At this week's event “AI and the Future of Work – Job Security, Meaning, Participation” at the Evangelische Akademie in Frankfurt, I had the privilege of giving the opening lecture entitled “Artificial Intelligence and the Future of Work.”

In my keynote speech, I began by putting the current dynamics of AI development into context. The systems are rapidly becoming more powerful and are already surpassing human capabilities in certain areas of application. At the same time, their use in companies is increasing significantly: more and more organizations are integrating AI into their processes, and its use in the workplace is growing noticeably.

This reveals a nuanced picture of the effects. At the individual level, AI is increasing employee productivity, in some cases significantly. At the company level, however, these efficiency gains have not yet been reflected across the board in measurable productivity increases. In addition, there are increasing indications of ambivalent effects, such as quality risks or technostress.

At the same time, the increasing use of AI is having a substantial impact on the labor market. Existing job profiles will change fundamentally in some cases, tasks will be redesigned, and requirements will be redefined. It will therefore be crucial to systematically build new skills – from a sound understanding of AI systems and data-based decision-making abilities to critical reflection and control skills in dealing with algorithmic results.

The public sector faces increasing pressure to drive digital innovation to meet modern societies’ demands. Existing literature calls for systematic approaches to digital innovation in the public sector and a better understanding thereof. However, the public sector still struggles to foster digital innovation and often fails to promote explorative initiatives as a basis for innovation.

In a recently published research study, using a case study of a German consortium project, we investigated how public-private partnerships can promote digital innovation in the public sector. We did so by adopting the resourcing perspective and building on recent conceptual work on network resourcing.

Our findings revealed that the unique characteristics of digital innovation, as opposed to traditional forms of innovation, influence how public-private partnerships can effectively drive digital innovation. We identified decentralized, cross-sector digital innovation clusters as a critical factor for the emergence of digital innovation in public-private partnerships and theorized dissemination practices as an extension to network resourcing in cases of distributed innovation agency within networks of public-private partnerships.

I am happy that our paper “Digital Innovation in the Public Sector: A Resourcing Perspective on How the Public Sector Collaborates with the Private Sector” has been accepted for publication in Information and Organization and is now available online.

Artificial intelligence (AI) has made its way into the everyday work of many organizations. Hardly any other technological development in recent decades has been adopted so quickly and at the same time been the subject of such controversial debate. While proponents expect enormous productivity gains and new forms of value creation, critics warn of job losses, de-skilling, and increasing stress for employees. As is so often the case, the reality lies somewhere in between.

In this article, I classify current empirical findings on the performance and use of AI, analyze its effects on individuals, organizations, and the labor market, and derive implications for companies and employees.