Doctoral student in Organizational Implications of Artificial Intelligence Full-time NEW

Doctoral Student in Organizational Implications of Artificial Intelligence

The deployment of Artificial Intelligence (AI) has expanded rapidly across public and private sectors. AI-driven technologies—particularly machine learning algorithms and large language models—are becoming integral to knowledge creation, task augmentation, and business analytics. This shift has catalyzed a rise of AI ecosystems, which brings together AI startups, intermediaries, and established enterprises, fundamentally reshaping how employees, businesses, and entire industries function. However, while certain use cases offer efficiency gains, organizations frequently grapple with critical challenges, such as low returns on investment, output unreliability, and pressing ethical dilemmas.

This PhD project aims to critically analyze the organizational implications of AI. The PhD student may explore questions such as, but not limited to: How do organizations mitigate the managerial challenges stemming from the probabilistic nature of AI technologies? How will AI transform the modern industry; and what are the opportunities and risks associated with such transformation? Along with the Big Tech companies and AI giants, what role do startups and intermediaries play in a more responsible transformation towards AI-based economy?

The PhD position is a part of the Wallenberg AI, Autonomous Systems and Software Program – Humanity and Society (WASP-HS) is a national research program in Sweden. WASP-HS fosters novel interdisciplinary knowledge about AI and autonomous systems and their impact on humanity and society. WASP-HS enables cutting-edge research, expertise, and capacity building in the social sciences and humanities. For more information, see here.

Supervision: Emrah Karakaya will be the main supervisor and Mats Engwall will be the co-supervisor. Decisions are made on admission.

Admission requirements: To be admitted to postgraduate education (Chapter 7, 39 § Swedish Higher Education Ordinance), the applicant must have basic eligibility in accordance with either of the following:

• passed a second cycle degree (for example a master's degree), or
• completed course requirements of at least 240 higher education credits, of which at least 60 second-cycle higher education credits, or
• acquired, in some other way within or outside the country, substantially equivalent knowledge

The applicants must hold, or be in the process of obtaining, a Master's degree in Industrial Engineering and Management, or equivalent. In addition to the above, there is also a mandatory requirement for English equivalent to English B/6.

Selection: In order to succeed as a doctoral student at KTH you need to be goal oriented and persevering in your work. During the selection process, candidates will be assessed upon their ability to:

• independently pursue his or her work,
• collaborate with others,
• have a professional approach,
• analyze and work with complex issues,
• conduct qualitative research methods such as interviews and case-study approach,
• analyze academic literatures of innovation management, organization studies or/and information systems,
• understand how AI technologies function, and
• communicate in Swedish or willingness to learn Swedish for case study interviews.

After the qualification requirements, great emphasis will be placed on personal skills.