The rapid growth of the automotive industry has raised significant concerns about the security of connected vehicles and their integrated supply chains, which are increasingly vulnerable to advanced cyber threats. Traditional authentication methods have proven insufficient, exposing systems to risks such as Sybil, Denial of Service (DoS), and Eclipse attacks. This study critically examines the limitations of current security protocols, focusing on authentication and data exchange vulnerabilities, and explores blockchain technology as a potential solution. Blockchain’s decentralized and cryptographically secure framework can significantly enhance Vehicle-to-Vehicle (V2V) communication, ensure data integrity, and enable transparent, immutable transactions within the supply chain. Additionally, blockchain strengthens authentication, secures digital identities, and improves data sharing, reducing the risk of unauthorized access and data breaches. Our contribution lies in the proposal to integrate Artificial Intelligence (AI) with blockchain technology to further improve security by refining cryptographic methods, automating key management, and bolstering anomaly detection. Despite challenges related to computational complexity, latency, scalability, and regulatory concerns, the combination of blockchain, AI offers the transformative potential to enhance the security, transparency, and efficiency of connected vehicle systems and their supply chains.

Supply chain digitalization has increased the need for reliable systems that support transparency, traceability, trust, and structured interorganizational information exchange. Electronic Data Interchange (EDI) remains widely used for standardized business transactions, while blockchain offers decentralized verification, data immutability, and stronger data governance. However, blockchain–EDI integration depends not only on technical compatibility but also on organizational capacity, partner alignment, financial resources, and regulatory preparedness. Existing studies mainly examine blockchain benefits and adoption barriers, with limited attention to readiness assessment before implementation. This study develops an analytical framework for evaluating organizational preparedness for blockchain–EDI integration in supply chains. Five readiness dimensions are identified from the literature: technological, organizational, partner, financial, and regulatory readiness. These dimensions are measured using a 0–5 scoring system, combined into a weighted readiness score, and linked to a logistic function that estimates integration success under different complexity levels. Deterministic simulation, Monte Carlo simulation, and sensitivity analysis are used to examine the model. The results show a nonlinear readiness-success relationship under assumed parameter values: low readiness is associated with limited estimated success, medium readiness forms a transition zone, and high readiness supports more stable estimated outcomes. The framework is positioned as a methodological readiness assessment model rather than an empirically validated predictive system. It provides a basis for future empirical calibration, pilot testing, and validation using organizational implementation data.