The Impact of Artificial Intelligence on Strategic Technology Management: A Mixed-Methods Analysis of Resources, Capabilities, and Human-AI Collaboration

This paper investigates the integration of artificial intelligence (AI) into Strategic Technology Management (STM). While organizations increasingly invest in AI, many struggle to align these technologies with business objectives, leading to underperforming investments. The authors address this gap by exploring how AI can be systematically embedded into STM to improve roadmap formulation, resource allocation, and human-machine interaction.

The researchers employed a mixed-methods design, combining quantitative survey data from 230 professionals with qualitative insights from 14 semi-structured interviews with industry experts, including CTOs and AI architects. This approach allowed the authors to develop the AI-based Strategic Technology Management (AIbSTM) conceptual framework, which synthesizes technical, human, and organizational dimensions of AI adoption.

The study reveals that AI acts as a catalyst for strategic clarity, forcing organizations to define clear business purposes before implementation. AI is most effective at tactical roadmap tasks, such as defining strategic actions and implementation pathways, while human judgment remains essential for high-level strategic intent and timing. The authors identify a hierarchy of resources: computational power is increasingly commoditized, while proprietary data, specialized human talent, and robust governance are the true sources of competitive advantage. Contrary to visions of autonomous AI leadership, the research concludes that the most viable path is human-centric augmentation, where AI serves as a collaborative partner that handles foundational analysis while humans retain accountability and contextual oversight.

This research provides a prescriptive framework for practitioners to navigate the complexities of AI integration. By moving beyond the hype of autonomous agents, the study offers a realistic roadmap for organizations to leverage AI to enhance decision-making and strategic alignment. It highlights that the primary challenge of AI adoption is not technical, but rather the socio-technical and cognitive chasms that require deliberate organizational change and new governance models.