Generative AI (GenAI) is changing the way we work. But how can the hype be turned into sustainable benefits for businesses? Our interview provides the answers. Artificial Intelligence (AI) is fundamentally changing the world of work. Companies are looking for ways to use AI not only as a supportive tool to increase personal productivity, but as a true cross-organizational efficiency and innovation booster. Campana & Schott has already supported over 125 Microsoft Copilot projects for more than 100 customers and also uses AI internally in a targeted manner.

How have market requirements changed? What pitfalls should companies avoid with their AI transformation? And how can AI be meaningfully integrated into the workplace? 

Read the answers from Marco Heid, Principal | Head of Content & Collaboration, and Boris Ovcak, Partner | Practice Division Head Transformation of Work.  CS: If you want to communicate a technology convincingly, you have to master it yourself - in other words, you can't credibly represent what you don't know. So let's start with a practical question: Do you use GenAI tools in your daily work?

Boris Ovcak: Yes, definitely. In my case, or rather at CS, it's Microsoft 365 Copilot, among other things. I cannot imagine my daily work without the GenAI tools. Two simple but incredibly valuable applications make my daily work much easier. The first is the automatically generated meeting notes. They are especially helpful when I was unable to attend a meeting. I get a compact summary, can quickly capture important points, and review the recording if necessary. Previously, I had to ask colleagues for details or have notes sent to me. Second, the ability to quickly access relevant information prior to customer meetings. A simple command like "Show me all the relevant business information about customer X" saves me a lot of time in preparation.

Marco Heid: Yes, I use Copilot intensively. The meeting summaries are a great efficiency gain. But I also find the AI-supported drafting and coaching function in MS Outlook particularly helpful. Especially when writing in a foreign language, Copilot helps me to refine my communication. This improves the quality of my writing, shows my clients that I value them, and makes me more confident in the long run. I also use AI to prepare for workshops - for example, to create agendas or structure content from previous projects.

CS: Let's take a look at Campana & Schott. As a technology consultancy, we not only support our customers in the implementation of Microsoft Copilot, but have also actively promoted its use within our company. What was the implementation like, what challenges did you face, and what lessons did you learn?

Boris Ovcak: The decision to use GenAI was a strategic one. We wanted to make our processes more efficient, improve the quality of our work, and reduce administrative tasks. At the same time, we wanted to learn first-hand how GenAI applications and Copilot work in the real world so that we could incorporate this knowledge into our consulting projects.

Marco Heid: We structured the process similarly to our customers: First we created the technical and organizational requirements, then we tested them with a pilot group, and finally we drove scaling. Today, almost 80% of our employees are familiar with Copilot's GenAI technology, thanks to a comprehensive enablement program with training and communities.  

The biggest challenge was balancing the different interests: Many wanted a license as soon as possible and were impatient, while at the same time we had to ensure that all governance and compliance requirements were met. Thanks to transparency and a structured project approach, we were able to achieve this balance.

CS: And as a result, would you say that GenAI has positively changed the day-to-day work at Campana & Schott?

Marco Heid: We see a high level of acceptance in our organization. Copilot has significantly accelerated and simplified our customer communication in sales and consulting. The technology helps us to improve our service concepts and facilitates the preparation and follow-up of meetings, to name just a few examples.  CS: Developments in the field of AI are advancing rapidly. You certainly feel this in your daily work. Looking back over the past year: How has collaboration with our customers changed in this area

Boris Ovcak: The market dynamics of the last 12-14 months have been unprecedented - almost greater than the sudden boom in remote working during the pandemic. A year ago, the focus was on pilots, early governance and proof of concepts. Today, companies are faced with the challenge of scaling GenAI and Copilot. The focus has shifted from time savings to real, measurable business impact. To achieve this, AI solutions need to be more deeply embedded in operational processes.

Marco Heid: I think at the beginning, many companies were still in the process of understanding the basics and doing their first experiments with generative AI. Now we are seeing mature implementation projects. The discussions are less about "What can this copilot actually do?" and more about "How can this copilot transform our core processes? Many customers are looking at AI solutions not just as a productivity tool, but as a strategic resource for innovation and efficiency.

CS: Many companies have now tested GenAI in small pilot projects and have seen initial effects - especially in terms of the time savings for individual employees that you mentioned. However, the next step of deploying the solution enterprise-wide and leveraging it for real business impact is something that many are hesitant to do. Why is that?

Marco Heid: The tipping point usually comes when companies see concrete, measurable benefits that align with their strategic goals. A good example is a large financial services company that started with a small pilot of Microsoft Copilot. A detailed business value analysis revealed that the technology was not only saving time, but also significantly improving processes.  

With more efficient access to relevant information, employees were able to make better-informed decisions, which improved the sales approach to customers and increased the closing rate. At the same time, Copilot accelerated the processing of inquiries, allowing more customers to be supported without additional resources. The measurable ROI convinced the company to roll out Copilot company-wide.

The key to successful scaling is not only to save time for individual employees, but also to make the added value visible to the entire company and to integrate AI applications into existing processes.  CS: With over 125 Copilot projects at 100 customers, you have gained a tremendous amount of experience - and not all of it has been smooth. What do you see as the biggest challenges and typical stumbling blocks?

Boris Ovcak: At the end of the day, Copilot is just technology. If it is introduced without accompanying change management measures, it will often fail. Clear guidelines and change measures are needed so that employees know when and how to use Copilot in a meaningful way. Without this support, the potential often remains untapped.  

User enablement is a critical factor. Many companies underestimate the importance of clear instructions for the efficient use of new tools. We recommend dedicated adoption programs with training and support structures to ensure sustainable integration.  

At the same time, expectations need to remain realistic. Copilot is not a magic tool that solves all problems, but must be integrated into processes in a targeted manner.

Marco Heid: Another critical factor is compliance with regulatory and legal requirements. Compliance, co-determination and data protection in particular place high demands on the use of GenAI.  

It is therefore essential to involve the works council at an early stage and to jointly define a clear framework for the use of GenAI tools such as Copilot. At the same time, organizational and technical measures must be taken to ensure that the requirements of the EU AI Act are met - for example, by securely processing sensitive or confidential data. Only by proactively addressing these issues will companies be able to realize the full potential of AI and ensure its long-term success.