, it's a lot of data driver drivers vehicle, many others it's about the identities. And there are so many different identities in that space. We have D I AI a lot of this autonomous driving energy management for electric vehicles, traffic management, many, many different services. We bring together for this smart mobility thing. And then we can deliver the services only if we manage to bring together data, identity, and AI. So what are my recommendations very quickly connect your identities, not manage them yourself. It's their identity, not yours orchestrator services. And don't invent what already exists. Segregate your data from applications. Use the data instead of locking it, use AI as a service sync in on a network for AI and augment your users. That's what AI factually is that together will help you to create new digital services by connecting identities, services, data. And I, so digital business is connected to business. Thank you.
