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processes toward real-time data-driven processes and more flexible coordination among
departments. At a higher level, AI also enables firms to adjust their business models
through new forms of value creation such as large-scale personalization, intelligent
services, and real-time customer experience.
Accordingly, AI-driven strategic restructuring may be understood as the
simultaneous adjustment of resources, operations, and value-creation models under the
influence of data technologies and algorithms.
4.3. AI and the intensification of innovation
Strategic restructuring is meaningful only when it increases the firm’s capacity for
innovation. In this study, innovation is treated as an intermediate outcome that reflects
the extent to which the firm transforms AI and strategic change into new value. Under the
influence of AI, the intensity of innovation may increase in three dimensions: products
and services, processes, and business models.
AI supports product and service innovation through data analysis and customer
behavior forecasting, thereby helping firms better identify market needs and develop
solutions more suited to specific customer groups. AI also promotes process innovation
through real-time data-processing capability, which shortens cycles of analysis,
experimentation, and adjustment. At a higher level, AI supports business model
innovation by enabling firms to reconsider how revenue is generated, how value is
distributed, and how relationships are organized with actors across the ecosystem.
However, AI does not automatically generate innovation. Its effect on innovation
depends on the flexibility of the firm’s strategic structure in allowing experimentation,
learning, and continuous adjustment. Therefore, the relationship between AI and
innovation is inherently indirect and mediated by strategic restructuring.
4.4. AI and the formation of sustainable competitive capability
The ultimate goal of strategic restructuring and innovation is to develop sustainable
competitive capability. In the context of AI, competitive capability does not arise from
owning technology, but from the ability to use technology to learn faster, adapt more
effectively, and recreate value more efficiently than competitors.
AI first enhances the speed of strategic response through faster collection,
processing, and interpretation of market signals. At the same time, AI improves the
quality of value creation by enabling the adjustment of products, services, and customer
experience based on real-world data. In addition, AI generates accumulative capability
through continuous cycles of learning and improvement, thereby creating capability gaps
among firms.
Accordingly, sustainable competitive capability in the AI era should be understood
as the ability to maintain relative advantage through continuous learning, rapid
adaptation, and ongoing innovation.
4.5. Risks and strategic paradoxes in AI implementation
Although AI creates substantial opportunities for strategic restructuring and
innovation, its deployment also entails notable risks and paradoxes. First, firms may
invest heavily in AI without generating strategic value if the technology is not
accompanied by organizational change. In such cases, AI merely increases costs without
producing substantive transformation.
Second, excessive dependence on technology and data may lead to data distortions,
algorithmic bias, and weakened strategic judgment if appropriate oversight mechanisms
are lacking. Third, capability gaps within the organization may cause AI to intensify

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