## 5 Discussion  
This study advances the understanding of low-code platform adoption by systematically synthesizing sector-specific challenges, benefits, and strategic trade-offs across industries with distinct technical and regulatory demands. Unlike prior works that generalize low-code applicability, our analysis reveals nuanced adoption patterns tied to domain-specific operational realities. In automotive and equipment manufacturing, LCDPs demonstrate transformative potential in bridging legacy systems with modern IoT ecosystems, enabling rapid prototyping and cross-departmental collaboration. However, our findings challenge the assumption that low-code democratization universally translates to mission-critical readiness. In highly regulated sectors like aerospace and energy, organizations prioritize hybrid architectures--combining low-code agility with traditional coding rigor--to reconcile compliance requirements with development speed. This insight refines existing narratives by emphasizing context-dependent adoption strategies over one-size-fits-all solutions.  
A key contribution lies in identifying the symbiotic relationship between low-code platforms and emerging technologies such as AI and edge computing. While prior research acknowledges these trends in isolation, our sectoral analysis demonstrates how their integration addresses specific limitations: AI-driven automation mitigates low-code's customization gaps in complex workflows, while edge-native deployments resolve latency bottlenecks in real-time industrial analytics. For instance, automotive predictive maintenance systems leveraging edge-enabled low-code apps achieve faster anomaly detection compared to cloud-centric approaches, a distinction underexplored in existing literature.  
The study also redefines the discourse on technical debt in low-code development. Contrary to frameworks that equate rapid deployment with maintainability risks, our observations highlight governance-driven success cases--such as Duke Energy's hybrid SCADA system--where structured oversight balances citizen developer empowerment with architectural integrity. This underscores the need for adaptive governance models tailored to industry-specific maturity levels, a dimension often overlooked in generic low-code evaluations.  
Operational efficiency gains, while significant, are contingent on overcoming interoperability and usability barriers. For example, our comparative workflow analysis illustrates how low-code reduces manual coding efforts but introduces new dependencies on platform-specific ecosystems. Organizations like Scania and ENEL mitigate these risks through open-source integrations and tiered training programs, strategies that provide actionable blueprints for practitioners navigating vendor lock-in dilemmas. These examples advance the field by translating theoretical interoperability challenges into pragmatic mitigation pathways.  
Ultimately, the research positions low-code not merely as a development tool but as a catalyst for organizational evolution. By enabling domain experts to co-design applications with IT teams, LCDPs foster a culture of iterative innovation--evident in TSMC's AI-integrated semiconductor workflows and ENEL's edge-native grid optimizations. This cultural shift, coupled with technical advancements, redefines low-code's role from a tactical accelerator to a strategic enabler of sustainable digital transformation.