Successful deployment of AI is mostly about people, collaboration and adaptation
Organizations that want to successfully deploy artificial intelligence (AI) should focus less on technology and more on how AI is embedded in daily work. This is according to Ines Baer's research on the practice of AI management within organizations.
Although AI is increasingly being used in both public and private organizations, many projects fall short of expectations or lead to unexpected consequences. Baer shows that these problems stem not so much from technical shortcomings, but from how organizations manage and integrate AI into their operations.
Baer examined how organizations develop, implement and align AI systems with their goals, work processes and values. In doing so, she used both literature review and extensive field research within a public employment organization.
Not a one-time implementation project
An important conclusion is that managing AI is not a one-time implementation project, but an ongoing process. Organizations must continually weigh technological opportunities against organizational needs and societal consequences. AI systems regularly turn out to create new opportunities, but also cause unforeseen effects that only become visible during use.
According to Baer, it is therefore insufficient to draw up an AI strategy in advance and then implement it. Success depends on ongoing collaboration between different experts, such as managers, IT specialists, policy makers and end users. In addition, organizations must be prepared to adapt systems as circumstances or needs change.
Carefully management
As AI is increasingly used in decision-making, for example within government organizations, job placement and service delivery, there is a growing need to carefully manage the impact of this technology. Baer emphasizes that investments must go not only to software and algorithms, but also to training, governance and an ongoing dialogue between technical experts and users.
Without such attention, AI systems risk leading to ambiguity, new risks or unwanted effects for workers and citizens. Baer therefore argues for a broader approach to AI that does not separate technology from the people, organizations and social context in which it operates.
The insights provide tools for managers, policymakers and technology professionals to deploy AI more effectively and responsibly. In doing so, organizations can better capitalize on the opportunities of AI, while simultaneously taking into account public values, work practices and societal interests.
Learn more about the dissertation