Q1. Could you start by giving us a brief overview of your professional background, particularly focusing on your expertise in the industry?

I have been in IT and IT transformational management roles for 25 years. At Accenture, I worked on IT transformation programs involving cloud security, data, AI, and ERP business processes. I'm currently the head of Enterprise Architecture, overseeing the enterprise architecture decisions for a large medical technology company in the Nordics.

Q2. What current trends in the IT industry do you think are most significantly impacting enterprise architecture today?

I want to cover four things.

• Rapid change

Technology and ways of working are changing very quickly, and that, together with global uncertainty when it comes to trade and it comes to doing business regulations, security, and time to market. These are all challenges that the business faces and that directly impact the speed at which we must make enterprise architecture decisions.

• Data

It's about gaining an understanding of how to combine fragmented data into a meaningful whole effectively, and with that comes validation. To ensure that the data is trusted, we can have a trusted database for data services that underpins the business.

• Finding people

This is about capabilities in enterprise architecture, encompassing end-to-end thinking, understanding of the technology landscape, and solution options available to companies.

• Regulation and security.

It's about staying on top of the ever-changing regulations and security, as well as understanding how this impacts your technology decisions.

Q3. With the rise of generative AI, how are you assessing its architectural implications and risks? Please give some examples of some organizations that are doing it.

AI is going to have a significant impact on the way we work, including how we interact with processes, data, and people. We are currently evaluating the use of AI in specific use cases. So, setting up or agreeing on use cases with the business.

It's essential, and then you work on how AI can support those use cases. To enable AI to function effectively, a robust data platform is critical.
If you don't have credible data and a credible data platform, your robot's AI solution will be ineffective. And it's also very likely to hallucinate and not have the right content; then, you know the result is going to be a disaster.

Firstly, get the use cases right; secondly, prove that AI can support use cases in a generative way. We're not talking about advanced automation. We're talking about AI and, thirdly, getting your data and platform services right. The fourth thing is to prepare people. So, how do you prepare for AI, and how do you prepare for it to come in and change the way you work? So, a good way to deal with that is to set up an AI center, which will provide central coordination of our AI activities. Otherwise, they're likely to burn through resources indiscriminately, resulting in a disorganized approach to using AI.

There are examples where organizations are embracing AI in a smart way, such as the banking and some airline industries, which are quite clever in their use of AI. However, it is not easy to pinpoint a company that is doing this well. I know for a fact that Klarna is a huge company that basically extends credit to customers. They have been able to automate 50% of specific customer service processes using AI. That has reduced the cost, but it's also improved the service. So that's just one example.

Q4. How do you assess the IT landscape to stay ahead of architectural decisions that can create a competitive advantage?

First of all, you need a clear view of your landscape, encompassing both process, data, and technical aspects. You need to have some good enterprise architecture tools at hand so you can gain a clear understanding of the current state. When you have that bird's-eye view, you can start implementing change management through impact assessments and other change-related activities. However, it's essential to have a clear understanding of the situation before embarking on that journey. And that's quite complex to have. So, get a view and then start making changes to that view.

Q5. Do you see any key players shaping the Zero Trust landscape, or is it still a patchwork of solutions depending on cloud and security posture?

It's a crowded market, but I still see the key players moving more into services offering like Fortinet, Crowd Strike, Check Point, Cloudflare, Okta, PAM side, Cisco, and Palo Alto, of course. Zscaler. And then you get to big integrators like Accenture and Capgemini.

Indian share players have combined their capabilities to form an end-to-end service offering.

You also see a lot of integrations already happening with things like ServiceNow, so you end up having instant response and change management in a coordinated way.

I think it's still quite fragmented, but the system integrators and the Indian Pure players are consolidating this into service Management offerings and umbrella offerings, which are making it less fragmented.

Q6. How do you evaluate when AI solutions are genuinely adding value versus just riding the hype?

This is related to the use cases again. Therefore, it's essential to have a clear use case, allowing you to evaluate whether AI can support you in achieving your goals and ambitions. You will quickly realize whether it's hype or real. There's a lot of hype out there. There are numerous small players. However, there are also numerous benefits to the right use cases. So again, the use case is critical.

Q7. If you were an investor looking at companies within the space, what critical question would you pose to their senior management?

Enterprise architecture enables the provision of an assessment or a bird's-eye view. That's very important and ensures that enterprise architecture solution technical architects are always involved in the decision-making process so that you move away from just having financial and process people making decisions. It's very important to have a solution, a technical architect, and an enterprise architect in the decision-making process when you make investment or change decisions.

Having the tools and the processes behind that is something that I think a lot of companies would appreciate.

The support in creating that platform/base. For security, everything has to start coming together, so I think there is an increasing demand for end-to-end managed services.

There is a lot of focus on reporting, and there will need to be more focus on remediation. The business continuity plan is not all about diagnosing and reporting security incidents, but it's about recovering from those events. And AI is all about the storming phase.

Understanding the use cases. Packaging those use cases and having AI support them would be very beneficial. But right now, it's all in the storming phase. It will eventually become the norm, and it will become an integral part of day-to-day business. At that point, having a package solution for specific use cases will be a significant benefit. And those can be industry-specific, of course.