Poor AI maturity in Swedish organizations

In recent years, artificial intelligence (AI) has become one of the most talked-about concepts in both the business world and the public sector. The debate is often characterised by grand visions and promises of how AI will revolutionise working life, streamline operations and create new value.

“Behind the headlines and the technological hype lies a different reality: AI maturity is still low in many Swedish organizations,” says Einav Peretz Andersson, who recently defended her doctoral thesis at Jönköping University (JU) on the role of AI in organizational change.

In her thesis, Einav has investigated how AI is actually used and integrated in organizations. While working on her thesis, she interviewed 246 small and medium-sized companies in the Jönköping County. The results show that there is a clear gap between rhetoric and reality.

"For several years, we have heard a strong public message that AI is everywhere. I also started my project with the assumption that most organizations were already quite mature in their use of AI. But when I worked closely with municipalities, manufacturing companies and industry leaders, I realized that this was not the case at all," says Einav, who recently defended her thesis at Jönköping International Business School at JU.

Gap between expectations and ability

Many organizations are still at a very early stage when it comes to integrating AI into their business.

“They may talk about AI or carry out small pilot projects, but they lack the structures, skills and strategic guidelines needed to use it effectively. The hype surrounding AI has grown much faster than the actual organizational capabilities required to implement it,” Einav notes.

According to her, it is precisely this gap between expectations and actual capabilities that poses one of the biggest challenges for organizations today. AI is not a technology that automatically transforms businesses; rather, its impact depends on how it is implemented, interpreted and used in specific contexts.

“Organizations that treat AI as a purely technical project often fail to capture its value, while those that combine technical development with learning, governance and strategic adaptation achieve better results,” says Einav.

AI transformation requires strategic investments

The challenges are particularly evident within the public sector. Many municipalities and authorities lack clear governance and expertise and have fragmented areas of responsibility, which limits their ability to use AI effectively.

“My research shows that many organizations, especially in the public sector, struggle with obstacles such as unclear governance, lack of expertise and fragmented responsibilities. These problems limit their ability to implement AI in a responsible and effective manner,” says Einav.

In the private sector, successful AI implementation hinges on the coordination of resources and investment in learning and collaboration.

“It is not enough to just use AI; organizations must build a coherent system around it. AI transformation requires strategic investments in expertise and governance, otherwise AI risks remaining a vision rather than a real force for change,” says Einav.

Read the entire thesis here External link, opens in new window..