Having already started using generative AI on journeys toward a better digital customer experience, there are several things that companies need to consider in order to gain the most value from the technology.

AI is playing an ever-greater role in firms’ ability to deliver digital customer experiences. In our Digital Leaders in Sweden 2025 report, we placed extra focus on AI to highlight new insights and perspectives.

We interviewed three researchers with different AI specializations to examine the subject from new angles and a research-based approach. Hedvig Kjellström researches the development of methods to enable artificial agents to interpret human and animal behavior. Alexander Flaig’s latest research investigates how retail firms can effectively integrate AI to create business value and increase profitability. Fredrik Heintz researches AI and autonomous systems, focusing on learning, reasoning and trustworthy AI. We see many common themes in their research perspectives. To clarify our insights, they are divided into three themes.

Theme 1: Future applications and the significance of AI

The future role and use of AI will likely include broader application and integration into our daily lives. All three researchers envisage AI as an increasingly present tool, used by people to solve questions, challenges and needs. A clear example is AI assistants, which will function as personal helpers, performing tasks and making decisions for individuals.

Backend processes will include AI agents that communicate and collaborate with each other. It is vital to emphasize that AI will not replace humans but become a tool to streamline and enhance our work. The combination of humans and AI will be stronger than they are individually, creating new ways of working, solving problems and making decisions.

63,5%

A BearingPoint study found that 63.5% cannot differentiate between content generated by ChatGPT-4 and content written by humans.

The BearingPoint study describes how AI cannot replace the human factor in customer interaction today. A hybrid strategy is thus necessary to develop and utilize AI’s strengths and human capabilities. This approach should assign simple and repetitive tasks to AI, thereby augmenting human skills and enhancing overall efficiency.

Theme 2: Challenges and critical success factors for AI implementation

Broad AI implementation in organizations is a major challenge, not when creating prototypes but when scaling up usage. Success requires openness to change and a data-driven approach. Cultural and organizational barriers can delay AI implementation more than technical limitations. Resistance to change and traditional structures can block progress, making it essential to foster a culture that welcomes innovation. Firms need to dare testing AI solutions and adapting them to specific needs, which requires an agile approach.

Theme 3: Key to responsible AI usage

Developing AI requires technical and ethical oversight to ensure responsible use. One challenge is validating AI models that are “black boxes,” meaning at times we do not know how they make decisions or where the data goes. This lack of transparency creates risks, especially in sensitive areas like medicine and the judiciary, where incorrect decisions can have serious consequences. Careful validation of AI systems and the development of methods to increase transparency and control are thus crucial.

70%

of firms believe that by 2025, responsible and ethical AI use will be their priority, according to the BearingPoint study.

Companies need strict control over the output of AI models to ensure they function and fulfill their purpose. As AI models often train and adjust themselves based on new data, their output can change in time in ways that are hard to predict. This makes it critical to continuously monitor the models’ performance and results. To prevent such situations, companies need robust mechanisms to continuously monitor, test and fine-tune AI models, while ensuring they adhere to ethical guidelines.

Conclusion

AI can transform how companies create value and deliver customer experiences. It streamlines processes, reduces costs and improves customer interactions, especially in retail. The challenge is to move from prototypes to broad implementation. A big thank you to Hedvig Kjellström (Professor in the Division of Robotics, Perception and Learning KTH), Alexander Flaig (Associate Professor, Department of Management and Engineering and Department of Business Administration, Linköping University) and Fredrik Heintz (Professor and Head of the Division of Artificial Intelligence and Integrated Systems, Linköping University) for sharing their expertise and thoughts with us.

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