Competing in the Age of Algorithms: Rethinking Business Models for the AI Economy (in cooperation with QUT, Brisbane)

Thesis (MA)

Advisor(s): Timo Böttcher (timo.boettcher@tum.de)

Introduction

Emerging artificial intelligence (AI) technologies like machine learning, robotic process automation, and smart contracts enable new forms of organizational design based on algorithmic coordination and control. These "algorithmic organizations" promise benefits like flexibility, transparency, and resilience compared to traditional centralized hierarchies. They rely on networks of software agents to make decisions, allocate resources, and govern interactions.

However, effectively managing AI within and across organizations presents challenges. Important questions remain around aligning algorithmic systems to human values, managing risks from uncontrolled AI, and maintaining meaningful human oversight over automated decision-making. Additional research is needed on how to design algorithmic structures while safeguarding human interests.

Moreover, AI is transforming business models and enabling new cross-organizational collaborations and customer value offerings. As algorithms become more capable, companies are incorporating AI into their core operations and strategies. This is shifting competitive dynamics and requiring new inter-organizational relationships to develop and leverage AI capabilities. Digital platform ecosystems are emerging to facilitate data sharing, algorithm development, and AI adoption across firms.

This topic examines the organizational implications of increasingly pervasive and powerful AI systems. By integrating perspectives from information systems, organizational theory, AI ethics, and strategy, it provides insights into managing, collaborating with, and competing using AI in an algorithmic business environment. The research will contribute to responsible and human-centric algorithmic transformation.

Potential research questions:

• How are business models and competitive dynamics evolving due to increasing use of AI within, beyond, and across organizations?
• How can traditional companies transition to become algorithmic organizations? What are the main organizational design considerations?
• What governance mechanisms enable mutually beneficial data sharing and collaboration on AI capabilities between organizations? What risks arise in these partnerships?
• How can digital platform ecosystems incentivize and facilitate adoption of AI technologies across interconnected organizations?
• What new forms of business-to-customer as well as business-to-business interactions emerge? What opportunities and challenges do they give rise to?
• How can algorithmic organizations be designed to optimize not just economic efficiency but also environmental and social impacts?

Tasks:

• Literature review on algorithmic organizations and related topics
• Collect data from interviews, case studies, or surveys
• Analyze data through qualitative methods, qualitative comparative analysis (QCA), or quantitative methods
• Discuss findings and derive practical guidelines

 Requirements

• Interest in current topics of digital business models, AI technologies, and organizational design
• Interest in creating and publishing high-impact research
• High degree of autonomy and individual responsibility
• Above-average grades or other qualifications
• Structured, reliable and self-motivated work style

Further Information

The thesis is offered in collaboration with the Queensland University of Technology (QUT) in Brisbane, Australia. It is expected that students spend six months at QUT to conduct their research.

The topic can be adopted according to your interests. The thesis must be written in English. If you have any further questions, do not hesitate to contact me directly.

Please send your application including our application form, "Notenauszug" from TUMonline, and CV to timo.boettcher@tum.de. Please note that we can only consider applications with complete documents.